thesis final 3 - SINTEF...Number of pages (incl. appendices): Master Thesis √ Project Work Name:...

Faculty of Engineering Science and Technology Department of Civil and Transport Engineering

Date: 11 june 2012

MASTER THESIS (TBA4910, master thesis)

Spring 2012

Mignote Beyene

English title: Effect of Speed Reductions for Train Punctuality

Norwegian title Hastighetsnedsettelser Og Punktlighet

NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY DEPARTMENT OF CIVIL AND TRANSPORT ENGINEERING

Report Title: Effect of speed reductions for train punctuality

Date: 11 -06- 2012

Number of pages (incl. appendices):

Master Thesis √ Project Work

Name: MIGNOTE ABATE BEYENE

Professor in charge/supervisor: NILS OLSSON

Other external professional contacts/supervisors:

Abstract: The rail way sector has been losing market, required increased subsidies and failed to generate anticipated rate of return. Therefore there has been a strong interest to measure the performance of railway operators in terms of punctuality. It is evident that In Norway punctuality shows considerable variation; most of the line being in non-optimal condition, speed is frequently reduced. Such speed reductions are often highlighted as major causes of delays. This master thesis studied the actual delays occurring on the parts of the line between Oslo and Trondheim which have speed restrictions. In doing actual time, travel times and speed restriction magnitudes data have been collected along the line. Combining both qualitative and quantitative approach to research the master thesis have mapped and analyzed speed restriction zones along the line. Using restriction mapping, statistical tools and curve fittings, the analysis revealed that as long as there is sufficient data, uniformity and regular fluctuation of the time magnitudes data there is an increasing effect caused and trend displayed on the actual time taken in the presence of the speed restrictions. Furthermore the research has looked in to the magnitude based relationship between the lost time due to restrictions and associated deviations in travel time. These resulted in a strong correlation between deviation of travel time and magnitude of lost time due to restrictions.

Keywords:

1. Speed restriction

2. Railway

3. Lost time due to restriction

4. Devaition in travel time

_________________________________________

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Preface This report is a result of a Master thesis TBA4910 in Project Management at the Norwegian

University of Science and Technology (NTNU) in Department Of Civil and Transport

Engineering in the spring of 2012. The report analyzes the effect of speed restrictions on

travel time there by its ultimate effect on delays and punctuality.

I would like to thank my supervisor Professor Nils Olsson for his invaluable guidance in

choice of the thesis thematic area and in further project work without his input this project

would not have come to reality. I would also like to extend my gratitude to Per Magnus

Hegglund from Jernbaneverket for his data supplements and assistance throughout the

project work process. Last but not least I would like to thank my wife, Mahlet, for her love,

support and patience during the past two or so years it has taken me to graduate. I would

like to thank Tizita and my parents for their unending love and support.

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Table of contents Preface ....................................................................................................................................... iii

Table of contents ........................................................................................................................ v

List of Tables ..............................................................................................................................vii

List of Figures .............................................................................................................................vii

Chapter one ................................................................................................................................ 1

Introduction ................................................................................................................................ 1

BACKGROUND ........................................................................................................................ 1

Overview ................................................................................................................................ 2

Data collection .................................................................................................................... 3

Research questions ............................................................................................................ 3

Method of attack ................................................................................................................ 4

Limitations .............................................................................................................................. 4

Outline of the report .............................................................................................................. 5

Chapter 2 .................................................................................................................................... 7

Literature study .......................................................................................................................... 7

The Norwegian railway network ............................................................................................ 7

Punctuality .............................................................................................................................. 8

Punctuality and Delays ......................................................................................................... 10

Variables affecting punctuality ........................................................................................ 10

Scheduling and running time calculation ............................................................................. 12

Traffic diagrams ................................................................................................................ 13

Recovery time as a component of total running time ..................................................... 16

Speed restrictions ................................................................................................................. 18

Permissible speed ............................................................................................................. 19

Temporary speed restrictions .......................................................................................... 21

Other types of speed restrictions ..................................................................................... 22

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Speed Restriction and the associated time calculations ...................................................... 23

Chapter 3 .................................................................................................................................. 29

Data Analysis ............................................................................................................................ 29

Data collected and restriction magnitudes .......................................................................... 30

The Train selection and the associated data ........................................................................ 32

The time calculations ........................................................................................................... 35

The effect of speed restriction on actual travel time .......................................................... 37

DOMBAS – FOKSTUA ........................................................................................................ 38

HJERKINN – KONGSVOL .................................................................................................... 39

LUNDAMO – LER ............................................................................................................... 40

MELHUS – NYPAN ............................................................................................................. 41

DRIVSTUA – OPPDAL ........................................................................................................ 43

FAGERHAUG – ULSBERG .................................................................................................. 44

GARLI – STØREN ............................................................................................................... 46

SELSBAKK – TRONDHEIM S ............................................................................................... 47

HJERNIK – DRIVSTUA ........................................................................................................ 48

OPPDAL – FAGERHAUG .................................................................................................... 50

LER – SØBERG ................................................................................................................... 51

NYPAN – HEIMDAL ........................................................................................................... 52

The correlation between restriction magnitude and deviation ........................................... 53

Conclusion ................................................................................................................................ 63

To what level of detail should such studies be done? ......................................................... 63

Relationship between speed reductions and delays ........................................................... 64

Trend based relationship ................................................................................................. 64

Magnitude based relationship ......................................................................................... 65

Appendix................................................................................................................................... 67

Bibliography .............................................................................................................................. 73

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List of Table Table 1 snapshot of the time restriction zones for week 1 2011 on Dovrebanen and

Rørosbanen .............................................................................................................................. 30

Table 2 summary of time loss due to speed restriction on the north line for week 1 2011 ... 31

Table 3 sample time record for train number 5733 between Alnabur and Bøn stations ....... 32

List of Figures Figure 1 the Norwegian railway network taken from (Sætermo, Olsson, & Veiseth, 2006) ...... 7

Figure 2 Punctuality measured as the percentage of punctuality to the final destination

(Olsson et.al 2010). .................................................................................................................... 8

Figure 3 componential tasks of scheduling and their relationship adapted from PESP model

(Liebchen & Möhring, 2007) .................................................................................................... 13

Figure 4 Horizontal traffic diagram (taken from Pachl 2002) .................................................. 14

Figure 5 Vertical traffic diagram (taken from Pachl 2002) ....................................................... 14

Figure 6 sectional view of vertical traffic diagram taken from the Norwegian Railway

infrastructure administrator Jernbaneverket website............................................................. 15

Figure 7 Components of total running time ............................................................................. 16

Figure 8 speed curve adapted from Pachl 2002 ...................................................................... 17

Figure 9 typical speed indicator taken from (Railway Group Standard, 2000) ........................ 20

Figure 10 deferential speed indicator taken from (Railway Group Standard, 2000) .............. 20

Figure 11 Permissible speed signing incase of diverging or crossover junctions (Railway

Group Standard, 2000) ............................................................................................................. 21

Figure 12 speed indicator in case of speed restrictions taken from (Railway Group Standard,

2000) ......................................................................................................................................... 22

Figure 13 deferential Speed indicator in case of speed restrictions taken from (Railway Group

Standard, 2000) ........................................................................................................................ 22

Figure 14 Illustration of Speed restriction zone and the associated velocities and

accelerations ............................................................................................................................ 23

Figure 15 Dombas - Fokstua travel time data and lost time due to speed restriction diagram

.................................................................................................................................................. 38

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Figure 16 Hjerkinn - Kongsvol travel time data and lost time due to speed restriction

diagram ..................................................................................................................................... 39

Figure 17 zoomed in view of speed restriction zone Hjerkinn - Kongsvol ............................... 39

Figure 18 Lundamo - Ler travel time data and lost time due to speed restriction diagram ... 40

Figure 19 Melhus - Nypan time data and lost time due to speed restriction diagram............ 41

Figure 20 snapshot of the restriction zone Melhus - Nypan .................................................... 42

Figure 21 Drivstua- Oppdal time data and lost time due to speed restriction diagram .......... 43

Figure 22 snapshot of the speed restriction zone Drivstua- Oppdal ....................................... 43

Figure 23 Fragerhuag - Ulsberg time data and lost time due to speed restriction diagram ... 45

Figure 24 exploded views of the speed restriction zones Fragerhuag - Ulsberg ..................... 45

Figure 25 Garli – Støren time data and lost time due to speed restriction diagram .............. 46

Figure 26 exploded view of the speed restriction zone Garli – Støren .................................... 47

Figure 27 Selsbakk – Trondheim S time data and lost time due to speed restriction diagram48

Figure 28 Hjernik – Drivstua data and lost time due to speed restriction diagram ................. 49

Figure 29 Exploded view of the speed restriction zone Hjernik – Drivstua ............................. 49

Figure 30 Oppdal – Fagerhaug time data and lost time due to speed restriction diagram..... 50

Figure 31 Exploded view of the speed restriction zone ........................................................... 50

Figure 32 Ler – Søberg time data and lost time due to speed restriction diagram ................. 51

Figure 33 Detailed view of the speed restriction zone Ler – Søberg ....................................... 52

Figure 34 Nypan – Heimdal time data and lost time due to speed restriction diagram ......... 52

Figure 35 Detailed view of the speed restriction zone Nypan – Heimdal ............................... 53

Figure 36 plot of the deviation magnitude against respective time lost due to deviation ..... 56

Figure 37 percentage of deviation against lost time ............................................................... 57

Figure 38 scatter diagram of percentage of deviation against lost time percentage .............. 58

Figure 39 scatter diagram of percentage of deviation against lost time percentage on first

week basis ................................................................................................................................ 60

Figure 40 scatter diagram of average deviation percentage against lost time percentage .... 61

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Chapter one

Introduction BACKGROUND The transportation industry is one of the prominent role playing sectors in setting the

central hub of nation’s economy and supporting economic development by aiding the

production and distribution of goods and services (WEF, 2010). From the wide range of

means of transportation the railway segment contributes a lot in the field and is one of the

major role players in the industry (NHO, 2007). During the past few decades and with

today’s ever changing business milieu the railway sector had gone through dramatic

reorganizations and governance structural reforms (Carney and Mew, 2003; Vatn, 2008).

The Governance reforms had led to the adoption of new technologies, and had also

redefined relationships and acted as a catalyst for innovation in the way how infrastructure

is handled, operated and maintained (Sascha Albersa, 2005 ).

The rail way sector had took the attention of policy makers owing to the fact that it has

been losing market, required increased subsidies and failed to generate anticipated rate of

return (Nash, 2000). As a result there has been a strong interest to measure the

performance of railway operators in terms of punctuality. Punctuality is a critical issue in

railways as the provision of reliable arrival time most often out ways the provision of faster

journey with less certain arrival times (Harris, 1992).

It is evident that In Norway punctuality shows considerable variation and the official target

for several railway lines and train is yet to be met (Olsson et.al 2010). With this context in

mind efforts had been employed to provide a holistic explanation regarding factors

influencing punctuality (Olsson & Haugland, 2004).

As a component of punctuality analysis comes, the need for finding out the influences of

speed reductions. Railways lines have defined maximum speed, which varies along the line.

When the line is in non-optimal condition, speed is frequently reduced. Such speed

reductions are often highlighted as major causes of delays. The lost time as a result of a

TBA49, Master Thesis Master thesis Mignote Beyene, Spring 2012

2

speed reduction is calculated, but the calculation is based on optimal conditions. As a result,

it is often claimed that the effect of speed reductions is higher than official calculations

show. Thus it is necessary for the railway organizations to develop the way they organize

and carry out their punctuality improvement activities.

The master thesis will study the actual delays occurring on the parts of the line which have

speed reductions. This information can be summarized in a table or database. The

information will be used in the planning and prioritization of maintenance activities. Data

on both speed reductions and delays are available. The thesis will include a literature study

of punctuality and previous studies.

The actual effect of speed reductions can be analyzed based on punctuality data. One

reason we are interested in this analysis is to be able to show the socio economic effect of

delays along the line. We can then point to certain parts of the line that need special

attention. The resources can be allocated based on this information.

Overview

As this project is conducted in order to look in to the overall effect of speed restriction on

punctuality, due focus has been set in analysing the railway line from Oslo to Trondheim.

Punctuality data generated from the Norwegian railway infrastructure administrator

Jernbaneverket is used for the analysis and further implications. The analysis also takes in to

account the utilization of other company or experience based analysis methods. The scope

of the data collected was limited to the extent of available data generated by

Jernbaneverket. The generated data were punctuality data including the train number, date

of travel, arrival and departure time for individual trains on individual stations.

The data were a mix of both freight trains and normal passenger trains. The intention

behind taking in to account various train types is to widen the manifestation of the effect of

speed restriction and to trace in detail, its associated effect on various incidents of

happenings. Besides it is necessary to analyse statistical data which describes these

conditions from observed occurrences. Both ways (from and to) punctuality data will be

used to look in to the magnified effect of the restrictions uphill and downhill. The data


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collected from punctuality and speed restrictions will be used to further investigate the

relationship between the restrictions and their effect on delays.

Data collection

The data collection includes both primary and secondary data. The data collection horizon is

set wide so that it will give the sound base for the demonstration of the effects and

relationship between speed restrictions.

Primary data: The primary data will be the punctuality data generated by the Norwegian

Railway infrastructure administrator Jernbaneverket. The generated data is a recorded time

measure for individual trains in the year 2011 -2012 on individual travels. Besides the

associated weekly magnitudes of speed restrictions are inferred from the time plan of

speed restriction by the infrastructure handler.

Secondary data: in virtue of secondary data literature survey on theoretical backgrounds on

punctuality, delays and speed restrictions from books, journals, websites and other data

collection of written reports of company cases and country specific experiences is

conducted. The main data sources included:

Research journal articles - industry related journals such as Journal of Air Transport

Management, Journal of Transportation Planning and Technology and Review of

Network Economics,

Search engines and scientific databases: BIBSYS NTNU electronic library database,

Google scholar, Science direct, First Search, Transport and NTIS.

Websites of companies and governmental institutions – websites of the Ministry of

Transport offices of Norway, website of and publications from Jernbaneverket.

Research questions

The main objective of this study focuses on analysing the effect of speed restriction on

delays. In doing so the study tries to address the following research questions:

What is the relation between speed reductions and delays?

On what level of detail should such studies be done, such as for each train number,

week day, direction, train product, time of the year, etc.


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The first research question of the relationship between speed restriction and delays will be

addressed by reviewing literatures. Thereby efforts employed to explain the relationship

between speed reductions and delays will be reviewed. In addition the associated terms

and analysis methods used in this study will be highlighted in the light of literature review.

The second research question will discuss about determining the level of detail the study

should be set towards to, on the way of figuring out the effects. In doing so the appropriate

level of detail in the analysis in the likes of each train number, week day, direction, train

product, time of the year, etc. will be determined. In addressing the third research question

the study will analyze the available punctuality data and use plots and tables to look in to

the effect of the speed restriction and its contribution to specific delays given the

magnitude of the reduction.

Method of attack

The method of attack includes both primary and secondary data collection, literature study,

data analysis, interpretation and conclusion. As pointed above after data collection;

literature studies will aid as a tool in explaining the state of the art in the field under

concern. With that, the analysis will utilize various tools to illustrate the associated effects

between delays and restrictions. Thereby conclusions will be made based on the output of

the interpretations of the analysis. Basically this study holds a strong premises and

assumption related to the relationship between delays and speed restriction. Experience

and some studies have indicated that there is a hazy correlation between speed restriction

magnitude and delays. But it was difficult to illustrate this for a small set of data and low

magnitude of speed restrictions. Therefore this study works on the premise of finding the

fuzzy boundary above which a pattern of correlation comes in to manifestation. In doing so

physical inspection of trends on graphs and correlation analysis will be made on the

deviation magnitudes and the lost time due to restriction. Here analysis will be based on

day by day analysis , weekly analysis , peak point analysis and average analysis for

respective speed restrictions.

Limitations

This thesis thematic area is limited to looking in to the relationships and effect of speed

restriction and delays. Furthermore due to lack of weekly speed restriction and associated


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data the analysis is done on the line segment of Oslo to Trondheim concentrating on the

section of the line Dombas to Trondheim. In addition given the amount of time of six

months for the literature reviews, data collection and analysis; the thesis only studies one

freight train coming from Oslo to Trondheim. As there are few available researches and

publications specifically conducted on this subject matter efforts had been employed to

include relevant issues on the shelf.

Outline of the report

The report is presented in such a way that the first chapter discusses the core issues and

thematical areas of the thesis. The second chapter reviews and presents literatures coined

with the subject matter; which would go in presenting what have been done so far when it

comes to effect of speed restrictions on delays and restriction . As well the literature review

will discuss key terms and analysis techniques utilized in planning and computing of speed

restrictions. The third chapter will present the collected data for analysis and the actual

analysis conducted. The analysis is utilizes two method of attacks. The first approach

investigates the effect of the speed restriction on delays there by punctuality. The second

approach looks in to the relationship between the magnitude of the lost time and the value

of the associated deviation in the actual travel times. Finally the last sections will summarize

the main findings of the thesis and present the list of main materials and literatures used in

the progress of the thesis, in the appendix and bibliography sections.


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8

Punctuality

In the transportation sector service planning goes further beyond determining optimal

travel cost and duration. It extends further in to meeting customer requirements and

expectations. Studies have shown that these days in the transport sector punctuality takes

of critical significance (Hariss, 1992, Bates, 2001). In rail way service in addition to

smoothening operations punctuality is contributing a lot towards insuring delivery of quality

service. Train stations currently, being crowded with busy multi-platform sets, it is

becoming critical to have a clear understanding of the punctuality of individual travels

coming in and going out (Carvile, 2003). Punctuality is a critical issue in railways as the

provision of reliable arrival time most often out ways the provision of faster journey with

less certain arrival times (Harris, 1992).

It have been noticed that in Norway the railway system doesn’t only show variation but also

there is a declining trend 1 When it comes to punctuality from the year 2005 to 2010 (see

figure 2 below ). With this context in mind efforts had been employed to provide a holistic

explanation regarding factors influencing punctuality (Olsson & Haugland, 2004).

Figure 2 Punctuality measured as the percentage of punctuality to the final destination (Olsson et.al 2010).

1 Punctuality measured as the percentage of punctuality to the final destination, month by month from January 2005 to April 2010 for the country as a whole (TIOS Trafikkinformasjon og oppfølgingssystem). Figure 2 is taken from Driftsstabilitet på Jernbaneverkets nett - årsaksanalyser 2005 – 2010 Punktlighets- og regularitetsutviklingen, gransking av årsaker by: Nils Olsson, Andreas Økland, Mads Veiseth og Øivind Stokland

30

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120Langdistanse Mellomdistanse Lokaltog Oslo Godstog CN Flytog


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Hansen (2001) defines punctuality as a percentage of trains arriving or departing a given

location or station across the railway network no later than a specified time in minutes.

With similar connotation Rudnicki (1997) also presents punctuality as a state of a measured

value that explains a given known vehicle arrives or departs a specific point in a previously

set time. In extension Olsson & Haugland (2004) defines Train punctuality as the associated

deviation, majorly negative from the defined timetable. For instance in most European

railway companies the threshold for delay is equal to or less than 5 minutes; on the other

hand trains arriving less than 3 minutes late in Netherlands are considered to be punctual.

The limit might also narrows down to 10-15 seconds in case of Japanese train operators.

This means that punctuality is often taken as, an event of meeting a set of predefined and

anticipated deviations from target value in a schedule. Ultimately failure to meet

punctuality or set target will end up in delays in the total train journey. With this context in

mind about punctuality, we will further try to look in to how it is measured and what factors

affect punctuality or contribute to delays.

Punctuality is a critical issue in railways as the provision of reliable arrival time most often

out ways the provision of faster journey with less certain arrival times (Hariss, 1992). Harris

(1992) points out three major reasons why punctuality is being taken worse than it actually

is as:

Passengers tend to have selective memory of concentrating more on poor

performances on top of good once

More often passengers take late trains than punctual once

Train operators tend to avoid early running, as it might balance out late arrivals

Generally for train operators it’s of great significance to have a detailed understanding of

punctuality as it helps a lot in optimizing their economical resource deployment in line with

meeting the requirement and expectation of their customers. Furthermore it enables them

to monitor their timetables and travel patterns giving a window of opportunity to analyze

and depict more efficient way of running their operations.


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Punctuality and Delays

The two terms are most often mentioned as similar terms but have different meaning

although delay could be other version of punctuality. Given a train is not punctual, and had a

negative deviation from predefined target time then we call it delayed. Delays are measured

in time units whereas punctuality is expressed through percentage of numbers.

Primarily there are two types of delays but different authors use different terminologies and

scope of definitions in presenting them. Gylee (1994) uses the term primary and secondary

delays to signify delays with their size to impact. The primary once being, the most impacting

and the secondary once being shadowed by the influence of the primary once. In

conjunction Olsson & Haugland (2004) present the Norwegian version of delay classification

as primary and secondary delays. Whereby primary delays are caused by direct influence on

the train itself and secondary delays are most often caused by the impact of other delayed

trains on the first one. Correspondingly different authors use other terms to explain the

above delay types. For instance Gibson et al. (2002) uses exogenous and reactionary. Carey

(1999) uses Exogenous versus knock on delays to express similar phenomenon but with

further emphasis on the terms.

Variables affecting punctuality

From above discussions it is evident that having detailed understanding of punctuality has

great significance. Hence the next level of understanding will be defining various factors that

influence punctuality. There are various factors affecting punctuality. Hariss (1992) has

listed five variables that affect punctuality of trains and tried to investigate in to their

correlations to punctuality with case studies. The major factors listed were:

Length of train in carriage: length of a train is assumed to have influence in virtue of

time taken to go across up and down hills and accelerate to regain speed in case of

speed restrictions.

Previous number of station stops: this is more related to the lateness caused by

loading and unloading as the train stops more frequently.

Previous distance covered: here it is assumed that with increased distance traveled

the probability of encountering defective tracks and wreckage is high.


11

Age of the motive power unit: this is a factors more related to aging parameter

decreasing reliability of the train engine and power units

Track occupation: this is more related to secondary type of delays whereby delay or

failure of one train propagates in to other train delays on the congested and busier

tracks.

While making the regression analysis for these factors to look in to their correlation with

punctuality, Harris (1992) found out that only distance covered and train length were

statistically significant in determining punctuality.

Correspondingly Olsson & Haugland (2004) had made related investigation on factors

affecting punctuality which was a point of inspiration for this thesis research questions. In

their research they have used the Norwegian railway network near Oslo and the Nordland to

analyze the effect and correlation of certain variables to punctuality. The variables used

included:

Number of passengers and occupancy ratio: it was found out that number of

passengers with higher rate of occupancy and punctuality has a negative correlation.

With increased number of passengers, it was noticed that the trains tend to be not

punctual.

Infrastructure Capacity utilization : it was noticed that with increased capacity

comes increased punctuality

Cancelation and regularity: this showed that cancelation and punctuality have a

positive correlation, cancellation and delay being apparent at the same time.

Speed restriction: the correlation was found to be weak and sometimes negative

opposite to what is expected. This might be counter balanced by the 4% allowance

the Norwegian timetable takes in to account. This is the main thematic area of this

thesis; hence we will focus more in this area on the chapters to come.

Railway construction work: as expected during constructions period trains passing

by will tend to be less punctual due to jams and stop over’s.

Departure and arrival punctuality. Here the relationship and correlation between

departure delays and delays associated with arrival was investigated and it marked

strong correlation.


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Operational train priority rules

From the above mentioned and discussed factors which affect punctuality we will go in

depth to investigate the effect of speed restrictions on punctuality. This is because speed

reductions are often highlighted as major causes of delays. The lost time as a result of a

speed reduction is calculated, but the calculation is based on optimal conditions. As a result,

it is often claimed that the effect of speed reductions is higher than official calculations

show. Most often in Norwegian railway network time tabling, the 4% allowances counter

balance this phenomenon and it was difficult to purely notice the effects of the restrictions.

Besides train time table schedulers have a rule of thumb of adding 1 minute allowance per

every 100km the train travels. This might have also led to diminishing the contribution and

effect of speed restrictions on total travel time, hence punctuality.

There are various methods of measuring punctuality. For instance Rietveld et al. (2001)

mentioned the following lists of measurement methods:

1. the probability that a train arrives x minutes late

2. the probability of an early departure

3. the mean difference between the expected arrival and the scheduled arrival time

4. the mean delay of an arrival given that one arrives late

5. the mean delay of an arrival given that one arrives more than x minutes late

6. the standard deviation of arrival times

Olsson & Haugland (2004) also has cited other methods of measurements including the

travel time variability and Norwegian way of measuring punctuality at the destination

station.

Scheduling and running time calculation

Since scheduling is done in a greater picture for a long span of time and lots of trains’ passing

by numerous stations; at points the task becomes overwhelmingly difficult to compose.

Although scheduling encompasses by far a great deal of tasks the major specific components

are determinable. According to Pachl (2002) the main target of scheduling is to determine

the travel date, the route along the network, respective arrival and departure times and


13

maximum speeds for a given train running along the line. Most of these components are

determinable and could be monitor by data tracking along the path.

Going in to details scheduling in railway would infer additional tasks of network planning,

line planning, timetable generation, vehicle scheduling, crew scheduling, and crew rostering.

Although there is no distinct boundary between these interrelated tasks network planning

and line planning are more of strategic planning whereas vehicle scheduling and crew

scheduling have operational tendency (Liebchen & Möhring, 2007). In between these two

tasks lies, the timetable generation, this serves as a bridge between service and operation.

This is demonstrated diagrammatically in figure 3 below.

Figure 3 componential tasks of scheduling and their relationship adapted from PESP model (Liebchen & Möhring, 2007) In the coming sections due focus will be given towards scheduling related with timetabling.

Traffic diagrams Traffic diagrams or graphical route diagrams are schematical representations and overview

of pre-scheduled train traffic at varied intersections. The traffic diagrams have multi-function

in laying the basis for planning of railway traffic and serving as an essential document for

Network planning

Line planning

Crew Scheduling

Time tabling

Vehicle Scheduling

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16

Recovery time as a component of total running time Running time of a train is a predefined scheduled time set that defines the total duration of

a travel between departure and destination stations. Running time is composed of

componential time sets including pure running time between scheduled stops, the dwell

time at scheduled stops, recovery time and scheduled waiting times. This is illustrated in

figure 7 below.

Figure 7 Components of total running time The pure running time is a mathematically calculated or operationally recorded shortest

time that a train takes to cover the distance between departure and destination station.

Here it should be noted that the running time is computed without adding time lost due to

small delays and malfunctions. It is purely the time taken while the train is under operation

and running. The computation of pure running time involves the construction of the speed

curve and integration of the curve to determine the running time. Figure 8 illustrates a

typical speed curve constructed to visualize and further integrate on the course of

computing the running time between two given stops.

Pure running time Dwell Time

Waiting time

Recovery time

Total running time

Total Dwell time


17

Figure 8 speed curve adapted from Pachl 2002 The associated elemental movements of the train between these two stop points are

composed of acceleration, running at constant speed, run out and braking. There are

associate calculations of force, inertia, acceleration and so forth to determine the

componential curves in the speed curve. As it is beyond the scope of this study we are not

going to deal with them in detail. In general literatures indicate that the construction of the

speed curve is a difficult task to develop analytically (Pachl 2002). Therefore one needs to go

for a step by step approximation from a series of straight lines.

The dwell time includes the time that is usually elapsed while alighting and boarding

passengers on scheduled start and stop stations. Dwell time usually takes in to account

those additional minutes consumed in the case of technical checks and schedule margins

(Heinz 2003).

To compensate for small delays there will be additional times added on the total running

time which is termed as Recovery time. Depending on the train operators geographical

location or country of origin there different magnitudes of recovery time additions.

Depending on the reason behind the need for the additions and condition specific situations

Acceleration Constant Speed Run-out Braking

V

S


18

there are two types of recovery times. Pachl (2002) uses regular and special recovery time

terminologies to explain the situations.

Regular recovery time is the time supplement usually added to running time as a percentage

of the pure running time. As discussed above this magnitude might vary based on

geographical location and country specific situations. In most European railways the

magnitude of the regular recovery time lies in between 3% to 7%. The North American

railways take an allowance of 6 - 8% (Pachl 2002). Some schedulers often spread the regular

recovery time throughout the total line of travel whereas; others supplement it at the end of

the last scheduled stop or large intermediate stations.

Special recovery time is another type of recovery time supplement whereby the allowance is

targeted at compensating lost time due to construction on the line, maintenance and

restrictions related to track malfunctions. Unlike regular recovery time which takes

percentage allowances, special recovery time is added as a fixed supplement to the running

time.

The fourth component is the scheduled waiting time. This time addition is made so as to

align travel time of passengers on change over stations and to make up for scheduled

passing or overtaking. Most often the scheduled waiting time is by default included under

dwell time as a supplement.

Speed restrictions

Speed restrictions or speed reduction is one of the variables that affect punctuality of trains.

In the presence of speed restrictions both freight and passenger trains need to make

technical adjustments so as to make it through the speed restriction zones. The railway

groups’ standard GK/RT0038 (Railway Group Standard, 2000) defines speed restriction as “a

set out principles governing the signing and advice of permissible speeds, temporary speed

restrictions and emergency speed restrictions on running lines to ensure that train drivers

have sufficient information to control their trains safely”. Speed restrictions influence the

travel time of the trains in virtue of time taken so as to adjust to the limit placed by the

restrictions. At times when the train approaches the speed restriction zone the operators

need to decelerate to attain the placed speed restriction and have to keep the speed


19

constant throughout the zone. In addition while exiting from the speed restriction zone the

operator again needs to accelerate to regain the optimal permissible speed set. Enticed with

this there will be train category and operator experience dependent associated time losses.

Most often the time taken to pass a speed restriction zone is merely a pure physics

calculation, which we will see later in the upcoming sections. But there are scenarios of

varied intensity which are taken in to account when it comes to the retardation and

acceleration of the trains. Despite all this there still prevails a conditional time loss which

may vary depending on the context of speed gains across uphill versus downhill, freight train

versus passenger train, short train versus long train etc.

In the railway business there are various types of speed restrictions which might include

permissible speed, temporary speed restriction, emergency speed restrictions and weekly

operating notice.

Permissible speed

Permissible speed restriction is on schedule basis computed and infrastructure controller

approved maximum speed limits over a section of line, for each planned direction of travel

and specific to each type of vehicle allowed to use the line. This often takes in to account the

physics based calculations so as to come up with the attainable maximum speed enabling

train operators to have full operational flexibility and safety clearance to guide their train

across the line. The permissible speed is further used to calculate and compose specific

deceleration distances. GK/RT0038 defines the deceleration distance as “The minimum

distance at which a warning indicator (for a permissible speed) or a warning board (for

temporary and emergency speed restrictions) shall be positioned approaching the start of

the change in speed to which it applies in order to ensure that all trains have sufficient

warning to be able to conform to the reduction in speed”.

Permissible speed should be backed by continuous route signing that provides a speed

indicator at each point where the permissible speed limit varies and the need for warnings

arises. Speed limits are usually presented with signings displaying the information with clear

and unambiguous clarity to the train drivers. Such signings design is based on the country

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23

provide advice to the train driver about temporary speed restrictions and alteration in

permissible speed. The emergency restrictions are similar to the weekly notice but differ in

the context of their applicability. These types of restrictions are temporary restrictions;

which are more restrictive than they appear on the weekly notice and include those

restrictions note displayed on weekly notice. But still these restrictions could be traced from

updates and amendments to weekly notices. They appear to be more bounding even when

they are not shown.

Speed Restriction and the associated time calculations

Basically running time calculations will take more than simple physics computations to come

up with the determined travel time for a train across the line. The figure below

demonstrates a sample train movement between two stops having a speed restriction zone

in between them.

Figure 14 Illustration of Speed restriction zone and the associated velocities and accelerations The train first starts from station “A” and accelerates to attain the permissible speed Vp.

Starting from point “B” the train travels with constant speed Vp until it reaches the speed

Vp

D

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E

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G

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Speed Restriction

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24

restriction zone. At point “C” the deceleration distance starts and the train starts to slow

down to reach the speed restriction zone permissible speed Vpr. the Norwegian time table

developers take a deceleration rate of -0.7m/s2 in their computations. The speed restriction

zone starts at point “D” and the train travels at constant velocity of Vpr throughout the

restriction zone and again starts to accelerate at point “E” to regain its permissible speed Vp

at point “F”. The Norwegian time table developers take an acceleration rate of 0.5m/s2 in

their computations. From point “F” onwards it travels at constant speed of Vp until it reaches

point “G” and starts to slow down until it reaches the destination stop at Station “H”.

In case of constant speed zones the train can travel at the permissible speed and the

associated time calculation will be as simple as dividing the distance traveled by velocity. See

equation 1

T= ……………………………………………………………….. (Equation1)

Average Velocity = ………………………………………………………………………………… (Equation 2)

In the case of speed restrictions where by the condition of deferential speeds comes in to

play one need to take in to account the change in velocities and the associated acceleration

and decelerations. The following formulas become more significant:

S = ………………………………………………………………………………………… (Equation 3)

√ …………………………………………………………………………… (Equation 4)

We can now use figure 14 to calculate the total time taken between two stop stations “A”

and “H” thereby we can develop a common understanding of how timetables in case of

speed restriction are developed. First we need to segment the total time taken in to

componential times in line with prevailing motion mechanisms. We can develop the time

segments as


25

T Total = TAB +TBC + TCD + TDE + TEF + TFG + TGH ……………………………………………… (Equation 5)

The time taken between points “A” and “B” could be computed by using both equation 3

and equation 4. First we need to calculate the distance covered by the train using equation 3

from rest condition Vo= 0 m/s at point “A” until it reaches the permissible speed Vp at point

“B” assuming a constant acceleration rate of 0.5 m/s2 .

→ SAB = = m ………………………………………………………………………… (Equation 6)

Now substituting equation 6 in to equation 4 we can easily compute TAB as

→ TAB √ = √2 sec …………………………………………………………. (Equation 7)

The time taken between points “B” and “C” could be computed by using equation 1

assuming the train travels at constant speed Vp and the distance between reaching the

permissible speed and point of deceleration C SBC is known.

→ TBC = ∗ ………………………………………………………………………………………………… (Equation 8)

The time taken to reduce the permissible speed Vp at point “C” to the reduced speed Vpr at

point D is easily computed in similar way as we did for TAB except this time the initial velocity

is Vp and the deceleration rate is -0.7m/s2.

→ SCD = ∗ . ……………………………………………………………………………………. (Equation 9)

Substituting equation 9 in to equation 4 we can calculate TCD as

→ TCD = ∗ . / ∗ . / ……………………………………………………………. (Equation 10)


26

Given we have a constant speed along the speed restriction zone between “D” and “E” and

with knowledge about the length of the speed restriction zone we can easily compute the

time taken TDE along the restriction zone as we did for TBC.

→ TDE = ∗ ……………………………………………………………………………………………… (Equation 11)

For points between “E” and “F” the time taken can be calculated the same way as the time

calculation between points “A” and “B” except this time we have an initial speed of Vp.

→ SEF = ∗ . / .................................................................................... (Equation 12)

Substituting Equation 12 in to Equation 4 we can calculate TEF as

→ TEF = ∗ . / ∗ . / ……………………………….…………………… (Equation 13)

The time taken between “F” and “G” TFG could be calculated considering a constant speed

and knowledge of the distance between attaining the permissible speed again and the start

of the braking zone as:

→ TFG = ∗ ……………………………………………………………………………………………….. (Equation 14)

And finally one could compute the time taken to bring the train from the permissible speed

at point “G” to stop at station “H” , given a deceleration rate of 0.7 m/s as :

→ SGH = ∗ . / ..................................................................................... (Equation 15)

Substituting equation 12 in to equation 4 we can calculate TGH as

→ TGH = ∗ 0.7 m/s2 ∗ 0.7 m/s2 ……………………………….………………………… (Equation 16)


27

Therefore we can calculate the total time taken across the speed restriction zone and the

total time along the diagram demonstrated by figure 15 substituting the computed results

from equations 7, 8 10, 11, 13, 14 and 16 in to equation 5. In the above computations

involving the quadratic equations to calculate time, the negative outcomes should be

ignored as it doesn’t make sense to have a negative time value.

In case of other railway administrator setting different magnitudes of acceleration and

deceleration rates one can easily change the values utilized in the computation above but

the basic governing structure of computation remains the same.

One need to bear in mind as mentioned in the speed curve construction the above

computations only serve as the basis for the linear approximations on the development of

the speed curve. Otherwise every linear trajectory motions displayed are only ideally

attainable and depend on the experience of the driver, the type of train, the topographic

condition, the age of the engine and so forth.


28

Chapter 3

Data Analysis

This chapter will present the method of attack and the analysis of this thesis. The chapter is

structured in such a way that first it discusses the typical calculations related with speed

restrictions. In continuation it discusses the data collected and the associated speed

restrictions across the railway line between Trondheim and Oslo. The major analysis part

will constitute investigating the effect of speed restriction on delays and punctuality. The

analysis will focus on representative train samples on the route including both freight and

passenger trains. The analysis will try to fill the research gap on the concept of speed

restrictions.

The basic premises behind the analysis is lost time as a result of a speed reduction. The lost

time due to the restriction is calculated using the appropriate physics formulas, but the

calculation is based on optimal conditions. As a result, it is often claimed that the effect of

speed reductions is higher than official calculations show. In this virtue literature studies

have shown that the effect of these restrictions seemed to get less significance as they are

canceled out due to allowances and long distance of travel. Therefore this analysis attempts

to widen the sample size and concentrate on speed restrictions to look in to its associated

ultimate effect. Majorly the analysis part will look in to freight train sample and follows the

train along the line to compute the deviation in running time with as well without the

presence of speed restrictions. Further efforts will be employed to compare the deviations

and come up with a reasonable explanation for the noted situations.

In doing so Train number 5733 is selected for further investigation as this train runs between

Trondheim and Oslo. Furthermore the delays related to this train and its economical

implication has been issue of hot debate in the Norwegian parliament. The analysis will use

this train to illustrate the effect of restriction in the respective speed restriction zone and

further investigates the associated relative effect of speed restriction magnitudes on the lost

times.


30

Data collected and restriction magnitudes

As discussed in the literature review section experience of the driver, the type of train, the

topographic condition, the age of the engine and so forth influence the time taken to cover

the distance between stations on the line. Therefore railway time table developers usually

go for adding special recovery time to compensate for time loses due to these factors

mentioned.

But the extent to which theses recovery additions magnitude should be set without

undermining the effect of the speed restrictions remains debatable. In this thesis in line with

the Generated time Data by the Norwegian Railway infrastructure administrator

Jernbaneverket, we also have acquired data about magnitude of the speed restrictions on

weekly basis throughout the railway line from Oslo to Trondheim starting from beginning of

2011 until March 2012. These times are computed in the same way we illustrated in the

previous sections; therefore it simplifies the need for computing los times due to

restrictions.

Table 1 snapshot of the time restriction zones for week 1 2011 on Dovrebanen and Rørosbanen

Table 1 above displays a snapshot of the weekly time restriction zone on the north line from

Oslo to Trondheim for week 1 of 2011. The report is given in table format columns showing

the name of stations, the starting and end point of the restriction zone, the amount of time

lost in the zone, the restriction speed magnitude, the reason for restriction and the status.

Planlagte Ikke planlagte HastighetBane # Tidstap Avtale # Tidstap Nedsatt Årsak Tiltak Oppheves kostnad

Fra km Til km (sek) (min) (min) (sek) (min) til dato

0 0 .0 0 00:00 3 64.00 01:04 (Km/t)Fokstua st 361.380 361.580 1 31.10 00:31 60 Feil på spv bytte spv deler? jan 2011Hjerkinn st 381.910 382.100 1 26.60 00:27 60 Feil på spv kapping/bytte av deler jan 2011Lundamo st 514.830 515.020 1 6.30 00:06 40 avvikende spv signalteknisk 2011 0,1 mill

0 0.00 00:00 2 12.83 00:13Hamar - Løten 141.990 142.730 1 6.73 00:07 80 plo signal utflytting av innfelt 2011Opphus - Koppang 238.200 238.300 1 6.10 00:06 60 setning innflytting av spor 2011

2 136.60 02:17 7 163.10 02:43

STÅENDE SAKTEKJØRINGER I REGION NORDI hht T-sirkulære 1/2011 (T.heim) og 1/2011 (Hamar), samt ruteordrer

Dovrebanen

Rørosbanen

Nordlandsbanen


31

In addition to this the weekly speed restriction forms collected for the year 2011-2012 also

includes the summary of weekly time losses due to the speed restrictions (see Table 2

below). The summary is developed based on values from table shown above. This summary

also display the adjacent stations restriction zone lays in between, the planned and not

planned magnitude of time lost or delays occurred due to the induction of the speed

restriction.

Table 2 summary of time loss due to speed restriction on the north line for week 1 2011

Such similar data for the whole year of 2011 and three months of 2012 have been collected

detailing 72 weeks’ time loss data due to speed restrictions along the railway line between

Oslo and Trondheim.

In addition to the weekly time loss data due to individual restriction points, the time data

record for individual trains in the whole line between Oslo and Trondheim has also been

collected. These data includes Standard Arrival (STA_TID), Actual Arrival time (ATA_TID),

Standard Departure time (STD_TID) and Actual departure time(ATD_TID) records for

individual trains passing individual stations. This way it will be possible to monitor and follow

individual trains along the line and look in to the magnitude of change in time where speed

restrictions are placed. In line with the time magnitudes the station names and train

Strekning Planlagt Ikke planlagt Akseptert tidstap Totalt Kongsv - Elverum 00:00 00:15 01:30 00:15Hamar - Koppang 00:00 00:13 00:30 00:13Koppang - Røros 00:00 00:00 01:30 00:00Røros - Støren 00:00 00:00 01:00 00:00Dombås -Støren 00:00 00:58 01:30 00:58Støren - Trheim 00:00 00:06 00:30 00:06Trondheim - Hell 00:22 00:47 00:30 01:09Hell - Storlien 00:41 00:00 01:00 00:41Hell - Steinkjer 00:00 00:27 01:00 00:27Steinkjer - Grong 00:00 00:00 01:00 00:00Grong - Mosjøen 00:00 00:00 01:30 00:00Mosj - Mo i Rana 01:54 01:07 01:00 03:01Mo i Rana - Rognan 00:00 00:11 01:30 00:11Rognan - Bodø 00:00 00:11 01:00 00:11Ofotbanen 00:00 00:00 01:00 00:00Hele regionen 02:57 04:15 16:00 07:12

Tidstap for uke 1


32

numbers were displayed enabling the time calculation between stations a possibility. The

Table 3 displays the snapshot format of the sample data collected between consecutive

stations between Oslo and Trondheim. This data set is generated by the north line

administrative section of Jernbaneverket which tracks real-time data and stores in a

database, thus making generation of such data set possible up on request by interested

parties.

Table 3 sample time record for train number 5733 between Alnabur and Bøn stations

The Train selection and the associated data

From number of trains travelling between Trondheim and Oslo Train number 5733 is

selected as a focus of investigation for this thesis. Train number 5733 is a freight train

passing through the northern railway line it starts from Alnabur station in Oslo and stops at

Trondheim Station. This train was selected as a point of focus of the analysis for three

reasons:

UTG_DT TOG_NR STASJON_STA_TID ATA_TID STD_TID ATD_TID1/3/2011 5733 ALB 03/01/2011 20:31:00 03/01/2011 20:31:00 03/01/2011 20:31:00 03/01/2011 20:31:001/3/2011 5733 GRO 03/01/2011 20:36:09 03/01/2011 20:36:00 03/01/2011 20:37:251/3/2011 5733 HGA 03/01/2011 20:37:25 03/01/2011 20:38:00 03/01/2011 20:38:211/3/2011 5733 HØB 03/01/2011 20:38:21 03/01/2011 20:39:00 03/01/2011 20:40:021/3/2011 5733 LØR 03/01/2011 20:40:02 03/01/2011 20:40:00 03/01/2011 20:41:111/3/2011 5733 HAB 03/01/2011 20:41:11 03/01/2011 20:42:00 03/01/2011 20:42:381/3/2011 5733 FJE 03/01/2011 20:42:38 03/01/2011 20:43:00 03/01/2011 20:44:071/3/2011 5733 STN 03/01/2011 20:44:07 03/01/2011 20:44:00 03/01/2011 20:45:001/3/2011 5733 SDA 03/01/2011 20:45:34 03/01/2011 20:47:00 03/01/2011 20:46:281/3/2011 5733 LLS 03/01/2011 20:47:44 03/01/2011 20:49:001/3/2011 5733 LSD 03/01/2011 20:59:42 03/01/2011 21:00:00 03/01/2011 21:00:511/3/2011 5733 FRO 03/01/2011 21:02:06 03/01/2011 21:02:00 03/01/2011 21:02:471/3/2011 5733 LBG 03/01/2011 21:03:53 03/01/2011 21:04:00 03/01/2011 21:04:431/3/2011 5733 KLØ 03/01/2011 21:06:32 03/01/2011 21:07:00 03/01/2011 21:07:321/3/2011 5733 ASE 03/01/2011 21:10:13 03/01/2011 21:10:00 03/01/2011 21:12:481/3/2011 5733 LAL 03/01/2011 21:14:08 03/01/2011 21:12:00 03/01/2011 21:15:031/3/2011 5733 JEH 03/01/2011 21:17:01 03/01/2011 21:15:00 03/01/2011 21:17:581/3/2011 5733 HSR 03/01/2011 21:20:31 03/01/2011 21:19:00 03/01/2011 21:21:171/3/2011 5733 SAD 03/01/2011 21:23:00 03/01/2011 21:22:00 03/01/2011 21:23:351/3/2011 5733 DAL 03/01/2011 21:25:38 03/01/2011 21:25:00 03/01/2011 21:26:151/3/2011 5733 BØN 03/01/2011 21:30:00 03/01/2011 21:29:00 03/01/2011 21:35:12


33

First this train is a freight train; this enables to widen the parametrical range of investigation

of the study. Usually freight trains offer the window of opportunity to consider the effect of

speed restrictions in association with the load size on the train while the train passes

through the speed restriction zone. This issue takes in to account the extended effect of the

restrictions while the trains go along different topographies and landscape levelling. The

effect of the restrictions will vary when the train goes uphill and downhill as the ease of

respective accelerations and decelerations vary to great extent. It is usually considered

passenger trains; given the load size they carry, would take less time to accelerate than

freight trains which would carry some load way higher.

Secondly this freight train offers to great extent the opportunity to work on pure running

times and their additions, omitting dwell times and their allowances. Freight trains usually

have fewer stop stations or nothing at all except the loading and unloading stations or

crossovers. This means while analysing the time data one will be working most of the time

on pure running times avoiding the need to deal with dwell times and respective allowances

which would had been frequent on passenger trains. Passenger train stops almost on every

station for alighting and boarding passengers. This will bring in to play the need for

computing dwell times and allowances making the analysis of the whole line a complex

issue. In such situations it would be difficult to purely work with the effect of restrictions on

running times as allowances added to compensate dwell times might have extended effect

interfering in to allowances for restriction. Thus freight train is preferred and selected as

focal point to benefit from the advantages it offers and the level of analysis needed is eased

putting speed restrictions a singled out candidate of investigation.

Finally the freight train 5733 has been known for low punctuality issues. The low punctuality

trend associated with this train is known for its direct economic impact. As this train runs

majorly along the Trondheim- Oslo line the transported materials have higher economic

impact as they will be shipped further with ships to other destinations. Hence delay or time

lost by this train would have a chained economical effect to the economy as well to the

following shipment and the associated other means of transportation. Few years back this

train has even raised a subject of hot debate in the Norwegian parliament owing to the

chained economic impact associated with it. Hence working with this train and the effect of


34

speed restriction would give a clear and in depth understanding of the whole picture of

restrictions at its best.

Train number 5733 has been tracked all the way from ALNABRU station in Oslo to

Trondheim S in Trondheim. The major stations in between the start and stop stations in

sequential pattern included

ALNABUR – GRORUD – HAUGENSTUA – LØRENSKOG – HANABORG – FJELIHAMAR –

STRØMMEN – SAGDALEN – LILLESTRØM – LILLESTRØM N - FROGNER – LINDEBERG - KLØFTA

– ASPER – LANGELAND – JESSHEIM – HAUERSETER – SAND – DAL – BØN – EIDSVOLL –

MINNESUND – MOLYKJA – MORSKOGEN – STRANDLYKJA – ESPA – TANGEN – STEINSRUD –

SØRLI – STANGE – OTTESTAD – HAMAR – JESSNES – BRUMUNDDAL – RUDSHØGDA – MOELV

– BERGSVIKA – BRØTTUM – BERGSENG – LILLEHAMMER – HOVE – FABERG – ØYER –

TRETTEN – LOSNA – FAVANG – RINGEBU – HUNDORB – FRON – VINSTRA – KVAM – SJOA –

OTTA – SEL – BRENNHAUG – DOVRE – DOMBAS – FOKSTUA – HJERKINN – KONGSVOLL

DRIVSTUA – OPPDAL – ULSBERG – BERKAK – GARLI – SOKNEDAL – STØREN – HOVIN –

LUNDAMO – LER – SØBERG – MELHUS – NYPAN – HEIMDAL – SELSBAKK – TRONDHEIM S.

The total distance covered along one travel between ALNABUR and Trondheim S being

545.54 Km.

While tracking the train along the way time data of Standard Arrival (STA_TID), Actual Arrival

time (ATA_TID), Standard Departure time (STD_TID) and Actual departure time (ATD_TID)

has been taken in to consideration along a time range of 72 weeks. The actual and the

standard prefixes designate the real time off happening and ought to be planned schedules

respectively. In line with this the speed restriction zones and the respective magnitudes

were mapped throughout the line for the whole 72 weeks.

The mapping is done in such a way that the respective speed restriction zones have been

identified and the respective restrictions were place in between the adjacent stations to the

restriction zone. This will enable us in comparing and analyzing the magnitude and intensity

of the restrictions effect on the travel time between these adjacent stations. Thereby we can

infer implications and deduce conclusions in line with the computation of the standard time

and the actual travel time. With respect to speed restriction data, the obtained data set only

covers the line between Dombas and Trondheim S ranging 209.83 kilometers. This is


35

because of the fact that the generated data set were from the north line administrative

section of Jernbaneverket. The time table planners of the northern administrative section

are only responsible for administering the line from Trondheim to DOMBAS as far as the

route is concerned. Thus le the computation and analysis will be conducted for the line

mentioned above.

The time calculations

With the obtained time data for train number 5733 standard and actual times have been

computed for consecutive stations depicting the actual and standard travel times between

the stations. The formulas used included:

_ – STD_TID

_ – _ : _ _ _ _ The standard time is the planned time that the train takes to cover the distance between to

stations taking in to account optimal conditions, permissible speed and respective

allowances. Standard time usually remains constant throughout the years unless there is

generic change on the path followed or track set up. Whereas the Actual time is the noted

and computed travel time the train actually takes to cover the distance between two

adjacent stations from real time data records. Actual time between stations will vary from

day to day depending on different factors including the weather condition, the freight load,

the driver experience and so forth.

With this set up in mind on Microsoft Excel sheet the standard and actual travel times has

been computed between adjacent stations. In line with this the speed restriction zones were

mapped with their respective magnitudes along the line. This resulted in an excel sheet with


36

respective columns of departure date, the associated times, standard time, actual time and

speed restriction magnitudes (if there happens to be one).

While doing so 13 speed restriction zones were identified for the line between Dombas and

Trondheim S for the 72 weeks range. Each one of this restriction zones have their own

adjacent stations identified. The identified 13 restriction zones for Train 5733 along the line

during the span mentioned above included:

DOMBAS – FOKSTUA , HJERKINN – KONGSVOL , LUNDAMO – LER , MELHUS – NYPAN ,

DRIVSTUA – OPPDAL , FAGERHAUG – ULSBERG , GARLI – STØREN , SELSBAKK – TRONDHEIM ,

HJERKINN – DRIVSTUA , OPPDAL – FAGERHAUG , FOKSTUA – HJERKINN, LER – SØBERG and

NYPAN – HEIMDAL.

Having this in place the concentration of the thesis is now directed towards analyzing the

actual and standard time of the identified 13 restriction zones in line with the restriction

magnitude. In doing so, two approaches are utilized to aid the understanding and

implications of the computed data set for the given zones.

The first approach is to draw the three time sets; which are the actual time taken, the

standard time and the restriction magnitude, along a diagrammatic chart for individual time

restriction zones for the 72 weeks’ time range. This will enable us to have a close look in to

the effect of the speed restriction on punctuality or delays affecting the travel time. This

could be inferred from the pattern displayed on the chart by the actual time taken in the

presence and absence of the speed restrictions. What usually expected is the actual travel

time should go up than normal trends whenever there is an introduction of speed

restriction. Here note that the actual travel times will vary along the 72 weeks not only

because of speed restrictions but also due to other factors mentioned at the beginning of

this section. In addition the speed restrictions are distributed randomly along the 72 weeks.

Every day of the 72 weeks will not have a speed restriction in place. Some weeks or days will

entertain the restriction where as others will be set to the permissible speed. Besides the

restriction magnitudes will vary from time to time depending on the reason behind the need

for the speed restriction. Some restrictions associated with reconstruction of the track might

last few weeks whereas maintenance activities or temporary accidents might last only few

hours.


37

The second approach is to plot the magnitude of the speed restrictions together with the

caused delay or any change in time on the actual travel time compared to the standard time.

To do so one can look in to first the deviation between the standard time and the actual

time. Thus plotting the magnitude of time lost due to the speed restriction along the x- axis

and placing the respective deviation on the y – axis one can investigate in to the effect of the

speed restriction magnitude on the deviation. The premise is that with increased time lost

due to speed restriction magnitude there will be increased travel time. Thus a strong

correlation trend between speed restriction magnitude and delays or lost time is expected.

This approach will ultimately enable us to detect if there is a correlation between the speed

restriction and the associated lost time.

Therefore the two approaches will enable us to understand and investigate in to first, the

effect of speed restriction on actual travel time and secondly if it does have effect, then to

what extent restriction magnitude affects travel time and to what level they correlate to

each other.

The effect of speed restriction on actual travel time

To understand the effect of the speed restriction on actual travel time we will take the first

approach. This approach is designated by plotting the three time sets; which are the actual

time taken, the standard time and the restriction magnitude, along a diagrammatic chart for

individual time restriction zones for the 72 weeks range. This is conducted in order to see if

there is any effect caused or trend displayed in the presence and absence of the restrictions.

With this context in mind a diagrammatical chart has been plotted for individual restriction

zones each having the time magnitude on the y-axis and the respective dates of the 72

weeks along the x- axis. The magnitudes on the y-axis will represent the three magnitudes

of standard time, actual time and the speed restriction magnitude with a notation of

individual series. In the coming sections we will go through the individual speed restriction

zone plotted diagrams and investigate in to and discuss the associated trends and patterns

displayed. From the inferred implications the first approach will deduce a concrete

conclusion on the effect of the speed restrictions on actual travel time on the basis of the

patterns displayed.


38

DOMBAS – FOKSTUA

The distance between these two stations runs for a length of 18.61 km. while mapping the

speed restriction zone it was found out that there are three speed restriction zones between

DOMBAS and FOKSTUA. These restrictions have a speed magnitude of 0:00:30, 0:00:31 and

0:00:52 seconds. The restrictions run for 19th and 20th weeks of 2011, first week of 2011 and

week 35 of 2011 respectively. The actual time, standard time and the mapped speed

restriction magnitude are plotted; for the time range of 72 weeks starting from first week of

2011, on Microsoft excel as shown in figure 16 below.

Figure 15 Dombas - Fokstua travel time data and lost time due to speed restriction diagram

From figure 16 we can see that the actual travel time varies along the line in random pattern

fluctuating from higher to lower values regardless of the presence of the speed restriction.

At some points it even goes below the standard time. This could be a result of unbalanced

special recovery supplements and not custom tailed allowance magnitudes laid over the line

resulting in misinterpretation of the standard time. Thus at some point the train might pass

by ahead of the scheduled time, but most often it gets delayed more than the 4% allowance

added. When it comes to the effect of the speed restriction on travel time there is some sort

of paternal uniformity on the second restriction zone and the highest travel time deviations

of the whole time range have been noted on the third restriction zone. Thus even though it

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40

looking in to figure 17 we can see that the varaibility in the actual travel time is patternal

with the exception of some pick points. In most of the data ranges the actual travel time lies

below the standard time. Looking in to the first zoomed in picture of the speed restriction

zone of figure 18 , although the effect of the speed restriction is low the actual travel time is

kept above the standard time for the first restriction zone. If we zoom in further to the

second restriction zone we can see that the actual travel time goes way above the standard

time. In the restriction zone the devaition of the actual travel time from the standard time is

two fold larger than the lost time due to the imposed restriction. This might imply the larger

the magnitude of the restriction the bigger will be the devaition , but we will investigate the

correlation in the second approach.

LUNDAMO – LER

The track between Lundamo and Ler extends about 5.71 kilometer and ussualy takes a

standard time of 4 minutes for train number 5733. For the range of time considered the

speed restriction zone extends through out the whole 72 weeks with a magnitude of

0:00:06.

Figure 18 Lundamo - Ler travel time data and lost time due to speed restriction diagram

0:00:00

0:01:26

0:02:53

0:04:19

0:05:46

0:07:12

0:08:38

Actual Time Taken Standard Time Restriction Magnitude


41

Looking in to figure 19 above the actual time is distributed and varied in a uniform pattern

with centering well above the standard time. But throughout the whole data range the

actual travel time is way above the standard time close to tenfold of the lost time due to the

speed restriction. The speed restrictions effect is manifested all over the diagram lifting the

actual time way above the standard time throughout the diagram. In case of speed

restrictions running more than six months it would have been better to incorporate the

imposed restriction in to permanent speed limit so that the restriction would be adjusted in

to the standard time computation.

MELHUS – NYPAN

The rail way line between Melhus and Nypan runs for 5.2 kilometer taking a standard time

of 4 minutes. The speed restriction mapping shows there is one speed restriction zone

between these two stations within the time range of the 14th week up to the 20th week of

2011. The magnitude of the speed restriction is 0:00:20.

Figure 19 Melhus - Nypan time data and lost time due to speed restriction diagram

0:00:00

0:01:26

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44

Figure 22 shows the time data and lost time due to speed restriction diagram for the line

between Drivstua and Oppdal. From the figure we can see that the actual time lies below

the standard time for most of the data ranges displayed and also it is varied uniformly

around the standard time. While zooming in to the speed restriction zone as displayed on

figure 23 one can see that the Actual travel time curve is lifted further above the standard

time. The actual travel time shows a trend of inclining, declining and again inclining and

declining.

This is typically associated with a cyclical change in the intensity of the reason behind the

speed restriction. For instance, if the weather is behind the imposition of the restriction then

cyclical variation in weather could bring the witnessed trend of change in the lost time. This

also could be explained through shifting of drivers, the drivers’ first hitting the pick and then

again lowering the lost time as time goes by supplemented by experience. Therefore from

this diagram we can see the actual travel time has been well affected by the imposition of

the speed restriction as the diagram entertains huge bump ups in the restriction zone unlike

the rest of the data range.

FAGERHAUG – ULSBERG

The line between Fagerhaug and Ulsberg that runs for 13.82 kilometers takes a standard

time of 10 minutes for train number 5733 to cross by. This is one of the most congested of

the zones mapped over the range of the 72 weeks. There are four speed restriction zones in

the data range at between 15th and 18th week, on the 20th week , between 24th and 25th

week and the last one running between week 38 and 39 0f 2011. These zones have a

restriction magnitude of 0:00:51, 0:00:45, 0:00:31 and 0:00:28 seconds respectively.

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46

the restriction is imposed due to construction work, in the beginning the construction work

is not that intensively done and as time goes by the work reaches its major stage creating

difficult ease of pass for the drivers. Then when the work comes to a closure little congestion

will be imposed on the line and the train can pass through easily with less time lose due to

the restriction. Thereby the actual time curve follows the same progressive trend from the

beginning to the middle and declines back towards the end.

GARLI – STØREN

The distance between these two stations extends for a length of 9.29 kilometers having

another station called Soknedal between the two. Train number 5733 takes a standard time

of 19 minutes to pass through the two stations. The speed restriction is imposed on the 15th

week of 2011 with a magnitude of 15 minutes. The actual speed restriction zone starts on

the way from Garli and Soknedal and ends on the way to Soknedal to Støren. That is why the

analysis is being conducted on the margin between Garli and Støren.

Figure 25 Garli – Støren time data and lost time due to speed restriction diagram

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trictions

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ises that

om Oslo

time for

has two

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striction


48

Figure 27 Selsbakk – Trondheim S time data and lost time due to speed restriction diagram As seen on figure 28 the actual time curve, fluctuates randomly hitting higher points and all

of a sudden arbitrarily moving down. Most of the actual travel time’s magnitudes are above

the standard time. The fluctuation could be due to the intense traffic condition near

Trondheim S which could vary on daily or even hourly basis. Therefore from the diagram one

can concluded there is no concrete reason to claim the speed restrictions have affected the

travel time.

HJERNIK – DRIVSTUA

This section of the line extends for 25.36 kilometers having a station called Kongsvoll in

between. Train 5733 takes a standard time of 19 minutes to cross between the two stations.

The speed restriction mapping shows that there is one restriction zone on the 20th week of

2011on this segment of the line with a magnitude of 0:00:50. This restriction zone was

stretched between Hjernik and Drivstua leaving out kongsvoll in between, because of the

fact that the restriction zone lays the whole way across Kongsvoll station. The restriction

zone starts on the way between Hjernik to kongsvoll and ends on the way kongsvoll to

Drivstua.

0:00:00

0:02:53

0:05:46

0:08:38

0:11:31

0:14:24

0:17:17

0:20:10

0:23:02

0:25:55

0:28:48


TBA49, Master t

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Figure 29

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Spring 2012

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agnitude

49

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51

Looking in to figure 31 one can easily see that the actual travel time is regularly distributed

and centered below the standard time except few bumps and larger deviation in the speed

restriction zone of the data range. Zooming in to the restriction zone in figure 32it is seen

that the Zooming in to the restriction zone in figure 32 it is seen that the imposed restriction

first seemed to cause no effect at all but starts to kick of lifting the actual time curve upper

as time goes on. But after the imposed restriction was over the actual time curve goes a little

bit higher for a while and comes back to the regular variation stream. This only is explained

through the mismatch of the planned restriction schedule and what actually happened on

the ground. This means that the speed restriction was imposed on the ground later than

what was written on the weekly planned speed restriction schedule and also the restriction

was revoked later than what was set to be the due date . Still figure 31 as well as figure

illustrates the fact that the speed restrictions had a significant effect on the given span.

LER – SØBERG

This segment of the line extends for 8.28 kilometers and takes a standard time of six minutes

for train 5733. This section contains one speed restriction zone on the 10th and 11th week of

2012 with an associated time loss of 0:00:40.

Figure 32 Ler – Søberg time data and lost time due to speed restriction diagram

0:00:00

0:01:26

0:02:53

0:04:19

0:05:46

0:07:12

0:08:38


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0:00:000:00:430:01:260:02:100:02:530:03:360:04:190:05:020:05:460:06:290:07:12


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Spring 2012

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Magnitude

52

n zone Ler – S

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lost time d

53

n zone Nypan

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sociated

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on, with


54

the premises of the deviation of the going up in line with an increase in the magnitude of

the computed lost time in the introduction of the speed restriction.

This premise is built up on the contextual understanding of the train drivers assuming higher

restriction magnitudes causing larger delays. To look in to this scenario this section tries to

compute the deviation of each recorded actual time from the planned standard time and

plots it on a graph against respective lost time magnitudes. Looking at the plots on the graph

we will check if there happens to be an increasing, decreasing or random trained in the plot

itself. This could be done in two ways; first plotting the actual deviation magnitude against

the lost time magnitudes and the second one by plotting the percentage of deviation against

the lost time. To do so one need first to compute the deviations and the percentage of

deviations. This is computed using the formulas below.

–

Percentage of deviation serves as a key factor to express deviations in terms of their basic

cause. Some small lost times could cause larger deviations compared to their own

magnitude; may be three times the computed lost time and at same time larger computed

lost times due to restriction may cause as half as their magnitude. But for someone who is

concentrating barely on caused deviations he/she would infer the larger the lost time the

larger would be the deviation. Therefore not to fall in this trap of delusion there needs to be

a consideration to take in to account the percentile of the deviation itself.


55

Plotting the computed deviation magnitude against the lost time will only shows how

specific magnitude of restrictions have brought lost time and how the trend is displayed if

there is one. Whereas plotting the percentage of the deviation against lost time will provide

in depth understanding of the criticality as well as the intensity of the speed restriction

magnitude itself; thereby also providing an opportunity to investigate in to trends if there

happens to be one.

Even though the above notion seems true, there should be a consistency in data type and

external factors that will affect the delay of the train in addition to the restrictions. As the

set up and the affecting factors on travel time do vary along the line from station to station it

calls for the need of normalization. The normalization could be done in two ways either with

utilizing factors on the computation or introducing constant denominator that could give a

common basis for the computations.

To do so the second way, which is introduction of a consistent denominator is preferred for

this condition. Therefore we will compute the both the percentage of the lost time and the

deviation percentage. This will enable us to look in to how lost time due to restriction and

deviation will vary in line with the standard time. This will be done in such a way that the

percentage of the deviation will be computed and rated against respective standard times.

Similarly the lost time due to restriction will be rated in percentiles with respect to their

standard times. Here the standard time will serve us a basis of consistency for the

computation as well it will enable a common ground and base factor to reduce

inconsistencies due to variation in stations. Plotting the percentage of lost time due to

restriction against the percentile of deviations will give us a primary basis for conclusion

when it comes to investigating the relationship between magnitude of lost time due to

restriction and the associated deviation in travel time.


56

Figure 36 plot of the deviation magnitude against respective time lost due to deviation with correlation factor of 0.092 Figure 36 displays the first way of plotting the deviation magnitude against lost time due to

imposition of the restriction. The trend shows that starting from a time loss of 0:00:06 until

0:00: 43 there is an increasing trend in lost time and then a decreasing and increasing

patterns fluctuate randomly until it reaches 0:01:19. After wards the graph shows an

increasingly upward curve. This implies with magnitudes larger than 0:01:19 the graph has

an increasing trend. Therefore we can state that for this data range collected; for speed

restrictions which have a computed time loss of greater than 0:01:19, the larger the

magnitude of the speed restriction the higher will be the associated deviation. Fitting the

time magnitude points on the scatter diagram with Microsoft excel an increasing linear curve

displayed as Linear (deviation) on the legend is obtained. This illustrates as the time lost

increases there is an associated increase in the actual travel time taken. Hence somewhat

for this data range, time loss due to restriction has positive impact on the associated

deviation in the travel time. In addition while doing the correlation analysis for this data set

it yielded a week correlation factor of 0.092.

00:00:0000:02:5300:05:4600:08:3800:11:3100:14:2400:17:1700:20:1000:23:02

0:00:00 0:00:43 0:01:26 0:02:10 0:02:53 0:03:36 0:04:19 0:05:02

Devaition

devaition Linear (devaition)

dev

Lost time


57

Figure 37 percentage of deviation against lost time Figure 37 illustrates a plot of the percentage of deviation drawn against the lost time due to

speed restriction. From the pattern displayed we can see that smaller lost times due to

restriction tend to have larger effect on travel time, causing by far larger deviations in

contrast to their magnitudes. Here further fitting points on the scatter diagram using

Microsoft excel we can obtain a down ward pointed decreasing linear curve designated as

linear (Series) on the legend. Hence even though small time losses due to restrictions have

small magnitude compared to their intensity they have, by far higher percentage of effect.

From the diagram we can see that the higher the lost time due to speed restrictions the

lower the percentage of the deviations get. Hence smaller speed restrictions, it tend to have

higher relative effect on the actual lost time compared to their magnitudes.

-20

-10

0

10

20

30

40

0:00:00 0:00:43 0:01:26 0:02:10 0:02:53 0:03:36 0:04:19 0:05:02

Series1 Linear (Series1)dev/lost t

Lost time


58

Figure 38 scatter diagram of percentage of deviation against lost time percentage with a correlation factor of 0.135 Figure 38 displays a scatter chart of travel time deviation percentage on the Y- axis plotted

against lost time due to restriction percentage on the X-axis. From the plots and the

percentages of respective magnitudes with respect to standard time percentage is the best

way to look in to the correlation between these two factors. Using the standard time as a

common of computation will ensure the consistency of the data as well serves a purpose of

normalization of the whole data set. Fitting the scatter diagram points in to a curve using

the curve fitting option on Microsoft excel the curve noted as Linear (Series 1) is obtained.

Although; the slope of the curve is so small, it depicts an increasing trend in the percentage

of deviation in line with increasing the lost time due to restrictions. Here in accordance to

the primary background premises of the thesis, what has been expected was a perfect linear

upward pointed curve especially for lost time magnitudes more than 4% of the standard

time. While conducting a correlation analysis for the whole data range including the whole

restriction period, it was found out that the percentage of lost time due to speed restriction

and the adjacent deviation percentage has a correlation factor of 0.135. Extending and

limiting the correlation analysis to peak values only somewhat similar correlation factor of

0.185 was obtained. The small angle of inclination or lower slope of the fitting curve implies

there appears to be low correlation between the percentage of deviation and the associated

lost time due to restriction. This weakness in the correlation, for the whole data set might be

due to in consistency in the setting and nature of the data considered, as the analysis has

-50%

0%

50%

100%

150%

200%

Series1 Linear (Series1)dev%

lost time%


59

been conducted on different stations on different seasons throughout the years. Variation

in season of the year will imply varied external effects on the travel time itself. For instance

equivalent restriction magnitudes in summer and winter have varied ultimatum effect on the

actual travel time thereby on the percentage of deviation itself. Furthermore the

topographic setup and related conditions on speed restriction zones varies along with the

stations hence it makes it difficult to conduct a consistent analysis along the line. Finally the

4% allowances added on the computed standard times had their own effect absorbing the

speed restriction effect from manifestation. On figure 38 above, this had been purely the

case for data ranges of lost time percentages lower than the 4% allowances absorbing the

effect and showing random variation. But for percentage of time lost more than 4% the

trend has been somehow an increasing curve.

With this weak or no correlation witnessed further efforts have been made to dissect the

data in to first week of imposition of the restriction. This is done as there was a tendency or

trend of increment in the first weeks of the time diagram graphs of respective zones. While

conducting the correlation analysis for this data segment it was found out that the

percentage of lost time due to speed restriction and the adjacent deviation percentage has a

correlation factor of 0.433. With this finding the percentage of deviation for the first weeks

was plotted against the adjacent percentage of time loss due to restriction. Fitting the

scatter diagram points in to a curve using the curve fitting option on Microsoft excel the

curve noted as Linear (First week basis) is obtained. This shows an increasing curve with

increased slope as shown in figure 39 below.


60

Figure 39 scatter diagram of percentage of deviation against lost time percentage on first week basis with a correlation factor of 0.433 With this context and new finding in mind further work was done to normalize the data set

of deviation percentage and lost time due to restriction percentage. This was done in order

to reduce noise of the data and to avoid misinterpretations caused due to arbitrary data

with extremely maximum and extremely minimum values. In doing so the average deviation

for respective time losses due to restriction percentages was computed. This is done in such

a way that the deviation percentages were averaged based on their respective time losses

percentages due to the restrictions categories. This means the deviation percentages of

individual speed restrictions were averaged. After this, correlation analysis was conducted

on Microsoft excel for the average deviation percentages and the respective time losses

percentages due to restrictions. This correlation analysis yielded a correlation factor of

0.595. This is a significant number showing a tendency towards a strong correlation. With

this finding the average deviation percentage for the data set was plotted against the

adjacent percentage of time loss due to restriction on a scatter diagram. Further fitting the

scatter diagram points in to a curve using the curve fitting option on Microsoft excel the

curve noted as Linear (Average deviation) is obtained. This shows a further increasing curve

with added increased slope than the plots so far, as shown in figure 40 below.

-50%

0%

50%

100%

150%

200%

First week basisFirst week basis Linear (First week basis)Dev%

Lost time %


61

Figure 40 scatter diagram of average deviation percentage against lost time percentage with correlation factor of 0.595

On figure 40 the y axis represents the averaged values of the deviation for individual speed

restrictions whereas the X-axis displays the percentage of lost time for individual speed

restrictions. This graphical illustration on figure 40 and the obtained correlation factor of

0.595 from the correlation analysis shows there is somehow a positive tendency towards

correlativeness between the average deviation percentage and the lost time percentage.

(See appendix).

Further working correlation analysis was made on the average deviation percentage of the

data set for more than 4% of the time lost percentage due to restriction. From the

correlation analysis it was found out that the average deviation percentage and percentage

of time lost due to restriction are correlated by a factor of 0.603 (see appendix). The

increase in the correlation factor after the 4% is as expected the fuzzy boundary of

correlations that came in to existence due to 4% time allowances added on the standard

time. Therefore omitting the extreme values or normalizing them using averaging statistical

tool one can see there is a correlation between deviation magnitude and the associated time

loss due to restrictions.

-10%

0%

10%

20%

30%

40%

50%

Average deviationAverage deviation Linear (Average deviation)Average Dev%

Lost time


62


63

Conclusion

This conclusion part is structured in such a way that, it presents the conclusions made on the

course of addressing the research questions.

To what level of detail should such studies be done?

For data analysis involving investigation in to speed restriction care should be taken in

selecting the appropriate tools of analysis. On the course of conducting this thesis it was

found out that restriction zone mapping and statistical analysis play the major role. In

addition diagrammatical plotting of data sets on Microsoft excels and inferring implications

is of high prominence. Specifically curve fitting and line plots on will take the biggest share

of the implication deduction part enabling a clearer understanding of outputs.

The actual Travel time and standard data sets collected also plays of high significance when

it comes to the ultimate outputs of the analysis and the thesis itself. The data set should be

consistent and accommodating when it comes to different attributes that would affect travel

time or else it should be normalized to mitigate interference. Otherwise it is difficult to get

grasp of the clear image and effect of speed restrictions, as different factors such as

topography, climatic conditions, seasonal variation, travel direction and type of train might

affect and sub standardize the analysis.

In this thesis work efforts has been employed to ensure the consistency of the analysis and

data sets collected. In this virtue the analysis was done on freight 5733 with lots of

punctuality complaints history. This has enabled the manifestation of trends on speed

restrictions to greater extent. In addition to keep uniformity of the analysis similar analysis

tools has been utilized throughout the work including normalization by averaging and

percentiles.


64

Relationship between speed reductions and delays

Trend based relationship From the analysis of most restriction zones and fitting curves of the travel times in the

restriction zone; it was found out that, for most of the restriction zones the travel time tends

to go up to reach its pick and declines again to lower magnitude towards the end. This

tendency is associated with the time based build up of learning curves of the drivers getting

accustomed to the restriction zone after a while. Furthermore progressive severity of the

reason behind the imposition of the restriction could also offer an explanation for this

phenomenon. In the restriction zone between Lundamo and Ler it have been noted that, the

speed restriction has been imposed more than a year and a half. This type of restrictions as

they long last rather than imposing them as temporary restrictions they should be

incorporated in to the standard time and should be set as a permanent restriction.

Also in some of the analyzed restriction zones cyclical variations has been noted which has

been explained by seasonal or cyclical variation on the root cause of the restriction

imposition itself and change of drivers bringing in to play different learning curves the

drivers. Most often lifting of the standard time and random shootings in travel time were

explained through imposing and revoking of restrictions ahead of time, placebo effects in

play on drivers and unbalanced special recovery times.

Looking in to the analysis done on the 13 restriction zones it was found out that as long as

there is sufficient data, uniformity and regular fluctuation of the time magnitudes on the

curves the actual time curve is lifted up above the standard line curve with a significant

margin. Visual inspection of the graphs indicated that the impact of speed restriction was

greater during the beginning of the period. This supports the premises of this thesis

assuming existence of an increasing trend in the relationship between the lost time due to

restriction and deviation for some range of data. Therefore there is an increasing effect

caused and trend displayed on the actual time taken in the presence of the speed

restrictions. This strengthens one of the research premises of speed restrictions having

effect on the actual travel time thereby causing delays.


65

Magnitude based relationship While working on the relationship between lost times due to speed restrictions and

magnitude of the caused deviation, even if the fitting curves has directed an increasing

tendency. First it was found out that there was a weak correlation between the percentage

of the lost time and the percentage of the caused deviation for the whole data set. But for

some data sets above the 4% allowances there, tends to be a positive correlation. The

correlation analysis on first weeks based on the imposition of the speed restriction also

showed a greater correlation with a factor of 0.433. These led to conducting an average

deviation percentage analysis to normalize the data; in which the correlation analysis yielded

a correlation factor of 0.595. This showed somehow there is a positive tendency towards

correlativeness between the average deviation percentage and the lost time percentage. In

addition correlation analysis made for speed restrictions greater than 4% lost time showed

that there is an increased correlation factor of 0.603. This is an indication that the fuzzy

boundary of correlations somehow lies on the 4% zone. This fuzzy boundary might come in

to existence as a result of the added 4% allowance which is usually added by the railway

time planners on the standard time. Therefore it could be concluded that, omitting the

extreme values or normalizing them using averaging and percentile statistical tools there is a

correlation between deviation magnitude and the associated time loss due to restrictions.

Hence this depicts the fact that there needs to be further work to be done with consistent

data sets on fixed positions to clearly zoom in to the real effects displayed.

In the relationship analysis it was interesting to note that small time loses associated with

lower restrictions tend to cause higher effect of intensity compared to their magnitude.

While fitting such curves it was found out there tends to be a decreasing curve illustrating

smaller reductions having significant percentile effect than bigger ones.

The lack of the anticipated purely increasing or strongly correlated pattern between

percentage of lost time due to restriction and associated deviation magnitudes is an

opportunity for further researches in the thematic area. This could be surmounted by

studying and analyzing the restriction zones with consistent data, specific seasons and

focused areas on the restriction zones. Furthermore expanding the range of the data to

include more percentage of lost time magnitudes, differ directions along segments and


66

varied types of trains would lead to refined results. In addition causes of different levels of

correlations between the lost time and deviation along the route are other thematic areas

whereby supplementary researches could be conducted.


67

Appendix

Time lost due to restriction %

Average Deviation percentage

2.50% 16.00%2.87% 15.05%4.39% -4.08%4.67% 2.90%4.81% 12.26%5.12% 42.67%5.17% 3.97%5.63% 1.42%7.50% -0.83%8.33% 33.94%8.50% 18.35%8.78% 15.69%

11.11% 8.97%13.75% 0.18%14.17% 28.96%23.12% 12.71%51.88% 43.46%59.17% 38.22% N= 20 82.81% 36.70% Correlation Factor 0.595

Time lost due to restriction %

Average Deviation percentage

4.39% -4.08%4.67% 2.90%4.81% 12.26%5.12% 42.67%5.17% 3.97%5.63% 1.42%7.50% -0.83%8.33% 33.94%8.50% 18.35%8.78% 15.69%

11.11% 8.97%13.75% 0.18%14.17% 28.96%23.12% 12.71%51.88% 43.46%59.17% 38.22%82.81% 36.70% N= 18

Correlation Factor 0.6026

18 19 20 21

18 19 20 21

67,86

64,51

62,24

59,54

57,20

53,44

49,62

46,10

44,60 *

42,22

40,30

36,38

32,28

29,80

26,94

25,18

22,76

20,95

19,83

19,05

18,92

17,93

16,42

16,17

15,50

14,15

13,09

12,10

12,09

10,50

9,30

8,72

6,87

5,85

3,89

2,28

0,27 *

1,40 *

2,29

4,38

10,50

7,33

8,72

7,33

7,33

5,85

7,33

5,26

3,89

1,97 *

1,08

Dønnum Bp

Km fraOslo S

EIDSVOLL

BØNVarud

DAL

SAND

HAUERSETER

Nordby

JESSHEIM

LANGELAND

ASPER

KLØFTA

LINDEBERG

FROGNER

Leirsund

LILLESTRØM N

General Motor s.sp.

LILLESTRØMH-sign 1214, Lillestrøm

Sagdalen

Sagdalen Bp.

STRØMMENFjellhamar

Fjellhamar Bp.

Hanaborg

LØRENSKOGHøybråten

Haugenstua Bp.

Haugenstua

GRORUDNyland

AKER

Alna

BROBEKK

BRYN

Sporv.303

OSLO S

NATIONALTHEATRET

Elisenberg Bp.A

SKØYEN

Km fraOslo S

GRORUD

ALNABRU

Km fraOslo S

AKER

ALNABRU

Km fraOslo S

ALNABRU

BROBEKK

Km fraOslo S

ALNABRU

Teisen s.sp

BRYNOslo S s.sp Kværner

LOENGA

3: 190 EVL

Kmmellomstasjon

Kryssspor-lengde

3,35

3/5: 7004: 7705: 310

2,27

DNM

5,04

2: 591 BØN

3,76

1: 536 DAL

2: 730 SAD

3,82

5,02

1: 5552: 664 HSR

2,35

1: 5473: 535 JEH

1,92

LAL

3,92

1: 711 ASE

4: 718 KLØ

4,10

2,48

1: 696 LBG

4,62

1: 321 FRO

4,23

15: 914 BRT

GMO

6: 3807: 3748: 3319: 270 LLS

1,12

0,91

SLD

0,99SLN

1,76

STN

2,02

FH1

1: 374 LØR

2,05

1,60

HG1

1,78

3: 560 GRO

2,87

AKE

1,96

BRB

3,62

BR

SP3

1,67

OSL

0,89

NTH

2,09

ELI

SKØ

Kmmellomstasjon

3,17

3: 560

Kryssspor-lengde

GRO

ALB

Kmmellomstasjon

1,39

Kryssspor-lengde

AKE

ALB

Kmmellomstasjon

Kryssspor-lengde

1,48

ALB

BRB

Kmmellomstasjon

3,44

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ALB

TEN

3,89

BR

KVÆ

LOE

18

18

18

18

19 20

19 20

19 20

19 20

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AKER - ALNABRU

ALNABRU - BROBEKK

LOENGA - ALNABRU

21

21

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20113 9)

21672 63)

RUTEORD. NR.BLAD NR. 9 GJELDER FRA OG MED:

161.1SKØYEN - OSLO S - EIDSVOLL Søndag 11. desember 20111) 44, 56, 322, 326, 330, 334, 405, 1671, 1675, 1676, 1679, 1680, 1683, 1684, 1688, 2154, 2157,

2158, 2161, 2162, 2165, 2166, 2169, 2170, 2173, 2177 Søndager - fredager.2) 54, 4805, 4806, 5073, 5074, 5823, 21526, 21527, 21528, 21563, 21603, 21604, 21626 Lørdager.3) 306, 310, 314, 318, 505, 507, 1004, 1006, 1008, 1010, 1014, 1018, 1022, 1655, 1656, 1659,

1660, 1663, 1664, 1667, 1668, 1672, 2107, 2108, 2114, 2117, 2118, 2121, 2122, 2125, 2126, 2129, 2130, 2133, 2134, 2137, 2138, 2141, 21565 Mandager - lørdager unntatt helligdager.

4) 406, 2178, 41988 Mandager - lørdager.5) 502, 4011, 5716, 5737, 11626, 11655, 21655, 22737, 23411, 41935 Lørdager unntatt helligdager.6) 535 Mandager - torsdager og lørdager.7) 545 Fredager og søndager.8) 1038, 5572, 5708, 5730, 5732, 5936, 41906 Tirsdager - lørdager unntatt dag etter helligdag.9) 1040, 4851, 4852, 4858, 4861, 20113, 21508, 21556, 41633, 41634, 41970, 45964, 48206

Søndager.10) 1042, 5715, 11523, 11628, 22715 Helligdager.11) 1653 Skøyen - Lillestrøm Mandager - fredager unntatt helligdager. Lillestrøm - Dal Alle dager.12) 2174 Skøyen - Strømmen Søndager - fredager. Strømmen - Lillestrøm Mandager - lørdager.13) 4001, 21653, 23401, 41913 Mandager, tirsdager, onsdager og fredager unntatt helligdager.14) 4008, 21652 Onsdager - søndager unntatt dag etter helligdag.15) 4801 Loenga - Frogner Mandager. Frogner - Eidsvoll Tirsdager.16) 4802, 4824, 4835, 4862, 5241, 5242 Tirsdager.17) 4811, 4855, 4857, 4866, 5938, 21061, 41637, 41638, 41924 Mandager.18) 4813, 4820 Onsdager og fredager.19) 4817 Loenga - Frogner Tirsdager og onsdager. Frogner - Eidsvoll Onsdager og torsdager.20) 4822, 21537 Onsdager og torsdager.21) 4836, 41647, 41648 Onsdager.22) 4840 Fredager. Kjøres bare etter særskilt kunngjøring.23) 4843, 41632, 41645 Torsdager unntatt helligdager.24) 4844 Eidsvoll - Kløfta Torsdager unntatt helligdager. Kløfta - Loenga Fredager unntatt dag etter

helligdag.

25) 4865 Torsdager.26) 5003, 21533, 40964 Mandager, torsdager og fredager.27) 5005, 5075, 21535, 21548, 21550, 21624 Tirsdager og onsdager. Kjøres bare etter særskilt

kunngjøring.28) 5007, 21062 Tirsdager og onsdager.29) 5021, 5022, 5032 Tirsdager og torsdager unntatt helligdager.30) 5031 Tirsdager, torsdager og lørdager unntatt helligdager.31) 5057, 5058 Onsdager og torsdager unntatt helligdager.32) 5060 Onsdager, torsdager og fredager unntatt helligdager.33) 5061 Tirsdager, onsdager og torsdager unntatt dag før helligdag.34) 5064, 20104 Mandager unntatt helligdager.35) 5066 Tirsdager - fredager unntatt helligdager.36) 5071, 5072, 21534, 21538, 21620, 44660, 44661 Mandager - fredager.37) 5076, 21529 Onsdager og torsdager. Kjøres bare etter særskilt kunngjøring.38) 5077, 21544, 21546, 21622 Mandager, torsdager og søndager.39) 5078, 21531 Mandager, tirsdager og fredager.40) 5252 Tirsdager - fredager unntatt helligdager. Kjøres fra og med 29. mai 2012.41) 5254 Tirsdager - fredager unntatt helligdager.Kjøres til og med 25. mai 2012.42) 5256, 5816, 41630, 41631, 41676, 41677 Lørdager unntatt dag etter helligdag.43) 5261, 5262 Mandager og tirsdager unntatt helligdager.44) 5506 Tirsdager - fredager unntatt helligdager. Kjøres bare etter særskilt kunngjøring.45) 5509, 5707, 5803, 5805, 5809, 22707 Mandager - torsdager unntatt helligdager.46) 5564, 5735, 22735 Mandager - torsdager unntatt helligdager. Kjøres bare etter særskilt

kunngjøring.47) 5565 Mandager - torsdager unntatt helligdager og dag før helligdag. Kjøres bare etter særskilt

kunngjøring.48) 5566, 41610, 41629 Fredager unntatt helligdager. Kjøres bare etter særskilt kunngjøring.49) 5567 Helligdag før hverdag. Kjøres bare etter særskilt kunngjøring.50) 5569, 5933, 5935 Mandager - torsdager unntatt helligdager og dag før helligdag.

51) 5571, 5719, 5821, 5826, 5827, 5828, 5937, 5939, 21673, 22719 Helligdag før hverdag.52) 5706, 5806, 5808, 5814 Tirsdager - fredager unntatt dag etter helligdag.53) 5718, 5820, 10353, 21675, 45989 Hverdag etter helligdag.54) 5734 Onsdager, torsdager og fredager unntatt helligdager og dag etter helligdag. Kjøres bare

etter særskilt kunngjøring.55) 5736 Lørdager unntatt dag etter helligdag. Kjøres bare etter særskilt kunngjøring.56) 5738, 21567, 41910 Søndager unntatt dag etter helligdag.57) 5800, 10351, 45944, 45949, 45962, 45965 Tirsdager - fredager unntatt helligdager og dag etter

helligdag.58) 5802, 5811 Mandager - fredager unntatt helligdager. Kjøres bare etter særskilt kunngjøring.59) 5931, 48215 Fredager.60) 11654 Dal - Lillestrøm Alle dager. Lillestrøm - Skøyen Helligdager.61) 12001, 12002 Mandager og torsdager unntatt helligdager.62) 21552, 41960 Tirsdager, torsdager og lørdager unntatt dag etter helligdag.63) 21672, 41971 Fredager unntatt helligdager.64) 22913 Mandager, tirsdager, onsdager, fredager og lørdager unntatt helligdager.65) 22981, 41981 Mandager - torsdager, lørdager og søndager.66) 40965 Tirsdager, onsdager og lørdager.67) 41640, 41641 Fredager unntatt dag etter helligdag.68) 41642 Torsdager unntatt helligdager. Kjøres bare etter særskilt kunngjøring.69) 41643 Fredager unntatt dag etter helligdag. Kjøres bare etter særskilt kunngjøring.70) 41922 Torsdager, fredager og lørdager.71) 41953 Mandager, onsdager og fredager unntatt helligdager.72) 41973 Mandager - torsdager og lørdager unntatt helligdager.

Funkwerk IT TrainPlan 2.14.10.1 (Patch 10+) Side 7 of 8 Utskrift: 20.10.2011 14:39

michot

Sticky Note

lilestormsund stop

michot

Sticky Note

main start from gronund based on the data table

michot

Sticky Note

grorund start

21 22 23 24

21 22 23 24

67,86

64,51

62,24

59,54

57,20

53,44

49,62

46,10

44,60 *

42,22

40,30

36,38

32,28

29,80

26,94

25,18

22,76

20,95

19,83

19,05

18,92

17,93

16,42

16,17

15,50

14,15

13,09

12,10

12,09

10,50

9,30

8,72

6,87

5,85

3,89

2,28

0,27 *

1,40 *

2,29

4,38

10,50

7,33

8,72

7,33

7,33

5,85

7,33

5,26

3,89

1,97 *

1,08

Dønnum Bp

Km fraOslo S

EIDSVOLL

BØNVarud

DAL

SAND

HAUERSETER

Nordby

JESSHEIM

LANGELAND

ASPER

KLØFTA

LINDEBERG

FROGNER

Leirsund

LILLESTRØM N

General Motor s.sp.

LILLESTRØMH-sign 1214, Lillestrøm

Sagdalen

Sagdalen Bp.

STRØMMENFjellhamar

Fjellhamar Bp.

Hanaborg

LØRENSKOGHøybråten

Haugenstua Bp.

Haugenstua

GRORUDNyland

AKER

Alna

BROBEKK

BRYN

Sporv.303

OSLO S

NATIONALTHEATRET

Elisenberg Bp.A

SKØYEN

Km fraOslo S

GRORUD

ALNABRU

Km fraOslo S

AKER

ALNABRU

Km fraOslo S

ALNABRU

BROBEKK

Km fraOslo S

ALNABRU

Teisen s.sp

BRYNOslo S s.sp Kværner

LOENGA

3: 190 EVL

Kmmellomstasjon

Kryssspor-lengde

3,35

3/5: 7004: 7705: 310

2,27

DNM

5,04

2: 591 BØN

3,76

1: 536 DAL

2: 730 SAD

3,82

5,02

1: 5552: 664 HSR

2,35

1: 5473: 535 JEH

1,92

LAL

3,92

1: 711 ASE

4: 718 KLØ

4,10

2,48

1: 696 LBG

4,62

1: 321 FRO

4,23

15: 914 BRT

GMO

6: 3807: 3748: 3319: 270 LLS

1,12

0,91

SLD

0,99SLN

1,76

STN

2,02

FH1

1: 374 LØR

2,05

1,60

HG1

1,78

3: 560 GRO

2,87

AKE

1,96

BRB

3,62

BR

SP3

1,67

OSL

0,89

NTH

2,09

ELI

SKØ

Kmmellomstasjon

3,17

3: 560

Kryssspor-lengde

GRO

ALB

Kmmellomstasjon

1,39

Kryssspor-lengde

AKE

ALB

Kmmellomstasjon

Kryssspor-lengde

1,48

ALB

BRB

Kmmellomstasjon

3,44

Kryssspor-lengde

ALB

TEN

3,89

BR

KVÆ

LOE

22 23

22 23

22 23

22 23

21

21

21

21

GRORUD - ALNABRU

AKER - ALNABRU

ALNABRU - BROBEKK

LOENGA - ALNABRU

24

24

24

24

11

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161.1SKØYEN - OSLO S - EIDSVOLL Søndag 11. desember 20111) 44, 56, 322, 326, 330, 334, 405, 1671, 1675, 1676, 1679, 1680, 1683, 1684, 1688, 2154, 2157,

2158, 2161, 2162, 2165, 2166, 2169, 2170, 2173, 2177 Søndager - fredager.2) 54, 4805, 4806, 5073, 5074, 5823, 21526, 21527, 21528, 21563, 21603, 21604, 21626 Lørdager.3) 306, 310, 314, 318, 505, 507, 1004, 1006, 1008, 1010, 1014, 1018, 1022, 1655, 1656, 1659,

1660, 1663, 1664, 1667, 1668, 1672, 2107, 2108, 2114, 2117, 2118, 2121, 2122, 2125, 2126, 2129, 2130, 2133, 2134, 2137, 2138, 2141, 21565 Mandager - lørdager unntatt helligdager.

4) 406, 2178, 41988 Mandager - lørdager.5) 502, 4011, 5716, 5737, 11626, 11655, 21655, 22737, 23411, 41935 Lørdager unntatt helligdager.6) 535 Mandager - torsdager og lørdager.7) 545 Fredager og søndager.8) 1038, 5572, 5708, 5730, 5732, 5936, 41906 Tirsdager - lørdager unntatt dag etter helligdag.9) 1040, 4851, 4852, 4858, 4861, 20113, 21508, 21556, 41633, 41634, 41970, 45964, 48206

Søndager.10) 1042, 5715, 11523, 11628, 22715 Helligdager.11) 1653 Skøyen - Lillestrøm Mandager - fredager unntatt helligdager. Lillestrøm - Dal Alle dager.12) 2174 Skøyen - Strømmen Søndager - fredager. Strømmen - Lillestrøm Mandager - lørdager.13) 4001, 21653, 23401, 41913 Mandager, tirsdager, onsdager og fredager unntatt helligdager.14) 4008, 21652 Onsdager - søndager unntatt dag etter helligdag.15) 4801 Loenga - Frogner Mandager. Frogner - Eidsvoll Tirsdager.16) 4802, 4824, 4835, 4862, 5241, 5242 Tirsdager.17) 4811, 4855, 4857, 4866, 5938, 21061, 41637, 41638, 41924 Mandager.18) 4813, 4820 Onsdager og fredager.19) 4817 Loenga - Frogner Tirsdager og onsdager. Frogner - Eidsvoll Onsdager og torsdager.20) 4822, 21537 Onsdager og torsdager.21) 4836, 41647, 41648 Onsdager.22) 4840 Fredager. Kjøres bare etter særskilt kunngjøring.23) 4843, 41632, 41645 Torsdager unntatt helligdager.24) 4844 Eidsvoll - Kløfta Torsdager unntatt helligdager. Kløfta - Loenga Fredager unntatt dag etter

helligdag.

25) 4865 Torsdager.26) 5003, 21533, 40964 Mandager, torsdager og fredager.27) 5005, 5075, 21535, 21548, 21550, 21624 Tirsdager og onsdager. Kjøres bare etter særskilt

kunngjøring.28) 5007, 21062 Tirsdager og onsdager.29) 5021, 5022, 5032 Tirsdager og torsdager unntatt helligdager.30) 5031 Tirsdager, torsdager og lørdager unntatt helligdager.31) 5057, 5058 Onsdager og torsdager unntatt helligdager.32) 5060 Onsdager, torsdager og fredager unntatt helligdager.33) 5061 Tirsdager, onsdager og torsdager unntatt dag før helligdag.34) 5064, 20104 Mandager unntatt helligdager.35) 5066 Tirsdager - fredager unntatt helligdager.36) 5071, 5072, 21534, 21538, 21620, 44660, 44661 Mandager - fredager.37) 5076, 21529 Onsdager og torsdager. Kjøres bare etter særskilt kunngjøring.38) 5077, 21544, 21546, 21622 Mandager, torsdager og søndager.39) 5078, 21531 Mandager, tirsdager og fredager.40) 5252 Tirsdager - fredager unntatt helligdager. Kjøres fra og med 29. mai 2012.41) 5254 Tirsdager - fredager unntatt helligdager.Kjøres til og med 25. mai 2012.42) 5256, 5816, 41630, 41631, 41676, 41677 Lørdager unntatt dag etter helligdag.43) 5261, 5262 Mandager og tirsdager unntatt helligdager.44) 5506 Tirsdager - fredager unntatt helligdager. Kjøres bare etter særskilt kunngjøring.45) 5509, 5707, 5803, 5805, 5809, 22707 Mandager - torsdager unntatt helligdager.46) 5564, 5735, 22735 Mandager - torsdager unntatt helligdager. Kjøres bare etter særskilt

kunngjøring.47) 5565 Mandager - torsdager unntatt helligdager og dag før helligdag. Kjøres bare etter særskilt

kunngjøring.48) 5566, 41610, 41629 Fredager unntatt helligdager. Kjøres bare etter særskilt kunngjøring.49) 5567 Helligdag før hverdag. Kjøres bare etter særskilt kunngjøring.50) 5569, 5933, 5935 Mandager - torsdager unntatt helligdager og dag før helligdag.

51) 5571, 5719, 5821, 5826, 5827, 5828, 5937, 5939, 21673, 22719 Helligdag før hverdag.52) 5706, 5806, 5808, 5814 Tirsdager - fredager unntatt dag etter helligdag.53) 5718, 5820, 10353, 21675, 45989 Hverdag etter helligdag.54) 5734 Onsdager, torsdager og fredager unntatt helligdager og dag etter helligdag. Kjøres bare

etter særskilt kunngjøring.55) 5736 Lørdager unntatt dag etter helligdag. Kjøres bare etter særskilt kunngjøring.56) 5738, 21567, 41910 Søndager unntatt dag etter helligdag.57) 5800, 10351, 45944, 45949, 45962, 45965 Tirsdager - fredager unntatt helligdager og dag etter

helligdag.58) 5802, 5811 Mandager - fredager unntatt helligdager. Kjøres bare etter særskilt kunngjøring.59) 5931, 48215 Fredager.60) 11654 Dal - Lillestrøm Alle dager. Lillestrøm - Skøyen Helligdager.61) 12001, 12002 Mandager og torsdager unntatt helligdager.62) 21552, 41960 Tirsdager, torsdager og lørdager unntatt dag etter helligdag.63) 21672, 41971 Fredager unntatt helligdager.64) 22913 Mandager, tirsdager, onsdager, fredager og lørdager unntatt helligdager.65) 22981, 41981 Mandager - torsdager, lørdager og søndager.66) 40965 Tirsdager, onsdager og lørdager.67) 41640, 41641 Fredager unntatt dag etter helligdag.68) 41642 Torsdager unntatt helligdager. Kjøres bare etter særskilt kunngjøring.69) 41643 Fredager unntatt dag etter helligdag. Kjøres bare etter særskilt kunngjøring.70) 41922 Torsdager, fredager og lørdager.71) 41953 Mandager, onsdager og fredager unntatt helligdager.72) 41973 Mandager - torsdager og lørdager unntatt helligdager.


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5733

30)

526720)

5270 21)

5267

20)

5270 21)

5253

16)

5938 40)

5735

32)

5719

29)

4162

942

)

336

336

4)

5253

16)

5733

30)

41642 45)

5938 40)

4844 14)

5253

16)

5733

30)

335

5735

32)

570925)


161.1EIDSVOLL - DOMBÅS Søndag 11. desember 20111) 44, 47, 322, 325, 326, 329, 330, 333, 334 Søndager - fredager.2) 306, 309, 310, 313, 314, 317, 318 Mandager - lørdager unntatt helligdager.3) 308 Dombås - Lillehammer Mandager - lørdager unntatt helligdager. Lillehammer - Eidsvoll Alle

dager.4) 405 Eidsvoll - Minnesund Søndager - fredager. Minnesund - Dombås Mandager - lørdager.5) 406 Mandager - lørdager.6) 2343 Mandager - fredager unntatt helligdager. Kjøres til og med 25. mai 2012.7) 2353 Mandager - fredager unntatt helligdager. Kjøres fra og med 29. mai 2012.8) 4801, 4802, 5241, 5242, 6210, 6212 Tirsdager.9) 4805, 4806 Lørdager.10) 4811 Mandager.11) 4813, 4820 Onsdager og fredager.12) 4817, 4822 Onsdager og torsdager.13) 4824 Hove - Brøttum Mandager. Brøttum - Eidsvoll Tirsdager.14) 4843, 4844, 41645 Torsdager unntatt helligdager.15) 5252 Tirsdager - fredager unntatt helligdager. Kjøres fra og med 29. mai 2012.16) 5253 Eidsvoll - Rudshøgda Mandager - fredager unntatt helligdager. Rudshøgda - Dombås

Tirsdager - lørdager unntatt dag etter helligdag.17) 5254 Tirsdager - fredager unntatt helligdager.Kjøres til og med 25. mai 2012.

18) 5256, 41677 Lørdager unntatt dag etter helligdag.19) 5261, 5262, 20347, 20348 Mandager og tirsdager unntatt helligdager.20) 5267, 5268 Tirsdager unntatt helligdager.21) 5269, 5270 Tirsdager unntatt helligdager. Kjøres bare etter særskilt kunngjøring.22) 5706 Dombås - Ringebu Mandager - torsdager unntatt helligdager. Ringebu - Eidsvoll Tirsdager -

fredager unntatt dag etter helligdag.23) 5707 Eidsvoll - Dovre Mandager - torsdager unntatt helligdager. Dovre - Dombås Tirsdager -

fredager unntatt dag etter helligdag.24) 5708, 5730, 5732 Tirsdager - lørdager unntatt dag etter helligdag.25) 5709 Eidsvoll - Tretten Mandager - fredager unntatt helligdager. Tretten - Dombås Tirsdager -

lørdager unntatt dag etter helligdag.26) 5715 Helligdager.27) 5716, 5737 Lørdager unntatt helligdager.28) 5718, 10353 Hverdag etter helligdag.29) 5719 Eidsvoll - Tretten Helligdag før hverdag. Tretten - Dombås Hverdag etter helligdag.30) 5733 Eidsvoll - Fåvang Mandager - fredager unntatt helligdager. Fåvang - Dombås Tirsdager -

lørdager unntatt dag etter helligdag.31) 5734 Onsdager, torsdager og fredager unntatt helligdager og dag etter helligdag. Kjøres bare

etter særskilt kunngjøring.

32) 5735 Eidsvoll - Brumunddal Mandager - torsdager unntatt helligdager. Brumunddal - Dombås Tirsdager - fredager unntatt dag etter helligdag. Kjøres bare etter særskilt kunngjøring.

33) 5736, 41630 Lørdager unntatt dag etter helligdag. Kjøres bare etter særskilt kunngjøring.34) 5738 Søndager unntatt dag etter helligdag.35) 5931 Eidsvoll - Brennhaug Fredager. Brennhaug - Dombås Lørdager.36) 5933 Mandager - torsdager unntatt helligdager og dag før helligdag.37) 5935 Eidsvoll - Kvam Mandager - torsdager unntatt helligdager og dag før helligdag. Kvam -

Dombås Tirsdager - fredager unntatt helligdager og dag etter helligdag.38) 5936 Dombås - Sjoa Mandager - fredager unntatt helligdager. Sjoa - Eidsvoll Tirsdager - lørdager

unntatt dag etter helligdag.39) 5937, 5939 Helligdag før hverdag.40) 5938 Dombås - Espa Søndager. Espa - Eidsvoll Mandager.41) 10351 Tirsdager - fredager unntatt helligdager og dag etter helligdag.42) 41629 Fredager unntatt helligdager. Kjøres bare etter særskilt kunngjøring.43) 41633, 41634 Søndager.44) 41640 Otta - Fron Torsdager unntatt helligdager. Fron - Eidsvoll Fredager unntatt dag etter

helligdag.45) 41642 Torsdager unntatt helligdager. Kjøres bare etter særskilt kunngjøring.46) 41647, 41648 Onsdager.


michot

Sticky Note

initial point edisvol

00 01 02 03 04

00 01 02 03 04

343,04

337,33

330,82

321,83

315,83

307,73

302,99

297,24

291,50

286,35

280,42

276,57

271,33

266,60

259,26

252,45

246,60

242,55

237,74237,14235,35

232,19

224,15

219,32

214,35

208,08

203,21

200,09198,26196,57

191,68190,59

187,75

184,18

180,20

174,71

168,47

162,91

155,95

152,48

148,23

144,39

139,90

136,25

133,19129,79129,41

126,26

123,85123,24

119,25

114,42

110,21

107,47

101,77

96,99

93,11

89,81

84,05

79,71

75,33

71,44 *

67,86

Km fraOslo S

DOMBÅS

Skeievoll Bp

DOVRE

BRENNHAUG

Rosten Bp

SEL

Myra Bp

OTTA

Sandbu Bp

SJOA

Kjørum Bp

KVAM

Brekka Bp

VINSTRA

FRON

HUNDORP

Frya Bp

RINGEBU

Randklev BpRingebu Pukkverk s.spKvitfjell

FÅVANG

LOSNA

Potterud Bp

TRETTEN

Nordli Bp

ØYERHafjellHunderfossenHunder Bp

FÅBERGFåberg Omformerstasjons

HOVE

LILLEHAMMER

Dallerud Bp

BERGSENG

Martoddden s.sp

BRØTTUM

BERGSVIKA

MOELV

Ringsaker Bp

RUDSHØGDAVeldre Bp

BRUMUNDDAL

Langodden Bp

JESSNESFuruberget Bp

HAMARIdeal Flatbrødfabr. s.spAkersvika Bp

OTTESTAD

STANGE

SØRLISTEINSRUD

TANGEN

ESPA

Kleverud Bp

STRANDLYKKJA

MORSKOGEN

MOLYKKJA

MINNESUND

Vettalstøen Bp

EIDSVOLL

1: 300 DOM

Kmmellomstasjon

Kryssspor-lengde

5,712: 5003: 4784: 41610: 956,51

SKE

8,99

2: 568 DOV

6,00

2: 565 BRH

RO

8,10

4,74

2: 740 SEL

5,75

MRA

5,74

2: 3903: 3604: 667 OTA

5,15

SDB

5,93

2: 620 SJO

3,85

KJØ

5,24

2: 519 KVA

4,73

BKK

7,34

2: 604 VIN

6,81

1: 640 FRN

1: 690 HUN

5,85

4,05FRY

4,81

2: 550 RBU

5,55

RANRPS

8,04

2: 880 FÅV

2: 579 LOS

4,83

4,97

POT

6,27

2: 860 TRE

4,87

NOR

6,64

2: 572 ØYE

4,89

HER

3,93

2: 652 FÅBFBS

3,57

1: 665 HVE

3,98

3: 3102: 652 LHM

5,49

DRU

6,24

2: 673 BGG

2: 740 BUM

4,21

3,65

5,56

6,96

2: 810 BVK

3,47

2: 651 MLV

4,25RKR

3,842: 700 RUD

4,49

VEL

2: 690 BRD

3,06LDN

3,402: 689 JES

3,53

FUBMRS

3,02

HMR

IFS

3,99AVI

4,83

1: 703 OTT

2: 700 STG

2,743: 606

5,70

2: 694

4,78

1: 393

SRI

STE

TAN

3,88

1: 661

3,30

5,76

2: 486

2: 680

EPA

KLR

SLY

MOR

4,34

4,38

2: 377 MOL

3,89

2: 670 MSU

3,52VET

3: 1903/5: 7004: 7705: 310 EVL

59)

5)

1719 56

159

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442933 4

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5733

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4)

5719

29)

5733

30)

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5709

25)

5708 24)

5709

25)

5253

16)

5718 28)

5936 38)

5935

37)

5935

37)

5735

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5709

25)

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4)

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32)

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5241

8)

22)


161.1EIDSVOLL - DOMBÅS Søndag 11. desember 20111) 44, 47, 322, 325, 326, 329, 330, 333, 334 Søndager - fredager.2) 306, 309, 310, 313, 314, 317, 318 Mandager - lørdager unntatt helligdager.3) 308 Dombås - Lillehammer Mandager - lørdager unntatt helligdager. Lillehammer - Eidsvoll Alle

dager.4) 405 Eidsvoll - Minnesund Søndager - fredager. Minnesund - Dombås Mandager - lørdager.5) 406 Mandager - lørdager.6) 2343 Mandager - fredager unntatt helligdager. Kjøres til og med 25. mai 2012.7) 2353 Mandager - fredager unntatt helligdager. Kjøres fra og med 29. mai 2012.8) 4801, 4802, 5241, 5242, 6210, 6212 Tirsdager.9) 4805, 4806 Lørdager.10) 4811 Mandager.11) 4813, 4820 Onsdager og fredager.12) 4817, 4822 Onsdager og torsdager.13) 4824 Hove - Brøttum Mandager. Brøttum - Eidsvoll Tirsdager.14) 4843, 4844, 41645 Torsdager unntatt helligdager.15) 5252 Tirsdager - fredager unntatt helligdager. Kjøres fra og med 29. mai 2012.16) 5253 Eidsvoll - Rudshøgda Mandager - fredager unntatt helligdager. Rudshøgda - Dombås

Tirsdager - lørdager unntatt dag etter helligdag.17) 5254 Tirsdager - fredager unntatt helligdager.Kjøres til og med 25. mai 2012.

18) 5256, 41677 Lørdager unntatt dag etter helligdag.19) 5261, 5262, 20347, 20348 Mandager og tirsdager unntatt helligdager.20) 5267, 5268 Tirsdager unntatt helligdager.21) 5269, 5270 Tirsdager unntatt helligdager. Kjøres bare etter særskilt kunngjøring.22) 5706 Dombås - Ringebu Mandager - torsdager unntatt helligdager. Ringebu - Eidsvoll Tirsdager -

fredager unntatt dag etter helligdag.23) 5707 Eidsvoll - Dovre Mandager - torsdager unntatt helligdager. Dovre - Dombås Tirsdager -

fredager unntatt dag etter helligdag.24) 5708, 5730, 5732 Tirsdager - lørdager unntatt dag etter helligdag.25) 5709 Eidsvoll - Tretten Mandager - fredager unntatt helligdager. Tretten - Dombås Tirsdager -

lørdager unntatt dag etter helligdag.26) 5715 Helligdager.27) 5716, 5737 Lørdager unntatt helligdager.28) 5718, 10353 Hverdag etter helligdag.29) 5719 Eidsvoll - Tretten Helligdag før hverdag. Tretten - Dombås Hverdag etter helligdag.30) 5733 Eidsvoll - Fåvang Mandager - fredager unntatt helligdager. Fåvang - Dombås Tirsdager -

lørdager unntatt dag etter helligdag.31) 5734 Onsdager, torsdager og fredager unntatt helligdager og dag etter helligdag. Kjøres bare

etter særskilt kunngjøring.

32) 5735 Eidsvoll - Brumunddal Mandager - torsdager unntatt helligdager. Brumunddal - Dombås Tirsdager - fredager unntatt dag etter helligdag. Kjøres bare etter særskilt kunngjøring.

33) 5736, 41630 Lørdager unntatt dag etter helligdag. Kjøres bare etter særskilt kunngjøring.34) 5738 Søndager unntatt dag etter helligdag.35) 5931 Eidsvoll - Brennhaug Fredager. Brennhaug - Dombås Lørdager.36) 5933 Mandager - torsdager unntatt helligdager og dag før helligdag.37) 5935 Eidsvoll - Kvam Mandager - torsdager unntatt helligdager og dag før helligdag. Kvam -

Dombås Tirsdager - fredager unntatt helligdager og dag etter helligdag.38) 5936 Dombås - Sjoa Mandager - fredager unntatt helligdager. Sjoa - Eidsvoll Tirsdager - lørdager

unntatt dag etter helligdag.39) 5937, 5939 Helligdag før hverdag.40) 5938 Dombås - Espa Søndager. Espa - Eidsvoll Mandager.41) 10351 Tirsdager - fredager unntatt helligdager og dag etter helligdag.42) 41629 Fredager unntatt helligdager. Kjøres bare etter særskilt kunngjøring.43) 41633, 41634 Søndager.44) 41640 Otta - Fron Torsdager unntatt helligdager. Fron - Eidsvoll Fredager unntatt dag etter

helligdag.45) 41642 Torsdager unntatt helligdager. Kjøres bare etter særskilt kunngjøring.46) 41647, 41648 Onsdager.


00 01 02 03 04 05 06

00 01 02 03 04 05 06

552,87

551,67

550,76

549,95

548,93

548,82

546,44

544,11

541,41

537,11

532,09

531,42

528,77

525,32

524,77

520,49

517,69

514,78

511,20

507,89

504,44

501,20

493,60

486,60

477,31

466,35

455,17

449,92

441,35

429,28

418,59

407,12

393,23

381,74

371,14

361,65

352,40

343,04

Km. fraOslo S

TRONDHEIM S

Skansen

TRONDHEIM M

Marienborg

Søndre Tilsving S

Stavne Bp

SELSBAKK

Kolstad Bp

HEIMDAL

NYPAN

MELHUS

Melhus Skysstasjon

SØBERG

Kvål

Kvål Bp

LER

Helgemo Bp

LUNDAMO

Horg Bp

HOVIN

Krogstad Bp

STØREN

Skjærli Bp

SOKNEDAL

GARLI

BERKÅK

ULSBERG

Markøya Pukkverk s.sp

FAGERHAUG

OPPDAL

Driva Bp

DRIVSTUA

KONGSVOLL

HJERKINN

Vålåsjø Bp

FOKSTUA

Gardsenden Bp

DOMBÅS

1: 470 MEL

TND

Km.mellomstasjon

Kryssings-sporlengde

SAV

2,11

1,94

7: 6788: 5579: 524 MBG

SS

2,38

2,33

1: 398 SLB

2,70

KOS

4,30

1: 6892: 6233: 270 HMD

5,02

1: 308 NYP

KST

1: 459 LER

3,32

4,00

1: 5822: 561 SØB

4,28

KÅL

2,80

2,91

HGM

3,58

1: 550 LMO

3,31

HRG

3,45

1: 524 HOI

3,24

7,60

1: 8222: 7003: 6314: 610 STØ

7,00

SÆR

9,29

2: 504 SDL

10,96

1: 780 GAL

11,18

2: 569 BÅK

13,89

13,82

2: 298 UBG

MPS

12,07

1: 702 FGH

10,69

2: 540 OPD

11,47

DRI

1: 710 DRS

1: 527 FOK

11,49

2: 322 KVL

10,60

1: 5492: 551 HJN

9,49

VÅL

9,25

9,36

GAE1: 3002: 5003: 4784: 41610: 95 DOM

15)

20

5)

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5709

11)

5931

21)

410

1040659

3724

)

573014)

5931

21)

10406

5735

16)

5735

16)

5933

22)

5939

25)

406 3)

5707

9)

573014)

5935

23)

5719

13)

5733

11)

5935

23)

5933

22)

573014)

5709

11)

405

2)

5935

23)

5718 12) 5939

25)

405

2)

5719

13)

5730 14)

5733

11)

5707

9)

5931

21)

406 3)

5709

11)

5735

16)

5708 10)


161.1TRONDHEIM S - DOMBÅS Søndag 11. desember 20111) 44, 47, 446, 450, 454, 10446, 10450, 10454 Søndager - fredager.2) 405 Mandager - lørdager.3) 406 Trondheim S - Soknedal søndager - fredager, Soknedal - Dombås mandager - lørdager.4) 413, 5716, 5737, 25701 Lørdager unntatt helligdager.5) 414, 5715 Helligdager.6) 417, 10382 Lørdager og helligdager.7) 418 Helligdag før hverdag.8) 5706 Mandager - torsdager unntatt helligdager.9) 5707 Tirsdager - fredager unntatt dag etter helligdag.10) 5708 Trondheim S - Kongsvoll mandager - fredager unntatt helligdager, Kongsvoll - Dombås

tirsdager - lørdager unntatt dag etter helligdag.

11) 5709, 5732, 5733 Tirsdager - lørdager unntatt dag etter helligdag.12) 5718 Trondheim S - Kongsvoll helligdag før hverdag, Kongsvoll - Dombås

hverdag etter helligdag.13) 5719 Hverdag etter helligdag.14) 5730 Trondheim S - Lundamo mandager - fredager unntatt helligdager, Lundamo - Dombås

tirsdager - lørdager unntatt dag etter helligdag.15) 5734 Onsdager, torsdager og fredager unntatt helligdager og dag etter helligdag.

Kjøres bare etter særskilt kunngjøring.16) 5735 Tirsdager - fredager unntatt dag etter helligdag. Kjøres bare etter særskilt kunngjøring.17) 5736 Lørdager unntatt dag etter helligdag. Kjøres bare etter særskilt kunngjøring.18) 5738 Søndager unntatt dag etter helligdag.

19) 5917, 5938 Søndager.20) 5920 Tirsdager.21) 5931 Lørdager.22) 5933 Dombås - Fokstua mandager - torsdager unntatt helligdager og dag før helligdag,

Fokstua - Trondheim S tirsdager - fredager unntatt helligdager og dag etter helligdag.23) 5935 Tirsdager - fredager unntatt helligdager og dag etter helligdag.24) 5937 Dombås - Garli helligdag før hverdag, Garli - Trondheim S hverdag etter helligdag.25) 5939 Dombås - Fokstua helligdag før hverdag, Fokstua - Trondheim S hverdag etter helligdag.26) 12344, 12347 Onsdager.



73

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