Vermelding onderdeel organisatie

1

Ingo A. Hansen, Professor for Design of Transport FacilitiesFaculty of Civil Engineering and GeosciencesTransportation and Planning Dept.i.a.hansen@citg.tudelft.nl

Capacity Increase through Optimised Timetabling

AppendixShort description of the tools developed by TU Delft

• Mining, filtering and analysis of train detection data (TNV-Prepare)• Stability analysis of network timetables (PETER)

AGRRI Network Capacity Seminar 28 November 2003 London

I.A. Hansen, Transportation and Planning Dept. 2

Tool for mining, filtering and analysis of train detection data

(1)

TNV-logfiles

Import & Filtering

Internal database

Input infra objects

(interactive)

Input train lines Timetable & route

(interactive)

Train line & Time period

Generation TNV-tables

Viewing TNV-tables

Displaying TNV-tables Export

TNV-tables

TNV-Prepare

TNV-Report

TNV-View

Construction infra network

Feasibility check routes

• Compilation of NS data records of track occupation and release indicating train # per section• Consistency proof of the routes used and times recorded• Preparation of data base with chronological and topographical order of train records

I.A. Hansen, Transportation and Planning Dept. 3

Tool for mining, filtering and analysis of train detection data

(2)Example track occupation records of IC 1500 at Eindhoven

I.A. Hansen, Transportation and Planning Dept. 4

Tool for mining, filtering and analysis of train detection data

(3)• Estimation of the braking/acceleration time from last/first measurement point until/from stop position at platform track• Comparison with scheduled arrival/ departure times according to the remaining braking/ acceleration distance• High precision of sec.

I.A. Hansen, Transportation and Planning Dept. 5

Tool for mining, filtering and analysis of train detection data

(4)

-120 -60 0 60 120 180 240 300 360 420 480 540

Arrival delays [s]

0.0

0.1

0.2

0.3

0.4

0.5

0 30 60 90 120 150 180 210 240 270 300 330

Dwell times [s]

0.0

0.1

0.2

0.3

0.4

0.5

Example distribution of arrival delays IC 2100 atThe Hague HS

Example distribution of dwell times IC 1900 atThe Hague HS

I.A. Hansen, Transportation and Planning Dept. 6

Tool for mining, filtering and analysis of train detection data

(5)

0

0.0015

0.003

0.0045

0.006

0.0075

0 120 240 360 480 600 720 840 960

Departure delays of late trains [s]

Prob

. Den

sity

Modelled Observed

Example distribution ofdeparture delays of IC Amsterdam-Vlissingenat station The Hague HS

I.A. Hansen, Transportation and Planning Dept. 7

Stability analysis tool for timetables of interconnected line

networks (1)• Model approach

– Discrete event– Dynamic system– Network model– Deterministic process times (design times)

• Model characteristics– Periodic steady-statePeriodic steady-state– Dynamic train interactionsDynamic train interactions– Slack times between eventsSlack times between events– Initial departure delaysInitial departure delays

I.A. Hansen, Transportation and Planning Dept. 8

Stability analysis tool for timetables of interconnected line

networks (2)• Analysis methods

– Critical circuit analysis (Critical circuits, minimum Critical circuit analysis (Critical circuits, minimum cycle time, throughput, stability margin)cycle time, throughput, stability margin)

• Recovery timesRecovery times– Delay impact on departing train, delay sensitivity Delay impact on departing train, delay sensitivity

of waiting train, circuit recovery timeof waiting train, circuit recovery time• Delay PropagationDelay Propagation

– Propagation initial delays through time and Propagation initial delays through time and network, settling time, total and mean network, settling time, total and mean consecutive delayconsecutive delay

I.A. Hansen, Transportation and Planning Dept. 9

Stability analysis tool for timetables of interconnected line

networks (3)• Example Dutch IC-network 2000-2001

– 29 train lines (both directions)29 train lines (both directions)– 74 stations74 stations– 334 departures/line segments334 departures/line segments– 51 transfers51 transfers

• Critical circuit analysis– Critical circuit: 19 departures, 9 train lines, 6 stationsCritical circuit: 19 departures, 9 train lines, 6 stations– Minimum cycle time:Minimum cycle time: 58:25 minutes58:25 minutes– Throughput:Throughput: 97 %97 %– Stability margin:Stability margin: 0:53 minutes0:53 minutes

I.A. Hansen, Transportation and Planning Dept. 10

Stability analysis tool for timetables of interconnected line

networks (4)Example

Dutch IC lines

I.A. Hansen, Transportation and Planning Dept. 11

Stability analysis tool for timetables of interconnected line

networks (5)Example

primary delay propagation of

IC 1700 from Utrecht to

the North

I.A. Hansen, Transportation and Planning Dept. 12

References

• Goverde, R.M.P., Hansen, I.A. (2000), “TNV-Prepare: Analysis of Dutch Railway Operations Based on Train Detection Data”, In: Allan, J., Hill, R.J., Brebbia, C.A., Sciutto, G., Sone, S. (eds.), Computers in Railways VII, WIT Press: Southampton, 779-788

• Hansen, I. (2001), “Improving railway punctuality by automatic piloting”, In: Proc. IEEE Intelligent Transportations Systems Conf. Aug. 25-29, Oakland (CA), 792-797

• Yuan, J., Goverde, R.M.P., Hansen, I.A. (2002), “Propagation of train delays in stations, In: Allan, J., Hill, R.J., Brebbia, C.A., Sciutto, G., Sone, S. (eds.), Computers in Railways VIII, WIT Press: Southampton, 975-984

• Goverde,R.M.P., Odijk, M.A. (2002), “Performance evaluation of network timetables using PETER”, In: Allan, J., Hill, R.J., Brebbia, C.A., Sciutto, G., Sone, S. (eds.), Computers in Railways VIII, WIT Press: Southampton, 731-740