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transcript
Planning Transport Systems
Geetam Tiwari
Department of Civil Engineering &
Transportation Research and Injury Prevention Program (TRIPP)
Indian Institute of Technology Delhi(IITD)
New Delhi, India
What is Transport Planning?
• Spatial and temporal spread of activities; where we live, work, how long we travel
• Travel demand estimation and design of facilities to meet the present and future demand; how do we travel
• Long range plans for multi-modal transportation systems; roads, metro, bus system, bicycle and pedestrian facilities
Travel demand model
Existing Landuse (2001)
PLOT MATRIX: MF35: TWBSFH
MATRIX BY O/D PAIRS
04-05-17 23:13
MODULE: 3.13
SPAFOUND....kp
EMME/2 PROJECT: kp
SCENARIO : 5 kp
MATRIX : mf35 twbsfh 0
WINDOW:
541.18/5346.11
4675.2/8446.62
SCALE: 1000
PLOT MATRIX:
mf35: twbsfh
LINKS: all
CONSTRAINT: mf35: twbsfhLOWER: 0UPPER: 5EXCLUDE
2000
DESIRE LINES FOR
BASE YEAR: TWO
WHEELER TRIPS
(PCU)
4000
6000
8000
10000
Volume Scale (PCU)
Infrastructure Improvement
8 Bridges Across River Sabarmati (3
Proposed)
8 Underpass/ flyovers (11 proposed)
Problem AnalysisSolution??
• Analysis in terms of PCU (NMV, pedestrians
ignored)
• Focus on inter zonal trips, short intra zonal trips
ignored
• Focus on travel time(speed)
• Conventional method designed to promote
personal motorised trips
Planning for safe Urban transport: a multi
sector task
City systems
Landuse plans
Transportation System
Infrastructure
Technology
outcome Flows
Congestion
Pollution
Accidents
Contiguous development of low-density, high
income and high-density, low-income colonies
(enclosed within red boundary) in southern
part of Delhi
Traffic risk and urban sprawl
Authors Main Findings
(Lovegrove and
Sayed 2007)
Related number of crashes to amount of travel within
geographic unit
(Galster et al. 2001) Accounted for multifaceted nature of design and
density and their relationship to sprawl.
(Ewing et al. 2003) Created a sprawl index and examined the relationship
between this index and traffic crashes. The main
findings include sprawling areas that are associated
with more traffic and pedestrian fatalities.
(Trowbridge et al.
2009;Trowbridge
and McDonald 2008)
Constructed sprawl indices to show that sprawl is
associated with more teen driving and longer
ambulance arrival times. In both papers the authors
conclude that sprawl can lead to more traffic fatalities.
(Lambert and Meyer
2006;Lucy 2003)
Used another index of sprawl and found that sprawl is
associated with more crashes.
Table 1
Urban Density and traffic risk
• Dense urban areas are safer than lower density
suburban environments. This is because per capita
lower vehicle miles are travelled in denser areas at lower
speed as compared to low density sub urban
environments.
• Development with lower vehicle mile travelled is likely to
have lower crash rate. This is related to density,
diversity, design, and destination.
• Density in urban areas and design treatments like
narrower streets, street trees, and traffic calming
measures appear to enhance a roadway safety.
Major recommendations
• Increase density, diversity, destinations and design in
urban environments. It is expected that this promotes
narrower, shorter, more enclosed and interconnected
streets leading to safer travels.
• Density is measured by number of people, households
or jobs per unit area(acre or km2) ,
• diversity refers to mixing of commercial, residential and
industrial areas.
• involves street typology of a community which can vary
from straight interconnected streets to loops of
curvilinear streets. Design also involves sidewalks,
pedestrian crossings road side trees.
Travel patterns in different city size
0%
20%
40%
60%
80%
100%
120%
>5 mill 2-5 mill 1-2 mill .5-1 mill .1-.5mill
Chart Title
On foot Bicycle
Moped/Scooter/Motor Cycle Car/Jeep/Van
Tempo/Autorickshaw/Taxi Bus
Train Water transport
Any other No travel
Travel mode share cities1 million-> 5 million population
0% 20% 40% 60% 80% 100% 120%
North Twenty Four Parganas
Pune
Ahmadabad
Thane
Bangalore
Mumbai Suburban
Modal Share( Above 5million popn size districts)
0% 20% 40% 60% 80% 100% 120%
Haora
Surat
Gurdaspur
Coimbatore
Hyderabad
Modal Share( 2 million-5million popn size districts)
0% 20% 40% 60% 80% 100% 120%
Sambalpur
Erode
Kolhapur
East Godavari
Kendrapara
Kalahandi
Meerut
Bhopal
Modal Share( 1million-2million popn size districts)
Travel mode shares in cities (.1 million -2 million population)
0% 20% 40% 60% 80% 100% 120%
Sambalpur
Erode
Kolhapur
East Godavari
Kendrapara
Kalahandi
Meerut
Bhopal
Modal Share( 1million-2million popn size districts)
0% 20% 40% 60% 80% 100% 120%
Bhilwara
Bikaner
Kottayam
Bagalkot
Bhagalpur
Gautam Buddha Nagar
Modal Share( .5 million-1 million popn size districts)
On foot Bicycle
Moped/Scooter/Motor Cycle Car/Jeep/Van
Tempo/Autorickshaw/Taxi Bus
Train Water transport
Any other No travel
0% 20% 40% 60% 80% 100% 120%
Rajgarh
Sonitpur
Muzaffarpur
Bhiwani
Ghazipur
Modal Share( .1million-.5million popn size districts)
sustainable safe traffic system
a road environment with an infrastructure adapted to the
limitations of the road user;
vehicles equipped with technology to simplify the driving task and
provided with features that protect vulnerable and other road
users; and
road users that are well informed and adequately educated.
Fifth Annual TRIPP Lecture
Discussion on a paradigm shift
Relative contribution
Driver failures:
‘excess’
18
Safe Urban Transport
• Interaction at three levels:
Landuse planning(mode choice & exposure)
Transport infrastructure(mode choice, risk to
captive users)
Urban design( mode choice)
1. Landuse planning
Urban poor in Delhi Symbiosis between formal
and informal sectors~90% people are employed in
unorganised sector( 2002)
48% unorganised sector is
dependent on “own business”-
vendors etc.
50% women have daily wage
jobs
Women are either domestic
workers, self employed, or
street vendors.
52% women walk to work
Women have longer work days
than men
Cities within cities
Converting walking
trips tp motorised
trips- buses, RTVs,
LCVs
Long cycling trips
Time poverty of
women increases
Opportunity for
“self employed”
business reduces
Large numer of people relocated for metro
and other development projects
Planned landuse has lead to ~40,000
households relocation in 4 years
Site
Numbe
r
No. of
Househ
olds
Distanc
e from
original
site
1 8000 8 km
2 4000 7 km
3 5000 18 km
4 3000 10 km
5 2300 12 km
6 50 5 km
7 500 18 km
8 5500 23 km
9 4500 20 km
10 1000 15 km
11 4000 18 km
12 50 8 km
13 65 35 km
14 20 40 km
15 1200 25 km
Distance to main road after relocation
0
500
1000
1500
2000
2500
3000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Site NumbersD
ista
nce (
mts
)
Original
Relocated
Distance to bus-stop after relocation
0
250
500
750
1000
1250
1500
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Site Numbers
Dis
tan
ce (
mts
)
Original
Relocated
•Rehabilitation of slums results in converting nmv trips to mv trips
• avg. distance to main road
before relocation< .5 km.
•avg. distance to main road after
relocation>2 kmn
•Avg. distance to bus stop 200
m before relocation
•Avg. distance to bus stop 1
km after relocation
•Minimum distance to bus stop
before 10m, after 1km
Location of informal settlements
Informal settlements relocated by planners in Delhi 2001-2006 15-20 kms
away from the original location
self planned -
expert planned-
Captive and potential NMV usersLow income households (slums/ JJ colonies, LIG Colonies, urban villages)
• 10% - 50% households in Indian cities with Household income 100-180 USD/month
• Motorized public transport (bus)- not an affordable option
CAPTIVE RIDER GROUP
School and College students
High density (planned and unplanned)And mixed land use – Short Trip Maker
• High ownership of bicycle, low car ownership
POTENTIAL RIDER GROUP
Impact on safety
• The probability of a specific threat-victim crash = total “at-risk” kms travelled by road users in the victim’s travel mode (Uvictim× dvictim) X total distance travelled by the vehicles that pose the threat (Mthreat× dthreat).
• The mobility indicators for travel to work – distance, time and cost –have increased for 83%, 82% and 61% of the households respectively.
• The relocated households are travelling longer distances than before on arterial or national highways coming to the city. These roads do not have dedicated facilities for pedestrian, bicycles or buses.
• Aggregate data of fatal crash from 2001-2009 shows the increase in fatal crashes involving pedestrians and bicyclists
Transport Market & Latent Demand
• Changing demand
Volume/ Demand
s
er
vi
c
e
V1 V2
T1
T2
Investment in car infrastructure leads to higher
speeds(short term), increased accidents, more cars,
congestion!!!
Conflict between safety and
mobility• Higher level of service implies
higher speeds-i.e. higher
probability of fatality
0
20
40
60
80
100
0 10 20 30 40 50 60 70
Impact speed km/h
Probability of
pedestrian
fatalityPercent
Planning for safe Urban transport: a multi
sector task
City systems
Heterogeneity, Informal economy,
squatter settlements
Transportation System
Pedestrians,
Non motorised vehicles,
para transit
outcome Flows
Congestion
Pollution
Accidents
Contrasting Approaches to
Transport PlanningThe Conventional Approach:
Transport Planning and Engineering
Physical dimensions
Mobility
Traffic focus, particularly on the car
Large in scale
Street as a road
Motorised transport
Forecasting traffic
Modelling approaches
Economic evaluation
Travel as a derived demand
Demand based
Speeding up traffic
Travel time minimisation
An Alternative ApproachSustainable Mobility
• Social dimensions
• Accessibility
• People focus, either in (or on) a vehicle or on foot
• Local in scale
• Street as a space
• All modes of transport often in a hierarchy with pedestrian and cyclist at the top and car users at the bottom
• Visioning on cities
• Scenario development and modelling
• Multicriteria analysis to take account of environmental and social concerns
• Travel as a valued activity as well as a derived demand
• Management based
• Slowing movement down
• Reasonable travel times and travel time reliability
• Integration of people and traffic
IIT Delhi 2007
Seoul
Restoration of Cheonggyecheon
Decrease of car-traffic volume : 125,000 veh/day
Before After(Sep. 2005)
Infrastructure and Travel Characteristics
• Before and after the introduction of Metro system, negligible change in congestion index.
• Curitiba planned high density along the corridor, PT infrastructure has resulted in high use of PT despite high car ownership
• Bogota NMV ridership increased from .8% to 4% after NMV infrastructure
• NMV ridership increased in The Netherlands after improvement in NMV infrastructure.
SDGs
• Universal, integrated and transformative
2030 Agenda for Sustainable Development
17 Sustainable Development Goals and 169
associated targets.
• Sustainable transport has been included in 7
of the 17 goals and is covered directly by 5
targets and indirectly by 7 targets.
Transport related issued in specific targets
• Target 3.6. By 2020, halve the number of global
deaths and injuries from road traffic accidents.
• Target 7.3. By 2030, double the global rate of
improvement in energy efficiency.
• Target 9.1. Develop quality, reliable, sustainable,
and resilient infrastructure, including regional and
trans-border infrastructure, to support economic
development and human well-being, with a focus
on affordable and equitable access for all.
Transport related issued in specific targets..
• Target 11.2. By 2030, provide access to safe,
affordable, accessible, and sustainable transport
systems for all, improving road safety, notably by
expanding public transport, with special attention
to the needs of those in vulnerable situations,
women, children, persons with disabilities, and
older persons.
• Target 11.6 by 2030, reduce the adverse per
capita environmental impact of cities, including by
paying special attention to air quality, municipal
and other waste management
Transport related issued in specific targets…
• Target 12.c. Rationalize inefficient fossil-fuel
subsidies that encourage wasteful consumption by
removing market distortions, in accordance with
national circumstances, including by restructuring
taxation and phasing out those harmful subsidies,
where they exist, to reflect their environmental
impacts, taking fully into account the specific
needs and conditions of developing countries and
minimizing the possible adverse impacts on their
development in a manner that protects the poor
and the affected communities
Impact on Public Health of Reducing
Greenhouse Gas Emissions from Urban
Land Transport
Based on :Public health benefits of strategies to reduce greenhouse-gas emissions: urban
land transport. Woodcock J, Edwards P, Tonne C. et al. The Lancet: Published Online November 25, 2009DOI:10.1016/S0140-
6736(09)61714-1 39
0
10
20
30
40
50
60
70
80
90
100
Bus Motorcycle Car Bicycle Rail Walk
km p
er p
erso
n p
er w
eek
Delhi travel patterns
Baseline
2030: Lower Carbon Driving
2030: Increased Active Travel
40
Change in disease burden Change in premature
deaths
Ischaemic heart
disease11-25% 2490-7140
Cerebrovascular
disease11-25% 1270-3650
Road traffic crashes 27-69% 1170-2990
Diabetes 6-17% 180-460
Depression 2-7% NA
Delhi: Health impacts by cause
41
0
1000
2000
3000
4000
5000
6000
7000
8000
Physical activity Air pollution Road traffic collisions
DA
LYs
per
mill
ion
po
pu
lati
on
in o
ne
year
Delhi: Health impacts by pathway
42
Landuse-Transport integration for
sustainable cities
• Integrating diverse socio economic
households in master plan
• Street designs and transport system to
ensure current and potential walking and
bicycling trips
• Lessons- indicators and methods from self
organising cities.