1. TRAVEL DEMAND MANAGEMENT
Measures, behavioral impact and user response
Presented by : Pranav Mishra , M.Tech. 2nd semester, RCGSIDM, IIT Kharagpur

2. Introduction
Congestion..??
…this figure says it all.

3. Losses due to traffic congestion..??
Cost Time
•Cost of transporting products. •Delay for passengers.
•Cost of travel. •Delay for employees.
•Cost of business •Increased accident
potential
Life Health
•Increased carbon-dioxide emission.
•More pollution.
•More diseases.
•Mental tension.

4. How to reduce traffic congestion..??
Road development More alternate modes
•Building new roads. •More public transport systems.
•Widening existing roads. •Develop waterways wherever possible.
• Bring private participation •Expand Railway network.
•Implement Metro Rails
Really…??? Is it feasible..?
What happened to existing
What happened to existing roads? modes?
Do we have spaces to widen? Do we have enough resource
to develop new modes?

5. Vicious loop of traffic congestion
Congestion
The number of Public pressures to
movements increase capacity
increases
New capacity
The average length
of movements
increases Movements are
more easy
Urban sprawl
is favored

6. Traditional measures
Alternate modes Road development
•Huge investment ,energy •Where the congestion is maximum,
and other resources are there is hardly any spaces available to
required to develop, widen the road.
operate and maintain.
Constraints – space, energy, finance, environment.
AN ALTERNATE APPROACH
•Instead of increasing the capacity of transportation system, use the
existing system efficiently.
•Instead of increasing supply to meet demand, control demand to
meet available supply.

7. Travel Demand Management
Paradigm shift TDM
From •It aims at reducing the demand at
PREDICT and PROVIDE first place, rather than extending
To facilities to meet for ever growing
PREDICT and PREVENT demand.
CONGESTION REDUCING MEASURES
Supply side Demand side
•Efficient use of existing •Managing the existing demand.
facilities. •Controlling the growth of demand.
•Increasing the supply •Cutting down the existing demand.

8. TDM measures
PULL MEASURES PUSH MEASURES
•Traffic management. •Increasing vehicle occupancy.
•Improvement of •Influencing time and need of travel.
alternative modes. •Creating deterrence by introducing
•Integrated multi mode charges.
transport system. •Imposing restrictions.
•New technologies. •Land use and urban planning
•Pull measures aims at Demand side
attracting the road users to •Reducing the vehicle by modal
alternative modes, whereas change and HOV.
push measures tries to •Redistributing the vehicles by
demoralize car users. changing time and space of travel.

9. TDM measures
PULL MEASURES
Integrated multi mode transport system
Traffic management
• Park and Ride facilities; •Efficient use via traffic
• Kiss and Ride facilities. eng. Measures
New technologies
Improvement of alternative modes • Intelligent Transportation
• Public transportation; System.
• Para-transit; • Low emission vehicle.
• Bicycle/walking. • New underground
delivery system.

10. TDM measures
PUSH MEASURES
Increasing vehicle occupancy
Carpools and vanpools;
Public and private transit, including bus pools.
Non-motorized travel, including bicycling and walking.
Influencing time and need of travel
•Compressed work weeks, in which employees work a full 40-hour
work week in fewer than the typical 5 days.
•Flexible work schedules, which allow employees to shift their work
start and end times (and thus travel times) to less congested times
of the day.

11. TDM measures
PUSH MEASURES
Introducing charges
•Parking surcharges placed on parking lots .
•Congestion pricing.
•Increased tax on fuel.
•Vehicle ownership taxation.
Imposing restrictions
• No entry to highly congested areas.
• Time restriction for parking.
• On street parking control.

12. TDM measures
PUSH MEASURES
Land use policy and urban planning
•Compact city.
•Intensive development with mixed land uses.
•Transit oriented development.
•Location of major trip-intensive land uses in areas well served by
public transport .
•Providing a mix of local services within walking distance of their
surrounding neighborhood

13. Effectiveness of TDM measures
Traditional measures
•Increasing the supply and adding to the existing facilities is
considered most effective in reducing congestion but are also most
expensive and difficult to implement, operate and maintain.
TDM measures
•Though these are significantly cheaper and easier to implement and
maintain, there is much controversy and speculations about strength,
role and effectiveness of TDM solutions
Studies are being done to understand the impact of TDM measures
on user behavior and response to verify it’s effectiveness.

14. Behavioral impact of TDM measures
Behavioral studies
•TDM measures, when enforced, it impacts the normal behavior of
road user.
•These impacts are studied and predicted using behavioral theories.
•It is important to understand how these measures affects the
commuter’s travel options with respect to time, cost and
convenience.
•A conceptual framework is prepared to determine
•if TDM measures will affect car use or not?
•If it does, how?

15. Behavioral impact of TDM measures
Conceptual framework
Individual factors
Goal adjustment and
Public information
implementation plan
Trip chain
TDM measures Travel options
attributes
Effect on other users Situational factors

16. Behavioral impact of TDM measures
Components of frameworks
TDM measures Travel choice
•Road pricing •Stay home
•Parking fees •Car pooling
•Improved service of public •Telecommuting
transport •Chain purpose, destination, departure
•Improved walk paths times.
Trip chain attributes Individual factors Situational factors
•Travel cost •Income •Weather
•Travel time •Attitude •Time pressure
•Convenience •Work situation •Weekday
•purpose •Travel pattern •Family structure

17. Behavioral impact of TDM measures
Behavioral study
•TDM measures affects trip chain attributes that leads to a different
travel choice.
•Change in trip chain attributes may also lead to formation of goal by
road user, and travel choice to be made, will be the one that is
nearest to his goal.
•Push measures may lead to formation of goal, but for
implementation, policy makers should introduce attractive pull
measures.
•Public information of pull measures may also lead to formation of
positive goals.
•Individual and situational factors are not influenced by TDM
measures but majorly influences the goal, implementation and travel
choice.

18. Behavioral impact of TDM measures
Conclusions of Behavioral study
•Type of measures required to break a habit may not be same as
required to yield a new habit.
•A push measure may influence road user to reduce car use, but due
to lack of available beneficial alternatives, car user may not show
positive result.
•Similarly, informing road user about pull measure may attract them
to non motorized or public transport, but user may not be willing to
change his travel pattern.
•Push measures may be helpful to break the habit and pull measures
have potential to attract user to form new habits.
Hence, it is advised to use both push and pull measures together to
achieve significant change in travel behavior.

19. User response to TDM measures
Study of user response
•As it is evident from studies that different measures have different
impact on users.
•So we can say that response of users for different measures will be
different too.
•To study this user response, set of car users were asked questions on
three different hypothetical scenarios
•One push measure ( Increased tax on fuel)
•One pull measure ( reduced cost and increased frequency of
public transport )
•Combination of these two measures.
This difference in response is not only with respect to different measures
implemented but also the on the extent to which a measure is implemented.

20. User response to TDM measures
Previous studies
•Estimates of transport elasticity provides information on the extent
to which travel demand is sensitive to price changes and to changes
in public transport services
•10% increase in fuel price causes between 1% – 3% car use
reduction (Dargay, 2007).
•10% increase in bus fare has been found to lead a 4% reduction
in travelling (dargay & Hanley, 2002).
•a 10% increase in service frequency led to an average increase of
5% in ridership (Evans, 2004).
Studies have shown that a combination of one push measure and two pull
measures led to a slightly higher reduction in distance travelled by car compared
to the measures evaluated individually.

21. User response to TDM measures
Objectives are to find out:
•To what extent car users expected to reduce their car use in
response to the TDM measure.
•In response to the TDM measures, which car reducing strategies
would be used by user.
Methodology :
•Questionnaire given to identify car users with similar characteristics.
•Then three separate questionnaires for three different scenarios
were given to three different sets of respondents.
•The policy package was described in detail and possible monetary,
time, convenience and environmental benefits of respective measures
were stated.

22. User response to TDM measures
Results
•Expected car use reduction in response to the TDM measure.
Pull measure Push measure combination
% of weekly car use 19 26 30
% of annual car use 20 18 25
•Combined measure reduces significantly higher than pull measure
for weekly car use
•Combined measure reduces significantly higher than push measure
for annual car use
•There is no significant difference in individual measures for annual
car use.
Hence, combined push and pull measures displays significant reduction in car
use, compared to individual measures.

23. User response to TDM measures
Results :
•In response to the TDM measures, which car reducing strategies
would be used by user.

24. User response to TDM measures
Results :
•Group evaluating pull measure ( improved public transport ),
•They will switch to public transport only, specially for shorter
distances.
•For longer distances, they were reluctant to reduce car use.
•Group evaluating push measure ( raised tax on fuel ),
•They would prefer walking/bicycling for shorter distances.
•For moderate distances, they would prefer public transport.
•One in five, still preferred to use car.
•Group evaluating combined measure,
•They preferred cycling/walking and public transport equally for
shorter distances.
•For greater distances, they preferred public transport.

25. Inferences
•Travel demand management measures can be effective in reducing
congestion, if implemented properly.
•Not only the choice of measures, but also the extent to which the
measure to be applied, is crucial for effectiveness of measures.
•A combination of push-pull measures yields better results in car use
reduction than individual measures.

26. References
•Garling T, Eek D, Loukopoulos p, Fujii S, Stenman O J, Kitamura R, Pendyala R, Vilhelmson B, 2002, A
conceptual analyses of the impact of travel demand management on private car use, Transport policy 9,
59-70.
•Eriksson L, Nordlund A M, Garvill J, 2010, Expected car use reduction in response to travel demand
management measures, Transportation research F 13, 329-342
•Loukopoulos P, Jacobson C, Garling T, Schneider C M, Fuji S, 2003, Car user responses to travel demand
management measures: Goal intentions and choice of adaptive alternatives, International Conference on
travel behavior and research, Lucerne.
•Victoria transport policy institute, [Internet, www], Address : http://www.vtpi.org/tdm/ [Accessed on 29
mach 2012]
• NSW Government, Transport: roads and maritime services, [Internet, www], Address:
http://www.rta.nsw.gov.au/usingroads/traveldemandmanagement/index.html, [Accessed on 29 march
2012]
• Auckland transport, [Internet, www], Address:
http://www.arc.govt.nz/albany/fms/main/Documents/Transport/RLTS/Chapter%208.pdf , [Accessed on
24 march 2012]