Travel demand management

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

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

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

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

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

6. Traditional measures 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. Road development Where the congestion is maximum, there is hardly any spaces available to widen the road. Alternate modes H uge investment , energy and other resources are required to develop, operate and maintain. Constraints – space, energy, finance, environment.

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

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

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

10. TDM measures 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. PUSH MEASURES Increasing vehicle occupancy Carpools and vanpools; Public and private transit, including bus pools. Non-motorized travel, including bicycling and walking.

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

12. TDM 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 PUSH MEASURES

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. Studies are being done to understand the impact of TDM measures on user behavior and response to verify it’s effectiveness. 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

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 TDM measures Trip chain attributes Travel options Public information Situational factors Effect on other users Goal adjustment and implementation plan Individual factors

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

17. 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. Behavioral impact of TDM measures

18. 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. Behavioral impact of TDM measures Hence, it is advised to use both push and pull measures together to achieve significant change in travel behavior.

19. 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 . User response to TDM 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. 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 ). User response to TDM measures S tudies 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. 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. User response to TDM measures 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. Results Expected car use reduction in response to the TDM measure. 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. User response to TDM measures Pull measure Push measure combination % of weekly car use 19 26 30 % of annual car use 20 18 25 Hence, combined push and pull measures displays significant reduction in car use, compared to individual measures.

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

24. Results : Group evaluating pull measure ( improved public transport ), They will switch t o 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. User response to TDM measures

25. 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. Inferences

26. 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] References