SOLVING TRAFFIC CONGESTION FROM THE DEMAND SIDE

  • Ying-En Ge Shanghai Maritime University
  • Olegas Prentkovskis Vilnius Gediminas Technical University Department of Transport Technological Equipment Editor-in-Chief of the TRANSPORT (http://www.tandfonline.com/tran)
  • Chunyan Tang Dalian University of Technology
  • Wafaa Saleh Edinburgh Napier University
  • Michael G. H. Bell University of Sydney Business School
  • Raimundas Junevičius Vilnius Gediminas Technical University
Keywords: travel demand management, traffic congestion pricing, travel behavior, travel plans, active demand management, integrative demand management

Abstract

It is nowadays widely accepted that solving traffic congestion from the demand side is more important and more feasible than offering more capacity or facilities for transportation. Following a brief overview of evolution of the concept of Travel Demand Management (TDM), there is a discussion on the TDM foundations that include demand-side strategies, traveler choice and application settings and the new dimensions that ATDM (Active forms of Transportation and Demand Management) bring to TDM, i.e. active management and integrative management. Subsequently, the authors provide a short review of the state-of-the-art TDM focusing on relevant literature published since 2000. Next, we highlight five TDM topics that are currently hot: traffic congestion pricing, public transit and bicycles, travel behavior, travel plans and methodology. The paper closes with some concluding remarks.

Author Biographiesaaa replica rolex repwatches replica rolex watches for men replica iwc watch

Ying-En Ge, Shanghai Maritime University
-
Olegas Prentkovskis, Vilnius Gediminas Technical University Department of Transport Technological Equipment Editor-in-Chief of the TRANSPORT (http://www.tandfonline.com/tran)
-
Chunyan Tang, Dalian University of Technology
-
Wafaa Saleh, Edinburgh Napier University
-
Michael G. H. Bell, University of Sydney Business School
-
Raimundas Junevičius, Vilnius Gediminas Technical University
-

References

Luten K, Binning K, Driver D, Hall T, Schreffler E, Anderson S, Chung F, Gray J, Schor J, Ungemah D, Widby T, Wisco T. Mitigating Traffic Congestion – The Role of Demand-Side Strategies. Publication Number: FHWA-HOP-05-001, U.S. Department of Transportation Federal Highway Administration. 114 p.; 2004. Available from Internet: http://www.ops.fhwa.dot.gov/publications/mitig_traf_cong/mitig_traf_cong.pdf

FHWA. The Active Transportation and Demand Management Program (ATDM): Lessons Learned. Publication Number: FHWA-HOP-13-018, US Department of Transportation, Federal Highway Administration (FHWA), Washington, DC. 54 p.; 2013. Available from Internet: http://www.ops.fhwa.dot.gov/publications/fhwahop13018

FHWA. ATDM Program Brief: An Introduction to Active Transportation and Demand Management. Publication Number: FHWA-HOP-12-032, US Department of Transportation, Federal Highway Administration (FHWA), Washington, DC. 2 p.; 2012. Available from Internet: http://ops.fhwa.dot.gov/publications/fhwahop12032

Malić A, Brčić D, Krasić D. Parking Measures in Travel Demand Management. Promet – Traffic&Transportation. 2000; 12(5–6):301-309.

Bonsall P. Do We Know Whether Personal Travel Planning Really Works? Transport Policy. 2009; 16(6):306-314.

Taylor M. A. P. Voluntary travel Behavior Change Programs in Australia: The Carrot Rather Than The Stick in Travel Demand Management. International Journal of Sustainable Transportation. 2007; 1(3):173-192.

Ko J.; Cho Y. Voluntary program to reduce car use: weekly no-driving day in Seoul, South Korea. Transportation Research Record. 2009; (2118):1-7.

Meyer MD. Demand Management as an Element of Transportation Policy: Using Carrots And Sticks to Influence Travel Behavior. Transportation Research Part A: Policy and Practice. 1999; 33(7-8):575-599.

Ferguson E. Travel Demand Management and Public Policy. Aldershot: Ashgate Publishing Ltd.; 2000.

Kaufman M, Formanack M, Gray J, Weinberger R. Contemporary Approaches to Parking Pricing: A Primer. Publication Number: FHWA-HOP-12-026, U.S. Department of Transportation Federal Highway Administration. 48 p.; 2012. Available from Internet: http://www.ops.fhwa.dot.gov/publications/fhwahop12026/fhwahop12026.pdf

Button K. The Political Economy of Parking Charges in “First” and “Second-Best” Worlds. Transport Policy. 2006; 13(6):470-478.

Kelly JA, Clinch JP. Influence of Varied Parking Tariffs on Parking Occupancy Levels by Trip Purpose. Transport Policy. 2006; 13(6):487-495.

Zhang HM, Ge Y-E. Modeling Variable Demand Equilibrium under Second-Best Road Pricing. Transportation Research Part B: Methodological 2004; 38(8):733-749.

Friesz TL, Mookherjee R, Yao T. Securitizing Congestion: The Congestion Call Option. Transportation Research Part B: Methodological 2008; 42(5):407-437.

Yao T, Friesz TL, Wei MM, Yin Y. Congestion Derivatives for a Traffic Bottleneck. Transportation Research Part B: Methodological 2010; 44(10):1149-1165.

Lindsey CR, Van den Berg VAC, Verhoef E. Step Tolling With Bottleneck Queuing Congestion, Journal of Urban Economics 2012; 72(1):46-59.

Yang H, Huang HJ. Mathematical and Economic Theory of Road Pricing. Bingley: Elsevier Science; 2005.

Yang H, Wang X. Managing Network Mobility with Tradable Credits. Transportation Research Part B: Methodological 2011; 45(3):580-594.

Van den Berg VAC. Coarse Tolling with Heterogeneous Preferences. Transportation Research Part B: Methodological 2014; 64:1-23.

Van den Berg VAC. Step-Tolling with Price-Sensitive Demand: Why More Steps in the Toll Make the Consumer Better Off. Transportation Research Part A: Policy and Practice 2012; 46(10):1608-1622.

Xiao F, Shen W, Zhang HM. The morning commute under flat toll and tactical waiting. Transportation Research Part B: Methodological 2012; 46(10):1346-1359.

Xiao F(E), Qian Z(S), Zhang HM. The Morning Commute Problem with Coarse Toll and Nonidentical Commuters. Networks and Spatial Economics 2011; 11(2):343-369.

Ge Y-E, Stewart K. Investigating Boundary Issues Arising from Congestion Charging in a Bottleneck Scenario. In: Tampere CMJ, Viti F, Immers LHB, editors. New Developments in Transport Planning: Advances in Dynamic Traffic Assignment. Massachusetts: Edward Elgar Publishing Ltd, 2010; p. 303-326.

Stewart KJ, Ge Y-E. Optimising time-varying network flows by low-revenue tolling under dynamic user equilibrium. European Journal of Transport and Infrastructure Research 2014; 14(1):30-45.

Ge YE, Stewart K, Sun B, Ban XG, Zhang S. Investigating Undesired Spatial and Temporal Boundary Effects of Congestion Charging. Transportmetrica B: Transport Dynamics 2014; doi:10.1080/21680566.2014.961044 (in press)

Albert G, Mahalel D. Congestion Tolls and Parking Fees: A Comparison of the Potential Effect on Travel Behavior. Transport Policy 2006; 13(6):496-502.

Timilsina GR, Dulal HB. Fiscal Policy Instruments for Reducing Congestion and Atmospheric Emissions in the Transport Sector: A Review. Policy Research Working Paper WPS4652, The World Bank. 44 p. 2008. doi:10.1596/1813-9450-4652

Xing J, Takahashi H, Kameoka H. Mitigation of Expressway Traffic Congestion Through Transportation Demand Management with Toll Discount. IET Intelligent Transport Systems 2010; 4(1):50-60.

Nagae T, Akamatsu T. Dynamic revenue management of a toll road project under transportation demand uncertainty. Networks and Spatial Economics 2006; 6(3-4):345-357.

Gärling T, Schuitema G. Travel Demand Management Targeting Reduced Private Car Use: Effectiveness, Public Acceptability and Political Feasibility. Journal of Social Issues 2007; 63(1):139-153.

Habibian M, Kermanshah M. Coping with Congestion: Understanding the Role of Simultaneous Transportation Demand Management Policies on Commuters. Transport Policy 2013; (30): 229-237.

Habibian M, Kermanshah M. Exploring the role of Transportation Demand Management Policies’ Interactions. Scientia Iranica 2011; 18(5):1037-1044.

Schreffler EN, Gopalakrishna D, Smith E, Berman W. Integrating Demand Management into the Transportation Planning Process. ITE Journal 2012; 82(1):38-41.

Hendricks SJ. Four challenges to Incorporating Transportation Demand Management into the Land Development Process. Transportation Research Record 2008; (2046):30-36.

Thompson RE, Suter SN. 2012. Development of Standard Performance Measures for Transportation Demand Management Programs. Transportation Research Record 2012; (2319):47-55.

Finke T, Schreffler EN. 2004. Using Multiple Assessment Levels for Evaluating Transportation Demand Management Projects: Monitoring and Evaluation Toolkit. Transportation Research Record 2004; (1864):135-143.

Tanadtang P, Park D, Hanaoka S. Incorporating Uncertain and Incomplete Subjective Judgments into the Evaluation Procedure of Transportation Demand Management Alternatives. Transportation 2005; 32(6):603-626.

Jou R-C, Chen C-C, Chen Y-L. The Effects of Travellers’ Acceptance/Satisfaction of Unimplemented/Implemented Transportation Demand Management Strategies on Travel Behavior. Transportmetrica 2010; 7(3):201-228.

Ko J, Cho Y, Choi J, Kim TH. Evaluation of Travel Demand Management Strategies Using Importance-Performance Analysis. Transportation Research Record 2009; (2118):67-74.

Basbas S. Environmental Evaluation of Contra-Flow Bus Lanes. Journal of Environmental Protection and Ecology 2009; 10(1):222-231.

Basbas S. Environmental Evaluation of High Occupancy Vehicles (HOV) Lanes. Fresenius Environmental Bulletin 2006; 15(8A):791-797.

Buliung, RN, Soltys K, Habel C, Lanyon R. Driving Factors behind Successful Carpool Formation and Use. Transportation Research Record 2009; (2118):31-38.

Wallace B, Barnes J, Rutherford GS. Evaluating the Effects of Traveler and Trip Characteristics on Trip Chaining, with Implications for Transportation Demand Management Strategies. Transportation Research Record 2000; (1718):97-106.

Bianco MJ. Effective Transportation Demand Management: Combining Parking Pricing, Transit Incentives, and Transportation Management in a Commercial District of Portland, Oregon. Transportation Research Record 2000; (1711):46-54.

Sundo MB, Fujii S. The Effects of a Compressed Working Week on Commuters’ Daily Activity Patterns. Transportation Research Part A: Policy and Practice 2005; 39(10):835-848.

Cairns S, Newson C, Davis A. Understanding Successful Workplace Travel Initiatives in the UK. Transportation Research Part A: Policy and Practice 2010; 44(7):473-494.

Akar G, Flynn C, Namgung M. Travel Choices and Links to Transportation Demand Management: Case Study at Ohio State University. Transportation Research Record 2012; (2319):77-85.

Mongioi F, McNally L, Thompson R. Integrating Measures for Business Continuity and Transportation Demand Management to Ensure Regional Emergency Preparedness and Mobility. Transportation Research Record 2009; (2137):85-94.

Banister D, Anderton K, Bonilla D, Givoni M, Schwanen T. Transportation and the Environment. Annual Review of Environment and Resources 2011; 36: 247-270.

Ungemah D, Dusza C. Transportation Demand Management Benchmark: Results from 2008 TDM Program Survey. Transportation Research Record 2009; (2118):55-66.

FHWA. Travel Demand Management. US Department of Transportation, Federal Highway Administration (FHWA), Washington, DC.; 2004. Available from Internet: http://www.ops.fhwa.dot.gov/tdm

Knight FH. Some Fallacies in the Interpretation of Social Cost. The Quarterly Journal of Economics 1924; 38(4):582-606.

Zhang L, Liu H, Sun D(J). Comparison and Optimization of Cordon and Area Pricings for Managing Travel Demand. Transport 2014; 29(3):248-259.

Liu Z, Li C, Li C. Traffic Impact Analysis of Congestion Charge in Mega Cities. Journal of Transportation Systems Engineering and Information Technology 2009; 9(6):57-62.

Ye S. Research on Urban Road Traffic Congestion Charging Based on Sustainable Development. Physics Procedia 2012; (24B):1567-1572.

Eliasson J, Mattsson LG. Equity Effects of Congestion Pricing: Quantitative Methodology and a Case Study for Stockholm. Transportation Research Part A: Policy and Practice 2006; 40(7):602-620.

Karlström A, Franklin JP. Behavioral Adjustments and Equity Effects of Congestion Pricing: Analysis of Morning Commutes during the Stockholm Trial. Transportation Research Part A: Policy and Practice 2009; 43(3):283-296.

Kockelman KM, Lemp JD. Anticipating New-Highway Impacts: Opportunities for Welfare Analysis and Credit-Based Congestion Pricing. Transportation Research Part A: Policy and Practice 2011; 45(8):825-838.

Yang H, Zhang XN. Multiclass Network Toll Design Problem with Social and Spatial Equity Constraints. Journal of Transportation Engineering 2002; 128(5):420-428.

Wu D, Yin YF, Lawphongpanich S, Yang H. Design of More Equitable Congestion Pricing and Tradable Credit Schemes for Multimodal Transportation Networks. Transportation Research Part B: Methodological 2012; 46(9):1273-1287.

Jang K, Song MK, Choi K, Kim D-K. A bi-level framework for pricing of High-Occupancy Toll Lanes. Transport 2014; 29(3):317-325.

Grujičić D, Ivanović I, Jović J, Đorić V. Customer Perception of Service Quality in Public Transport. Transport 2014; 29(3):285-295.

Fuller D, Gauvin L, Kestens Y, Daniel M, Fournier M, Morency P, Drouin L. Use of a New Public Bicycle Share Program in Montreal, Canada. American Journal of Preventive Medicine 2011; 41(1):80-83.

Fuller D, Gauvin L, Kestens Y, Daniel M, Fournier M, Morency P, Drouin L. Impact Evaluation of a Public Bicycle Share Program on Cycling: A Case Example of BIXI in Montreal, Quebec. American Journal of Public Health 2013; 103(3):e85-e92.

Fuller D, Gauvin L, Kestens Y, Morency P, Drouin L. The potential modal shift and health benefits of implementing a public bicycle share program in Montreal, Canada. International Journal of Behavioral Nutrition and Physical Activity 2013; doi:10.1186/1479-5868-10-66

Fuller D, Gauvin L, Morency P, Kestens Y, Drouin L. The impact of implementing a public bicycle share program on the likelihood of collisions and near misses in Montreal, Canada. Preventive Medicine 2013; 57(6):920-924.

Fuller D, Sahlqvist S, Cummins S, Ogilvie D. The Impact of Public Transportation Strikes on Use of A Bicycle Share Program In London: Interrupted Time Series Design. Preventive Medicine 2012; 54(1):74-76.

Stewart K, McHale A. Cycle lanes: their effect on driver passing distances in urban areas. Transport 2014; 29(3):307-316.

Tsenkova S, Mahalek D. The impact of planning policies on bicycle-transit integration in Calgary. Urban, Planning and Transport Research 2014; 2(1):126-146.

Lin J-R, Yang T-H. Strategic Design of Public Bicycle Sharing Systems with Service Level Constraints. Transportation Research Part E: Logistics and Transportation Review 2011; 47(2):284-294.

Shu J, Chou MC, Liu Q, Teo C-P; Wang I-L. 2013. Models for Effective Deployment and Redistribution of Bicycles Within Public Bicycle-Sharing Systems. Operations Research 2013; 61(6):1346-1359.

Shaheen SA, Zhang H, Martin E, Guzman S. China’s Hangzhou Public Bicycle: Understanding Early Adoption And Behavioral Response to Bikesharing. Transportation Research Record 2011; (2247):33-41.

Bachand-Marleau J, Larsen J, El-Geneidy AM. Much-Anticipated Marriage of Cycling And Transit: How Will it Work? Transportation Research Record 2011; (2247):109-117.

Choocharukul K, Van HT, Fujii S. Psychological Effects of Travel Behavior on Preference of Residential Location Choice. Transportation Research Part A: Policy and Practice 2008; 42(1):116-124.

Carreno M, Ge Y-E, Borthwick S. Could Green Taxation Measures Help Incentivise Future Chinese Car Drivers to Purchase Low Emission Vehicles? Transport 2014; 29(3):260-268.

Al-Atawi A, Saleh W. Travel Behaviour in Saudi Arabia and the Role of Social Factors. Transport 2014; 29(3):269-277.

Zong F, Juan Z, Jia H. Examination of Staggered Shifts Impacts on Travel Behavior: A Case Study of Beijing, China. Transport 2013; 28(2):175-185.

Friman M, Larhult L, Gärling T. An Analysis of Soft Transport Policy Measures Implemented in Sweden to Reduce Private Car Use. Transportation 2013; 40(1):109-129.

Llewellyn R, Tricker R, Paton D. Travel Plans: A Critical Comparison of the Application of Land Use Planning Processes in England and Scotland. Transport 2014; 29(3):235-247.

Baslington H. School Travel Plans: Overcoming Barriers to Implementation. Transport Reviews 2008; 28(2):239-258.

Vanoutrive T. Workplace Travel Plans: Can they be Evaluated Effectively by Experts? Transportation Planning and Technology 2014; 37(8):757-774.

Yang M, Tang D, Ding H, Wang W, Luo T, Luo S. Evaluating Staggered Working Hours Using a Multi-Agent-Based Q-Learning Model. Transport 2014; 29(3):296-306.

Ficzere P, Ultmann Z, Török Á. Time–Space Analysis of Transport System Using Different Mapping Methods. Transport 2014; 29(3):278-284.

Grigonis V, Burinskienė M, Paliulis G, Ušpalytė-Vitkūnienė R, Dumbliauskas V, Barauskas A. 2014. Modelling a Passenger Car System Based on the Principles of Sustainable Mobility in Vilnius City. Transport 2014; 29(3):334-341.

Ko J, Kim D, Sin HG, Lee S. The Efficiency of Vehicle Monitoring Locations for a Voluntary Travel Demand Management Program. Transport 2014; 29(3):326-333.

Jiang Y, Li X. Travel Time Prediction Based on Historical Trajectory Data. Annals of GIS 2013; 19(1):27-35.

Ge YE, Sun BR, Zhang HM, Szeto WY, Zhou X. A Comparison of Dynamic User Optimal States with Zero, Fixed and Variable Tolerances. Networks and Spatial Economics 2015; doi:10.1007/s11067-014-9243-9

Published
2015-12-21
How to Cite
1.
Ge Y-E, Prentkovskis O, Tang C, Saleh W, Bell MGH, Junevičius R. SOLVING TRAFFIC CONGESTION FROM THE DEMAND SIDE. Promet [Internet]. 2015Dec.21 [cited 2024Dec.3];27(6):529-38. Available from: https://traffic.fpz.hr/index.php/PROMTT/article/view/1734
Section
Articles