IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v67y2014icp69-80.html
   My bibliography  Save this article

A dynamic pricing strategy for high occupancy toll lanes

Author

Listed:
  • Jang, Kitae
  • Chung, Koohong
  • Yeo, Hwasoo

Abstract

High Occupancy Toll (HOT) lanes are emerging as a solution to the underutilization of High Occupancy Vehicle (HOV) lanes and also a means to generate revenue for the State Departments of Transportation. This paper proposes a method to determine the toll price dynamically in response to the changes in traffic condition, and describes the procedures for estimating the essential parameters. Such parameters include expected delays, available capacity for toll-paying vehicles and distribution of travelers’ value of time (VOT). The objective function of the proposed pricing strategy can be flexibly modified to minimize delay, maximize revenue or combinations of specified levels of delay and revenue. Real-world data from a 14-mile of freeway segment in the San Francisco Bay Area are used to demonstrate the applicability and feasibility of the proposed method, and findings and implications from this case study are discussed.

Suggested Citation

  • Jang, Kitae & Chung, Koohong & Yeo, Hwasoo, 2014. "A dynamic pricing strategy for high occupancy toll lanes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 69-80.
  • Handle: RePEc:eee:transa:v:67:y:2014:i:c:p:69-80
    DOI: 10.1016/j.tra.2014.05.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856414001232
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tra.2014.05.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ozbay, Kaan & Yanmaz-Tuzel, Ozlem, 2008. "Valuation of travel time and departure time choice in the presence of time-of-day pricing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(4), pages 577-590, May.
    2. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
    3. Small, Kenneth A. & Yan, Jia, 2001. "The Value of "Value Pricing" of Roads: Second-Best Pricing and Product Differentiation," Journal of Urban Economics, Elsevier, vol. 49(2), pages 310-336, March.
    4. John Calfee & Clifford Winston & Randolph Stempski, 2001. "Econometric Issues In Estimating Consumer Preferences From Stated Preference Data: A Case Study Of The Value Of Automobile Travel Time," The Review of Economics and Statistics, MIT Press, vol. 83(4), pages 699-707, November.
    5. Calfee, John & Winston, Clifford, 1998. "The value of automobile travel time: implications for congestion policy," Journal of Public Economics, Elsevier, vol. 69(1), pages 83-102, July.
    6. Verhoef, Erik & Nijkamp, Peter & Rietveld, Piet, 1996. "Second-Best Congestion Pricing: The Case of an Untolled Alternative," Journal of Urban Economics, Elsevier, vol. 40(3), pages 279-302, November.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    8. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    9. Small, Kenneth A., 2001. "The Value of Pricing," University of California Transportation Center, Working Papers qt0rm449sx, University of California Transportation Center.
    10. Windover, John R. & Cassidy, Michael J., 2001. "Some observed details of freeway traffic evolution," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(10), pages 881-894, December.
    11. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    12. Newell, G. F., 1993. "A simplified theory of kinematic waves in highway traffic, part II: Queueing at freeway bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 289-303, August.
    13. Kenneth A. Small & Clifford Winston & Jia Yan, 2005. "Uncovering the Distribution of Motorists' Preferences for Travel Time and Reliability," Econometrica, Econometric Society, vol. 73(4), pages 1367-1382, July.
    14. Kenneth E. Train, 1998. "Recreation Demand Models with Taste Differences over People," Land Economics, University of Wisconsin Press, vol. 74(2), pages 230-239.
    15. Liu, Louie Nan & McDonald, John F., 1999. "Economic efficiency of second-best congestion pricing schemes in urban highway systems," Transportation Research Part B: Methodological, Elsevier, vol. 33(3), pages 157-188, April.
    16. Hess, Stephane & Bierlaire, Michel & Polak, John W., 2005. "Estimation of value of travel-time savings using mixed logit models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 221-236.
    17. Newell, G. F., 1993. "A simplified theory of kinematic waves in highway traffic, part I: General theory," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 281-287, August.
    18. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    19. Erik T. Verhoef & Kenneth A. Small, 2004. "Product Differentiation on Roads," Journal of Transport Economics and Policy, University of Bath, vol. 38(1), pages 127-156, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zang, Guangzhi & Xu, Meng & Gao, Ziyou, 2020. "High-occupancy vehicle lane management with tradable credit scheme: An equilibrium analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    2. Wencheng Huang & Bin Shuai & Eric Antwi, 2019. "A two-stage optimization approach for subscription bus services network design: the China case," Public Transport, Springer, vol. 11(3), pages 589-616, October.
    3. M Rouhani, Omid, 2016. "Social welfare analysis of HOV to HOT conversion," MPRA Paper 75816, University Library of Munich, Germany.
    4. Xiqun (Michael) Chen & Xiang He & Chenfeng Xiong & Zheng Zhu & Lei Zhang, 2019. "A Bayesian Stochastic Kriging Optimization Model Dealing with Heteroscedastic Simulation Noise for Freeway Traffic Management," Transportation Science, INFORMS, vol. 53(2), pages 545-565, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kenneth A. Small & Clifford Winston & Jia Yan, 2005. "Differentiated Road Pricing, Express Lanes and Carpools: Exploiting Heterogeneous Preferences in Policy Design," Working Papers 050616, University of California-Irvine, Department of Economics, revised Mar 2006.
    2. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    3. Hossan, Md Sakoat & Asgari, Hamidreza & Jin, Xia, 2016. "Investigating preference heterogeneity in Value of Time (VOT) and Value of Reliability (VOR) estimation for managed lanes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 638-649.
    4. Cantos-Sánchez, Pedro & Moner-Colonques, Rafael & Sempere-Monerris, José J. & Álvarez-SanJaime, Óscar, 2011. "Viability of new road infrastructure with heterogeneous users," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(5), pages 435-450, June.
    5. Hole, Arne Risa, 2008. "Modelling heterogeneity in patients' preferences for the attributes of a general practitioner appointment," Journal of Health Economics, Elsevier, vol. 27(4), pages 1078-1094, July.
    6. Frick, Bernd & Barros, Carlos Pestana & Prinz, Joachim, 2010. "Analysing head coach dismissals in the German "Bundesliga" with a mixed logit approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 151-159, January.
    7. Siikamaki, Juha & Layton, David F., 2007. "Discrete choice survey experiments: A comparison using flexible methods," Journal of Environmental Economics and Management, Elsevier, vol. 53(1), pages 122-139, January.
    8. Campbell, Danny & Hutchinson, W. George & Scarpa, Riccardo, 2006. "Using Discrete Choice Experiments to Derive Individual-Specific WTP Estimates for Landscape Improvements under Agri-Environmental Schemes: Evidence from the Rural Environment Protection Scheme in Irel," Sustainability Indicators and Environmental Valuation Working Papers 12220, Fondazione Eni Enrico Mattei (FEEM).
    9. Yu, Xiaojuan & van den Berg, Vincent A.C. & Verhoef, Erik T., 2019. "Carpooling with heterogeneous users in the bottleneck model," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 178-200.
    10. Mariel, Petr & Ayala, Amaya de & Hoyos, David & Abdullah, Sabah, 2013. "Selecting random parameters in discrete choice experiment for environmental valuation: A simulation experiment," Journal of choice modelling, Elsevier, vol. 7(C), pages 44-57.
    11. Haghani, Milad & Sarvi, Majid & Shahhoseini, Zahra, 2015. "Accommodating taste heterogeneity and desired substitution pattern in exit choices of pedestrian crowd evacuees using a mixed nested logit model," Journal of choice modelling, Elsevier, vol. 16(C), pages 58-68.
    12. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    13. Campbell, Danny, 2007. "Combining mixed logit models and random effects models to identify the determinants of willingness to pay for rural landscape improvements," 81st Annual Conference, April 2-4, 2007, Reading University, UK 7975, Agricultural Economics Society.
    14. Fosgerau, Mogens & Hess, Stephane, 2008. "Competing methods for representing random taste heterogeneity in discrete choice models," MPRA Paper 10038, University Library of Munich, Germany.
    15. Hess, Stephane & Rose, John M., 2009. "Allowing for intra-respondent variations in coefficients estimated on repeated choice data," Transportation Research Part B: Methodological, Elsevier, vol. 43(6), pages 708-719, July.
    16. Francisco Javier Amador Morera & Rosa Marina González Marrero, 2005. "Value of Travel Time Savings for University Students and Preference Heterogeneity," Hacienda Pública Española / Review of Public Economics, IEF, vol. 174(3), pages 25-41, September.
    17. Wongprawmas, Rungsaran & Canavari, Maurizio, 2017. "Consumers’ willingness-to-pay for food safety labels in an emerging market: The case of fresh produce in Thailand," Food Policy, Elsevier, vol. 69(C), pages 25-34.
    18. Danny Campbell & George Hutchinson & Riccardo Scarpa, 2006. "Using mixed logit models to derive individual-specific WTP estimates for landscape improvements under agri-environmental schemes: evidence from the Rural Environment Protection Scheme in Ireland," Working Papers 0607, Rural Economy and Development Programme,Teagasc.
    19. Monchambert, Guillaume, 2020. "Why do (or don’t) people carpool for long distance trips? A discrete choice experiment in France," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 911-931.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:67:y:2014:i:c:p:69-80. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.