Daily Commuting and Parking Pattern under the Fully Station-Based One-Way Carsharing Vehicle Environment
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 5
Abstract
This study is the first in the literature to investigate the joint equilibrium of departure time and parking location choices in the station-based one-way carsharing system. Time-varying road tolls are optimized to eliminate queueing deadweight loss, minimize schedule delay cost, and induce an economically efficient parking pattern. The round-trip commuting pattern under the fully privately owned vehicle environment was also studied, and the aggregate social cost of the two travel modes are compared with each other to verify the potential benefit gained from implementing the one-way carsharing service. We then investigated demand elasticity with respect to the user’s daily travel cost in a one-way carsharing-only system, and an externality-based charging mechanism is proposed to achieve the optimal demand-supply level. In the one-way carsharing-only travel mode, the following results were obtained: (1) the evening commute pattern is not a simple mirror image of the morning one when spatial parking is considered in both scenarios with and without pricing; (2) when taking account of elastic demand, in optimal time-varying pricing regimes, the charging scheme automatically leads to the socially optimal demand level, but in free-pricing regime, additional user anonymous tax must be charged to achieve the optimal demand level; and (3) the station-based one-way carsharing service benefits the public in aggregate social cost saving compared with the mode of driving a self-owned car.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work has been substantially supported by the National Natural Science Foundation of China through several projects (Nos. 72021002 and 71890973).
References
Arnott, R., A. de Palma, and R. Lindsey. 1991. “Temporal and spatial equilibrium analysis of commuter parking.” J. Public Econ. 45 (3): 301–335. https://doi.org/10.1016/0047-2727(91)90030-6.
Burns, L. D. 2013. “Sustainable mobility: A vision of our transport future.” Nature 497 (7448): 181–182. https://doi.org/10.1038/497181a.
Daganzo, C. F. 1985. “The uniqueness of a time-dependent equilibrium distribution of arrivals at a single bottleneck.” Transp. Sci. 19 (1): 29–37. https://doi.org/10.1287/trsc.19.1.29.
Dias, F. F., P. S. Lavieri, V. M. Garikapati, S. Astroza, R. M. Pendyala, and C. R. Bhat. 2017. “A behavioral choice model of the use of car-sharing and ride-sourcing services.” Transportation 44 (6): 1307–1323. https://doi.org/10.1007/s11116-017-9797-8.
Eliasson, J. 2021. “Efficient transport pricing—Why, what, and when?” Commun. Transp. Res. 1 (Dec): 100006. https://doi.org/10.1016/j.commtr.2021.100006.
Gonzales, E. J., and C. F. Daganzo. 2013. “The evening commute with cars and transit: Duality results and user equilibrium for the combined morning and evening peaks.” Transp. Res. Part B Methodol. 57 (Nov): 286–299. https://doi.org/10.1016/j.trb.2013.06.009.
He, F., Y. Yin, Z. Chen, and J. Zhou. 2015. “Pricing of parking games with atomic players.” Transp. Res. Part B Methodol. 73 (Mar): 1–12. https://doi.org/10.1016/j.trb.2014.12.003.
Huang, K., K. An, G. Correia, R. Jeppe, and W. Ma. 2021. “An innovative approach to solve the carsharing demand-supply imbalance problem under demand uncertainty.” Transp. Res. Part C Emerging Technol. 132 (Nov): 103369. https://doi.org/10.1016/j.trc.2021.103369.
Jian, S., T. H. Rashidi, K. P. Wijayaratna, and V. V. Dixit. 2016a. “A spatial hazard-based analysis for modelling vehicle selection in station-based carsharing systems.” Transp. Res. Part C Emerging Technol. 72 (Nov): 130–142. https://doi.org/10.1016/j.trc.2016.09.008.
Jian, S., D. Rey, and V. Dixit. 2016b. “Dynamic optimal vehicle relocation in carshare systems.” Transp. Res. Rec. 2567 (1): 1–9. https://doi.org/10.3141/2567-01.
Liu, Y., and Y. Li. 2017. “Pricing scheme design of ridesharing program in morning commute problem.” Transp. Res. Part C Emerging Technol. 79 (Jun): 156–177. https://doi.org/10.1016/j.trc.2017.02.020.
Ma, R., and H. M. Zhang. 2017. “The morning commute problem with ridesharing and dynamic parking charges.” Transp. Res. Part B Methodol. 106 (Dec): 345–374. https://doi.org/10.1016/j.trb.2017.07.002.
Nansubuga, B., and C. Kowalkowski. 2021. “Carsharing: A systematic literature review and research agenda.” J. Serv. Manage. 32 (6): 55–91. https://doi.org/10.1108/JOSM-10-2020-0344.
Nourinejad, M., and M. Amirgholy. 2018. Parking pricing and design in the morning commute problem with regular and autonomous vehicles. Amsterdam, Netherlands: Social Science Electronic Publishing.
Nourinejad, M., and M. J. Roorda. 2017. “Impact of hourly parking pricing on travel demand.” Transp. Res. Part A Policy Pract. 98 (Apr): 28–45. https://doi.org/10.1016/j.tra.2017.01.023.
Qin, H., E. Su, Y. Wang, J. Li, and B. Lev. 2022. “Branch-and-price-and-cut for the electric vehicle relocation problem in one-way carsharing systems.” Omega 109 (Jun): 102609. https://doi.org/10.1016/j.omega.2022.102609.
Rayle, L., D. Dai, N. Chan, R. Cervero, and S. Shaheen. 2016. “Just a better taxi? A survey-based comparison of taxis, transit, and ridesourcing services in San Francisco.” Transport Policy 45 (Jan): 168–178. https://doi.org/10.1016/j.tranpol.2015.10.004.
Shaheen, S. A., A. P. Cohen, and M. S. Chung. 2009. “North American Carsharing: 10-year retrospective.” Transp. Res. Rec. 2110 (1): 35–44. https://doi.org/10.3141/2110-05.
Smith, M. J. 1984. “The existence of a time-dependent equilibrium distribution of arrivals at a single bottleneck.” Transp. Sci. 18 (4): 385–394. https://doi.org/10.1287/trsc.18.4.385.
Wang, C., J. Bi, Q. Sai, and Z. Yuan. 2021. “Analysis and prediction of carsharing demand based on data mining methods.” Algorithms 14 (6): 179. https://doi.org/10.3390/a14060179.
Weikl, S., and K. Bogenberger. 2015. “A practice-ready relocation model for free-floating carsharing systems with electric vehicles–mesoscopic approach and field trial results.” Transp. Res. Part C Emerging Technol. 57 (Aug): 206–223. https://doi.org/10.1016/j.trc.2015.06.024.
Xiao, L. L., T. L. Liu, and H. J. Huang. 2016. “On the morning commute problem with carpooling behavior under parking space constraint.” Transp. Res. Part B Methodol. 91 (Sep): 383–407. https://doi.org/10.1016/j.trb.2016.05.014.
Zhang, S., H. Sun, Y. Lv, and J. Wu. 2021. “Day-to-day dynamics of traveler learning behavior and the incentivization scheme of the operator for one-way carsharing services.” Comput. Ind. Eng. 155 (May): 107170. https://doi.org/10.1016/j.cie.2021.107170.
Zhang, X., W. Liu, S. T. Waller, and Y. Yin. 2019. “Modelling and managing the integrated morning-evening commuting and parking patterns under the fully autonomous vehicle environment.” Transp. Res. Part B Methodol. 128 (Oct): 380–407. https://doi.org/10.1016/j.trb.2019.08.010.
Zhang, X., H. Yang, H. J. Huang, and H. M. Zhang. 2005. “Integrated scheduling of daily work activities and morning–evening commutes with bottleneck congestion.” Transp. Res. Part A Policy Pract. 39 (1): 41–60. https://doi.org/10.1016/j.tra.2004.04.005.
Zhang, X. N., H. J. Huang, and H. M. Zhang. 2008. “Integrated daily commuting patterns and optimal road tolls and parking fees in a linear city.” Transp. Res. Part B Methodol. 42 (1): 38–56. https://doi.org/10.1016/j.trb.2007.06.001.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 149 • Issue 5 • May 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Jun 21, 2022
Accepted: Nov 28, 2022
Published online: Feb 24, 2023
Published in print: May 1, 2023
Discussion open until: Jul 24, 2023
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.