Deviation between Actual and Shortest Travel Time Paths for Commuters
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 144, Issue 8
Abstract
This study evaluates routes followed by residents of the Minneapolis–St. Paul metropolitan area, as measured by the Global Positioning System (GPS) component of the 2010/11 Twin Cities Travel Behavior Inventory (TBI). It finds that most commuters used paths longer than the shortest path. This is in part a function of trip distance (+, longer distance trips deviate more), trip circuity (−, more circuitous trips deviate less), number of turns (+, trips with more turns per kilometer deviate more), age of driver (−, older drivers deviate less), employment status (+, part-time workers deviate more), flexibility in work hours (+, more flexibility deviate more), and household income (−, higher-income travelers deviate less). Some reasons for these findings are conjectured.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availabilty Statement
The raw data used for the research are accessible through the Transportation Secure Data Center (TSDC) of the National Renewable Energy Laboratory (https://www.nrel.gov/transportation/secure-transportation-data/). Details about TomTom data can be found at www.tomtom.com/licensing.
Acknowledgments
The Federal Highway Administration of the US Department of Transportation is acknowledged for funding the work presented here under a grant to the Resource Systems Group (RSG). All analysis and errors are the responsibility of the authors. A technical report representing an earlier version of this work was published as Chap. 4 of RSG (2015) Multiday GPS Travel Behavior Data for Travel Analysis (FHWA-HEP-015-026). This research is also supported by the National Natural Science Foundation of China (51178110, 51378119, and 51608115) and by the Top-notch Academic Programs Project of Jiangsu Higher Education Institutions (PPZY2015A063).
References
Bandeira, J., T. G. Almeida, A. J. Khattak, N. M. Rouphail, and M. C. Coelho. 2013. “Generating emissions information for route selection: Experimental monitoring and routes characterization.” J. Intell. Transp. Syst. 17 (1): 3–17. https://doi.org/10.1080/15472450.2012.706197.
Bekhor, S., M. E. Ben-Akiva, and M. S. Ramming. 2006. “Evaluation of choice set generation algorithms for route choice models.” Ann. Oper. Res. 144 (1): 235–247. https://doi.org/10.1007/s10479-006-0009-8.
Carrion, C., and D. Levinson. 2012a. “A model of bridge choice across the mississippi river in Minneapolis.” In Network reliability in practice, 115–129. New York: Springer.
Carrion, C., and D. Levinson. 2012b. “Value of travel time reliability: A review of current evidence.” Transp. Res. Part A: Policy Pract. 46 (4): 720–741. https://doi.org/10.1016/j.tra.2012.01.003.
Carrion, C., and D. Levinson. 2013. “Valuation of travel time reliability from a GPS-based experimental design.” Transp. Res. Part C: Emerging Technol. 35 (9): 305–323. https://doi.org/10.1016/j.trc.2012.10.010.
Chen, C., H. Gong, C. Lawson, and E. Bialostozky. 2010. “Evaluating the feasibility of a passive travel survey collection in a complex urban environment: Lessons learned from the New York City case study.” Transp. Res. Part A: Policy Pract. 44 (10): 830–840. https://doi.org/10.1016/j.tra.2010.08.004.
Cohn, N. 2009. “Real-time traffic information and navigation.” Transp. Res. Rec. 2129 (1): 129–135. https://doi.org/10.3141/2129-15.
Di, X., and H. X. Liu. 2016. “Boundedly rational travel behavior: A review of models and methodologies.” Transp. Res. Part B: Methodol. 85: 142–179. https://doi.org/10.1016/j.trb.2016.01.002.
Di, X., H. X. Liu, and X. J. Ban. 2016. “Second best toll pricing within the framework of bounded rationality.” Transp. Res. Part B: Methodol. 83: 74–90. https://doi.org/10.1016/j.trb.2015.11.002.
Di, X., H. X. Liu, J. S. Pang, and X. Ban. 2013. “Boundedly rational user equilibria (BRUE): Mathematical formulation and solution sets.” Transp. Res. Part B: Methodol. 57: 300–313. https://doi.org/10.1016/j.trb.2013.06.008.
Di, X., H. X. Liu, S. J. Zhu, and D. M. Levinson. 2017. “Indifference bands for boundedly rational route switching.” Transportation 44 (5): 1169–1194. https://doi.org/10.1007/s11116-016-9699-1.
Doherty, S. T., N. Noel, M. Lee-Gosselin, C. Sirois, M. Ueno, and F. Theberge. 2001. “Moving Beyond Observed Outcomes: Integrating Global Positioning Systems and Interactive Computer-based Travel Behaviour Surveys.” In Proc., Transportation Research Board Conf. on Personal Travel: The Long and Short of It. Washington, DC: Transportation Research Board.
Du, J., and L. Aultman-Hall. 2007. “Increasing the accuracy of trip rate information from passive multi-day GPS travel datasets: Automatic trip end identification issues.” Transp. Res. Part A: Policy Pract. 41 (3): 220–232. https://doi.org/10.1016/j.tra.2006.05.001.
Giacomin, D. J., and D. M. Levinson. 2015. “Road network circuity in metropolitan areas.” Environ. Plann. B: Plann. Des. 42 (6): 1040–1053. https://doi.org/10.1068/b130131p.
Gong, H., C. Chen, E. Bialostozky, and C. T. Lawson. 2012. “A GPS/GIS method for travel mode detection in New York City.” Comput. Environ. Urban Syst. 36 (2): 131–139. https://doi.org/10.1016/j.compenvurbsys.2011.05.003.
Kahneman, D. 2011. Thinking, fast and slow. London: Macmillan.
Levinson, D., and A. El-Geneidy. 2009. “The minimum circuity frontier and the journey to work.” Reg. Sci. Urban Econ. 39 (6): 732–738. https://doi.org/10.1016/j.regsciurbeco.2009.07.003.
Levinson, D., and S. Zhu. 2013. “A portfolio theory of route choice.” Transp. Res. Part C: Emerging Technol. 35 (9): 232–243. https://doi.org/10.1016/j.trc.2013.03.001.
Mahmassani, H. S., and G. L. Chang. 1987. “On boundedly rational user equilibrium in transportation systems.” Transp. Sci. 21 (2): 89–99. https://doi.org/10.1287/trsc.21.2.89.
Morikawa, T., T. Miwa, S. Kurauchi, T. Yamamoto, and K. Kobayashi. 2005. “Driver’s route choice behavior and its implications on network simulation and traffic assignment.” In Vol. 31 of Simulation approaches in transportation analysis, Operations Research/Computer Science Interfaces Series, edited by R. Kitamura and M. Kuwahara, 341–369. Boston, MA: Springer.
Ng, M., and K. Sathasivan. 2014. “Probabilistic modeling of erroneous human response to in-vehicle route guidance systems: A first look.” J. Intell. Transp. Syst. Res. 18 (2): 131–137. https://doi.org/10.1080/15472450.2013.785327.
Parthasarathi, P., D. Levinson, and H. Hochmair. 2013. “Network structure and travel time perception.” PLoS One 8 (10): e77718. https://doi.org/10.1371/journal.pone.0077718.
Prato, C., and S. Bekhor. 2006. “Applying branch-and-bound technique to route choice set generation.” Transp. Res. Rec. 1985 (1): 19–28.
Redmond, L. S., and P. L. Mokhtarian. 2001. “The positive utility of the commute: Modeling ideal commute time and relative desired commute amount.” Transportation 28 (2): 179–205. https://doi.org/10.1023/A:1010366321778.
Schonfelder, S., K. W. Axhausen, and M. Bierlaire. 2002. “Exploring the potentials of automatically collected GPS data for travel behaviour analysis—A Swedish data source.” GI-Technologien für Verkehr und Logistik 13: 155–179.
Simon, H. A. 1955. “A behavioral model of rational choice.” Q. J. Econ. 69 (1): 99–118. https://doi.org/10.2307/1884852.
Small, K. A., and S. Song. 1992. “‘Wasteful’ Commuting: A Resolution.” J. Political Econ. 100 (4): 888–898. https://doi.org/10.1086/261844.
Stopher, P., C. FitzGerald, and M. Xu. 2007. “Assessing the accuracy of the Sydney Household Travel Survey with GPS.” Transportation 34 (6): 723–741. https://doi.org/10.1007/s11116-007-9126-8.
Stutzer, A., and B. S. Frey. 2008. “Stress that doesn’t pay: The commuting paradox.” Scand. J. Econ. 110 (2): 339–366. https://doi.org/10.1111/j.1467-9442.2008.00542.x.
TSDC (Transportation Secure Data Center). 2017. “National Renewable Energy Laboratory.” Accessed January 15, 2017. www.nrel.gov/tsdc.
Wardrop, J. G. 1952. “Road paper. Some theoretical aspects of road traffic research.” Proc. Inst. Civ. Eng. 1 (3): 325–362. https://doi.org/10.1680/ipeds.1952.11259.
Wolf, J., R. Guensler, and W. Bachman. 2001. “Elimination of the travel diary: Experiment to derive trip purpose from Global Positioning System travel data.” Transp. Res. Rec. 1768 (1): 125–134.
Wu, X., D. Levinson, and H. Liu. 2009. “Perception of waiting time at signalized intersections.” Transp. Res. Rec. 2135 (1): 52–59.
Yao, E., and Y. Song. 2013. “Study on eco-route planning algorithm and environmental impact assessment.” J. Intell. Transp. Syst. Res. 17 (1): 42–53. https://doi.org/10.1080/15472450.2013.747822.
Zhang, L. 2011. “Behavioral foundation of route choice and traffic assignment: Comparison of principles of user equilibrium traffic assignment under different behavioral assumptions.” Transp. Res. Rec. 2254 (1): 1–10.
Zhang, L., and D. Levinson. 2008. “Determinants of route choice and value of traveler information: A field experiment.” Transp. Res. Rec. 2086 (1): 81–92.
Zhang, L., F. Xie, and D. Levinson. 2009. “Illusion of motion: Variation in value of travel time under different freeway driving conditions.” Transp. Res. Rec. 2135 (1): 34–42.
Zheng, Y., L. Liu, L. Wang, and X. Xie. 2008. “Learning transportation mode from raw gps data for geographic applications on the web.” In Proc., 17th Int. Conf. on World Wide Web, 247–256. Beijing: International Conference on World Wide Web.
Zhu, S., and D. Levinson. 2015. “Do people use the shortest path? An empirical test of Wardrop’s first principle.” PLoS One 10 (8): e0134322. https://doi.org/10.1371/journal.pone.0134322.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 144 • Issue 8 • August 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: Feb 22, 2017
Accepted: Feb 6, 2018
Published online: Jun 12, 2018
Published in print: Aug 1, 2018
Discussion open until: Nov 12, 2018
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.