This paper examines morning commute route choices of 182 drivers, with the use of disaggregated Global Positioning System–based vehicle activity data collected during a 10-day period. This paper attempts to describe how these commuters tend to behave in the real world. A binary logit model of morning commuters’ choice between a single commute route and multiple routes was established on the basis of evidence of drivers’ varying valuations of a number of route and trip characteristics as well as commuters’ sociodemographic characteristics. The research results of this paper indicate a strong relationship between the morning commute route choice decision (single versus multiple routes) and commuters’ work schedule flexibility, sociodemographic characteristics, and commute route attributes.
Get full access to this article
View all access options for this article.
References
1.
ManneringF.Poisson Analysis of Commuter Flexibility in Changing Route and Departure Time.Transportation Research Part B, Vol. 23, No. 1, 1989, pp. 53–60.
2.
AntonisseR. W., DalyA. J., and Ben-AkivaM.Highway Assignment Method Based on Behavioral Models of Car Drivers’ Route Choice. In Transportation Research Record 1220, TRB, National Research Council, Washington, D.C., 1989, pp. 1–11.
3.
JanO., HorowitzA., and PengZ.. Using Global Positioning System Data to Understand Variations in Path Choice. In Transportation Research Record: Journal of the Transportation Research Board, No. 1725, TRB, National Research Council, Washington, D.C., 2000, pp. 37–44.
4.
PolydoropoulouA., Ben-AkivaM., and KaysiI.. Influence of Traffic Information on Drivers’ Route Choice Behavior. In Transportation Research Record 1453, TRB, National Research Council, Washington, D.C., 1994, pp. 56–65.
5.
Ben-AkivaM., PalmaA. D., and KaysiI.. Dynamic Network Models and Driver Information Systems.Transportation Research Part A, Vol., 25, No. 5, 1991, pp. 251–266.
6.
DiaH.An Agent-Based Approach to Modeling Driver Route Choice, Behavior Under the Influence of Real-Time Information.Transportation Research Part C, Vol. 10, 2002, pp. 331–349.
7.
SternE., HolmE., and MaarseveenM. V.. Information and Commuters Behaviour: A Comparative Analysis.Europe on the Move, 1993, pp. 141–155.
8.
PolydoropoulouA., Ben-AkivaM., and KaysiI.. Influence of Traffic Information on Drivers’ Route Choice Behavior. In Transportation Research Record 1453, TRB, National Research Council, Washington, D.C., 1994, pp. 56–65.
9.
BovyP., and SternE.. Route Choice: Wayfinding in Transport Network.Kluwer Academic Publishers, Dordrecht, Netherlands, 1990.
10.
Abdel-AtyM. A., KitamuraR., and JovanisP. P.. Using Stated Preference Data for Studying the Effect of Advanced Traffic Information on Drivers’ Route Choice.Transportation Research Part C, Vol. 5, No. 1, 1997, pp. 39–50.
11.
KhattakA. J., SchoferJ. L., and KoppelmanF. S.. Effect of Traffic Information on Commuters’ Propensity to Change Route and Departure Time.Journal of Advanced Transportation, Vol. 29, No. 2, 1995, pp. 193–212.
12.
SrinivasanK. K., and MahmassaniH. S.. Modeling Inertia and Compliance Mechanisms in Route Choice Behavior Under Real-Time Information. In Transportation Research Record: Journal of the Transportation Research Board, No. 1725, TRB, National Research Council, Washington, D.C., 2000, pp. 45–53.
13.
KhattakA. J., SchoferJ. L., and KoppelmanF. S.. Factors Influencing Commuters’ En Route Diversion Behavior in Response to Delay. In Transportation Research Record 1318, TRB, National Research Council, Washington, D.C., 1991, pp. 125–136.
14.
ManneringF., and KimS. G.. Statistical Analysis of Commuters’ Route Choice, Mode, and Departure Time Flexibility.Transportation Research Part C, Vol. 2, No. 1, 1994, pp. 35–47.
15.
MahmassaniH. S., CapliceC. G., and WaltonC. M.. Characteristics of Urban Commuter Behavior: Switching Propensity and Use of Information. In Transportation Research Record 1285, TRB, National Research Council, Washington, D.C., 1990, pp. 57–69.
16.
LiH., GuenslerR., OgleJ., and WangJ.. Using GPS Data to Understand Day-to-Day Dynamics of Morning Commute Behavior. In Transportation Research Record: Journal of the Transportation Research Board, No. 1895, Transportation Research Board of the National Academies, Washington, D.C., 2004, pp. 78–84.
17.
Abdel-AtyM. A., VaughnK. M., KitamuraR., JovanisP. P., and ManneringF. L.. Models of Commuters’ Information Use and Route Choice: Initial Results Based on Southern California Commuter Route Choice Survey. In Transportation Research Record 1453, TRB, National Research Council, Washington, D.C., 1994, pp. 46–55.
18.
OgleJ.Quantifying Driver Speeding Behavior: Estimating Crash Risk with Vehicle Instrumentation. Ph.D. dissertation. Georgia Institute of Technology, Atlanta,2004.
19.
OgleJ., GuenslerR., and ElangoV.. Georgia's Commute Atlanta Value Pricing Program: Recruitment Methods and Travel Diary Response Rates. In Transportation Research Record: Journal of the Transportation Research Board, No. 1931, Transportation Research Board of the National Academies, Washington, D.C., 2005, pp. 28–37.
20.
LiH.Investigating Morning Commute Route Choice Behavior Using Global Positioning Systems and Multi-day Travel Data. Ph.D. dissertation. Georgia Institute of Technology, Atlanta,2004.
21.
DohertyS. T., NoelN., GosselinM., SiroisC., and UenoM.. Moving Beyond Observed Outcomes: Integrating Global Positioning Systems and Interactive Computer-Based Travel Behavior Surveys.Transportation Research Circular E-C026: Personal Travel: The Long and Short of It.TRB, National Research Council, Washington, D.C., 2001, pp. 449–466. TRB.org/trb/publications/ec026/ec026.pdf.
