Most route choice models are related to revealed choice behavior and are estimated by adding alternative paths to observed routes. This paper focuses on the effects of choice set composition in route choice modeling by designing an experimental analysis of actual route choice behavior of individuals driving habitually from home to work in an urban network. The numerical analysis concentrates on a qualitative perspective, by considering path sets built with different generation techniques, and a quantitative perspective, by accounting for path sets constructed with sample size reduction from each initial choice set. Comparison of prediction accuracy across different choice sets suggests that a recently developed branch and bound algorithm generates heterogeneous routes that allow for estimating models with better prediction abilities with respect to the outcomes of the drivers' actual choices. Further, comparison of route choice models across different choice set compositions indicates that nonnested structures, such as C-logit and path size logit, yield more robust parameter estimates.
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References
1.
Ben-AkivaM. E., BergmanM. J., DalyA. J., and RamaswamyR.Modeling Inter-Urban Route Choice Behaviour. In Proc., 9th International Symposium on Transportation and Traffic Theory, VNU Science Press, Utrecht, Netherlands, 1984, pp. 299–330.
2.
De La BarraT., PerezB., and AnezJ.Multidimensional Path Search and Assignment. Presented at 21st PTRC Summer Annual Meeting, Manchester, United Kingdom, 1993.
3.
AzevedoJ. A., Santos CostaM. E. O., Silvestre MaderaJ. J. E. R., and Vieira MartinsE. Q.An Algorithm for the Ranking of Shortest Paths. European Journal of Operational Research, Vol. 69, 1993, pp. 97–106.
4.
BekhorS., Ben-AkivaM., and RammingS.Route Choice: Choice Set Generation and Probabilistic Choice Models. In Proc., 4th Triennial Symposium on Transportation Analysis Conference, University of Azores, Sao Miguel, Portugal, 2001, pp. 459–464.
5.
PratoC. G., and BekhorS.Applying Branch-and-Bound Technique to Route Choice Set Generation. In Transportation Research Record: Journal of the Transportation Research Board, No. 1985, Transportation Research Board of the National Academies, Washington, D.C., 2006, pp. 19–28.
6.
CascettaE., NuzzoloA., RussoF., and VitettaA.A Modified Logit Route Choice Model Overcoming Path Overlapping Problems: Specification and Some Calibration Results for Interurban Networks. In Proc., 13th International Symposium on Transportation and Traffic Theory, Pergamon, Lyon, France, 1996, pp. 697–711.
7.
Ben-AkivaM., and BierlaireM.Discrete Choice Methods and Their Applications to Short Term Travel Decisions. In Handbook of Transportation Science, Kluwer, Dordrecht, Netherlands, 1999, pp. 5–12.
8.
RammingS.Network Knowledge and Route Choice. PhD thesis. Massachusetts Institute of Technology, Cambridge, 2001.
9.
PrashkerJ. N., and BekhorS.Investigation of Stochastic Network Loading Procedures. In Transportation Research Record 1645, TRB, National Research Council, Washington, D.C., 1998, pp. 94–102.
10.
BekhorS., and PrashkerJ. N.Stochastic User Equilibrium Formulation for Generalized Nested Logit Model. In Transportation Research Record: Journal of the Transportation Research Board, No. 1752, TRB, National Research Council, Washington, D.C., 2001, pp. 84–90.
11.
YaiT., IwakuraS., and MorichiS.Multinomial Probit with Structured Covariance for Route Choice Behavior. Transportation Research B, Vol. 31, 1997, pp. 195–207.
12.
BekhorS., Ben-AkivaM. S., and RammingS. M.Adaptation of Logit Kernel to Route Choice Situation. In Transportation Research Record: Journal of the Transportation Research Board, No. 1805, TRB, National Research Council, Washington, D.C., 2002, pp. 78–85.
13.
BierlaireM., and FrejingerE.Route Choice Models with Subpath Components. Presented at 5th Swiss Transport Research Conference, Ascona, Switzerland, 2005.
14.
OrtuzarJ. D., and WillumsenL. G.Modelling Transport, 3rd ed. John Wiley and Sons Ltd., Chichester, United Kingdom, 2001.
15.
StopherP.Captivity and Choice in Travel Behavior Models. Transportation Journal of ASCE, Vol. 106, 1980, pp. 427–435.
16.
WilliamsH. C. W. L., and OrtuzarJ. D.Behavioural Theories of Dispersion and Mis-specification of Travel Demand Models. Transportation Research B, Vol. 16, 1982, pp. 167–219.
17.
SwaitJ., and Ben-AkivaM.Incorporating Random Constraints in Discrete Models of Choice Set Generation. Transportation Research B, Vol. 21, 1987, pp. 91–102.
18.
SwaitJ., and Ben-AkivaM.Empirical Test of a Constrained Choice Discrete Model: Mode Choice in Sao Paulo, Brazil. Transportation Research B, Vol. 21, 1987, pp. 103–115.
19.
BasarG., and BhatC. R.A Parameterized Probabilistic Consideration Set Model for Airport Choice: An Application to the San Francisco Bay Area. Transportation Research B, Vol. 38, 2004, pp. 889–904.
20.
McFaddenD.Modeling the Choice of Residential Location. In Transportation Research Record 673, TRB, National Research Council, Washington, D.C., 1978, pp. 72–77.
21.
NerellaS., and BhatC. R.Numerical Analysis of Effect of Sampling of Alternatives in Discrete Choice Models. In Transportation Research Record: Journal of the Transportation Research Board, No. 1894, Transportation Research Board of the National Academies, Washington, D.C., 2004, pp. 11–19.
22.
HansenE.Industrial Location Choice in Sao Paulo, Brazil: A Nested Logit Model. Regional Science and Urban Economics, Vol. 17, 1987, pp. 89–108.
23.
FriedmanJ., GerlowskiD., and SilbermanJ.What Attracts Foreign Multinational Corporations? Evidence from Branch Plant Location in the United States. Journal of Regional Science, Vol. 32, 1992, pp. 403–418.
24.
WoodwardD.Location Determinants of Japanese Manufacturing Start-Ups in the United States. Southern Economic Journal, Vol. 58, 1992, pp. 690–708.
25.
Ben-AkivaM., and BowmanJ. L.Integration of an Activity-Based Model System and a Residential Location Model. Urban Studies, Vol. 35, 1998, pp. 1131–1153.
26.
SermonsM. W., and KoppelmanF. S.Representing Differences Between Female and Male Commute Behavior in Residential Location Choice Models. Journal of Transport Geography, Vol. 9, 2001, pp. 101–110.
27.
BhatC. R., and GuoJ. Y.A Mixed Spatially Correlated Model: Formulation and Application to Residential Choice Modeling. Transportation Research B, Vol. 38, 2004, pp. 147–168.
28.
PozsgayM. A., and BhatC. R.Destination Choice Modeling for Home-Based Recreational Trips: Analysis and Implications for Land Use, Transportation, and Air Quality Planning. In Transportation Research Record: Journal of the Transportation Research Board, No. 1777, TRB, National Academy of Sciences, Washington, D.C., 2001, pp. 47–54.
29.
SchlichR., SimmaA., and AxhausenK. W.Destination Choice Modeling for Different Leisure Activities. Presented at 2nd Swiss Transport Research Conference, Ascona, Switzerland, 2002.
30.
Ben-AkivaM., McFaddenD., and TrainK.The Demand for Local Telephone Service: A Fully Discrete Model of Residential Calling Patterns and Service Choices. Rand Journal of Economics, Vol. 18, 1987, pp. 109–123.
31.
GilbrideT. J., and AllenbyG. M.A Choice Model with Conjunctive, Disjunctive, and Compensatory Screening Rules. Marketing Science, Vol. 23, 2004, pp. 391–406.
32.
PratoC. G., BekhorS., and PronelloC.Methodology for Exploratory Analysis of Latent Factors Influencing Drivers' Behavior. In Transportation Research Record: Journal of the Transportation Research Board, No. 1926, Transportation Research Board of the National Academies, Washington, D.C., 2005, pp. 115–125.
