Fosgerau, Mogens and Frejinger, Emma and Karlstrom, Anders (2013): A link based network route choice model with unrestricted choice set. Forthcoming in: Transportation Research Part B (2013)

PDF
MPRA_paper_48707.pdf Download (225kB)  Preview 
Abstract
This paper considers the path choice problem, formulating and discussing an econometric random utility model for the choice of path in a network with no restriction on the choice set. Starting from a dynamic specification of link choices we show that it is equivalent to a static model of the multinomial logit form but with infinitely many alternatives. The model can be consistently estimated and used for prediction in a computationally efficient way. Similarly to the path size logit model, we propose an attribute called link size that corrects utilities of overlapping paths but that is link additive. The model is applied to data recording path choices in a network with more than 3,000 nodes and 7,000 links.
Item Type:  MPRA Paper 

Original Title:  A link based network route choice model with unrestricted choice set 
Language:  English 
Keywords:  discrete choice; recursive logit; networks; route choice; infinite choice set 
Subjects:  C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C25  Discrete Regression and Qualitative Choice Models ; Discrete Regressors ; Proportions ; Probabilities C  Mathematical and Quantitative Methods > C5  Econometric Modeling 
Item ID:  48707 
Depositing User:  Prof. Mogens Fosgerau 
Date Deposited:  30 Jul 2013 11:55 
Last Modified:  27 Sep 2019 09:41 
References:  Aguirregabiria, V. and Mira, P. (2002). Swapping the nested fixed point algorithm: A class of estimators for discrete markov decision models, Econometrica 70(4): 1519–1543. Aguirregabiria, V. and Mira, P. (2010). Dynamic discrete choice structural models: A survey, Journal of Econometrics 156(1): 38–67. Akamatsu, T. (1996). Cyclic flows, markov process and stochastic traffic assignment, Transportation Research Part B 30(5): 369–386. Baillon, J.B. and Cominetti, R. (2008). Markovian traffic equilibrium, Mathematical Programming 111(12): 33–56. Beckmann, M., McGuire, C. and Winston, C. (1956). Studies in the Economics of Transportation, Yale University Press New Haven. Bekhor, S., BenAkiva, M. and Ramming, M. (2002). Adaptation of logit kernel to route choice situation, Transportation Research Record 1805: 78– 85. Bell, M. (1995). Alternatives to Dial’s logit assignment algorithm, Trans portation Research Part B 29(4): 287–295. Bellman, R. (1957). Dynamic Programming, Princeton University Press, Princeton. BenAkiva, M. and Bierlaire, M. (1999). Discrete choice methods and their applications to shortterm travel decisions, in R. Hall (ed.), Handbook of Transportation Science, Kluwer, pp. 5–34. Cascetta, E., Nuzzolo, A., Russo, F. and Vitetta, A. (1996). A modified logit route choice model overcoming path overlapping problems. Specification and some calibration results for interurban networks, in J. B. Lesort (ed.), Proceedings of the 13th International Symposium on Transportation and Traffic Theory, Lyon, France. DeSerpa, A. (1971). A theory of the economics of time, The Economic Journal 81(324): 828–846. Dial, R. (1971). A probabilistic multipath traffic assignment algorithm which obviates path enumeration, Transportation Research 5(2): 83–111. Dijkstra, E. (1959). A note on two problems in connexion with graphs, Numerische Mathematik 1: 269–271. Flotterod, G. and Bierlaire, M. (2013). Metropolishastings sampling of paths, Transportation Research Part B 48(1): 53 – 66. Fosgerau, M. (2006). Investigating the distribution of travel time savings, Transportation Research Part B 40(8): 688–707. Fosgerau, M., McFadden, M. and Bierlaire, M. (2013). Choice probability generating functions, Journal of Choice Modelling 8(1): 1–18. Frejinger, E. and Bierlaire, M. (2007). Capturing correlation with subnetworks in route choice models, Transportation Research Part B 41(3): 363– 378. Frejinger, E., Bierlaire, M. and BenAkiva, M. (2009). Sampling of alternatives for route choice modeling, Transportation Research Part B 43(10): 984–994. Guevara, C. A. and BenAkiva, M. E. (2013). Sampling of alternatives in multivariate extreme value (MEV) models, Transportation Research Part B 48(1): 31 – 52. Gunn, H. (2000). An introduction to the valuation of traveltime savings and losses, in D. Hensher and K. Button (eds), Handbook of Transport Modelling, Elsevier Science Ltd., chapter 26. Hensher, D. (2001). Measurement of the valuation of travel time savings, Journal of Transport Economics and Policy 35(1): 71–98. Johnson, B. (1966). Travel time and the price of leisure, Economic Inquiry 4(2): 135–145. McFadden, D. (1976). The mathematical theory of demand models, in P. Stopher and A. Meyburg (eds), Behavioral Travel Demand Models, Lexington Books, pp. 305–314. McFadden, D. (1978). Modelling the choice of residential location, in A. Karlqvist, L. Lundqvist, F. Snickars and J. Weibull (eds), Spatial Interaction Theory and Residential Location, NorthHolland, Amsterdam, pp. 75–96. Melo, E. (2012). A representative consumer theorem for discrete choice models in networked markets, Economics Letters 117(3): 862–865. Oort, C. (1969). The evaluation of travelling time, Journal of Transport Economics and Policy 3(3): 279–286. Ramming, M. (2002). Network Knowledge and Route Choice, PhD thesis, Massachusetts Institute of Technology. Ramos, G., Frejinger, E., Daamen, W. and Hoogendoorn, S. (2012). Route choice model estimation in a dynamic network based on GPS data. Presented at the 1st European Symposium on Quantitive Methods in Transportation Systems. Rust, J. (1987). Optimal replacement of GMC bus engines: An empirical model of Harold Zurcher, Econometrica 55(5): 999–1033. Saad, Y. and van der Vorst, H. (2000). Iterative solution of linear systems in the 20th century, Journal of Computational and Applied Mathematics 123(12): 1–33. Valiant, L. G. (1979). The complexity of enumeration and reliability problems, SIAM Journal on Computing 8(3): 410–421. Vovsha, P. and Bekhor, S. (1998). Linknested logit model of route choice Overcoming route overlapping problem, Transportation Research Record 1645: 133–142. 
URI:  https://mpra.ub.unimuenchen.de/id/eprint/48707 