Quantifying benefits of traveler information systems to performance of transport networks prior to implementation: a double-class structured-parameter stochastic trip assignment approach

References

• Adler, J. L., Blue, V. J. and Wu, T. L.1999. Assessing driver and network performance under bi-objective route guidance systems, in Presented at the 78th Transportation Research Board; Washington, DC.
   Google Scholar
• Akamatsu, T.1996. Cyclic flows, Markov process and stochastic traffic assignment, Transportation Research, 30B, (5), 369–386.
   Google Scholar
• Al-Deek, H. and Kanafani, A.1993. Modeling the benefits of advanced traveler information systems in corridors with incidents, Transportation Research C, 1, 303–324.
   Google Scholar
• Auld, J. and Mohammadian, A.2009. Framework for the development of the agent-based dynamic activity planning and travel scheduling (ADAPTS) model, Transportation Letters, 1, (3), 245–255.
   Web of Science ®Google Scholar
• Bar Gera, H.Transportation network test problems. Available at: http://www.bgu.ac.il/∼bargera/tntp/.
   Google Scholar
• Bekhor, S. and Prashker, J.1752. Stochastic user equilibrium formulation for the generalized nested logit model, Transportation Research Record, 2001, 84–90.
   Google Scholar
• Bekhor, S., Ben-Akiva, M. and Ramming, M. S.1805. Adaptation of logit kernel to route choice situation, Transportation Research Record, 2002, 78–85.
   Google Scholar
• Bekhor, S., Reznikova, L. and Toledo, T.2003. Application of cross-nested logit route choice model in stochastic user equilibrium traffic assignment, Transportation Research Record, 2007, 41–49.
   Google Scholar
• Bekhor, S., Toledo, T. and Reznikova, L.2008. A path-based algorithm for the cross-nested logit stochastic user equilibrium traffic assignment, Computer-Aided Civil and Infrastructure Engineering, 24, 15–25.
   Web of Science ®Google Scholar
• Bell, M. G. H.1995. Alternatives to dial's logit assignment algorithm, Transportation Research, 29B, (4), 287–296.
   Google Scholar
• Ben-Akiva, M. and Bierlaire, M.1999. Discrete choice methods and their applications to short term travel decisions, in Handbook of transportation science, (ed. HallW.., 5–33; Dordrecht, Kluwer.
   Google Scholar
• Ben-Akiva, M., de Palama, A. and Kaysi, I.1991. Dynamic network models and driver information systems, Transportation Research Part A, 25, 251–266.
   Google Scholar
• Bennett, L.1993. The existence of equivalent mathematical programs for certain mixed equilibrium traffic assignment problems, European Journal of Operational Research, 71, 177–187.
   Web of Science ®Google Scholar
• Bovy, P. H. L., Bekhor, S. and Prato, G.2008. The factor of revisited path size: alternative derivation, in Transportation Research Record, Journal of the Transportation Research Board, No. 2076, 132–140; Washington, DC, Transportation Research Board of the National Academies.
   Google Scholar
• Burrell, J. E.1968. Multiple road assignment and its application to capacity restraint, in Proceeding of the 4th International Symposium on the Theory of Traffic Flow, 210–219; West Germany, Karlsruhe.
   Google Scholar
• 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 Proceeding of the 13th International Symposium on Transportation and Traffic Theory, Pergamon, Lyon, France, 697–711.
   Google Scholar
• Chen, A., Kasikitwiwat, P. and Zhaowang, J.1857. Solving the overlapping problem in route choice with paired combinatorial logit model, Transportation Research Recordno, 2003, 65–73.
   Google Scholar
• Chen, A., Ryu, S., Xu, X. and Choi, K.2014. Computation and application of the paired combinatorial logit stochastic user equilibrium problem, Computers and Operations Research, 43, 68–77.
   Web of Science ®Google Scholar
• Chu, C.1989. A paired combinatorial logit model for travel demand analysis, in Proceeding of the Fifth World Conference on Transportation Research, Vol. Vol. 4, Ventura, CA.
   Google Scholar
• Clark, C. E.1961. The greatest of a finite set of random variables, Operation Research, 9, 145–162.
   Web of Science ®Google Scholar
• Daganzo, C. F. and Sheffi, Y.1977. On stochastic models of traffic assignment, Transportation Science, 11, 253–274.
   Google Scholar
• Dial, R. B.1971. A probabilistic multipath traffic assignment algorithm which obviates path enumeration, Transportation Research, 5, 83–111.
   Google Scholar
• Fisk, C.1980. Some developments in equilibrium traffic assignment, Transportation Research, 14B, 243–255.
   Google Scholar
• Florian, M.1974. On modeling congestion in dial's probabilistic assignment model, Transportation Research, 8, 85–86.
   Google Scholar
• Frejinger, E., Bierlaire, M. and Ben-Akiva, M.2009. Sampling of alternatives for route choice modeling, Transportation Research Part B, 42, 984–994.
   Google Scholar
• Gao, S. and Huang, H.2013. Real-time traveler information for optimal adaptive routing in stochastic time-dependent networks, Transportation Research Part C, 21, 196–213.
   Web of Science ®Google Scholar
• Haghani, M., Shahhoseini, Z. and Sarvi, M.2014. Path-based stochastic traffic assignment: an investigation on the effect of choice-sets size, model specification and model calibration on prediction of static flow, in Presented in 93rd Transportation Research Board; Washington, DC.
   Google Scholar
• Hall, R. W.1996. Route choice and advanced traveler information systems on a capacitated and dynamic network, Transportation Research Part C, 4, (5), 289–306.
   Web of Science ®Google Scholar
• Harker, P.1988. Multiple equilibrium behaviors in networks, Transportation Science, 22, 39–46.
   Web of Science ®Google Scholar
• Horowitz, J. L., Sparmann, J. M. and Daganzo, F. C.1982. An investigation of the accuracy of the Clark approximation for the multinomial probit model, Transportation Science, 16, (3), 382–401.
   Web of Science ®Google Scholar
• Huang, H. and Li, Z.2007. A MuLTICLASS, multicriteria logit-based traffic equilibrium assignment model under ATIS, European Journal of Operational Research, 176, 1464–1477.
   Web of Science ®Google Scholar
• Kanafani, A. and Al-Deek, H.1991. A simple model for route guidance benefit, Transportation Research B, 25, 191–202.
   Google Scholar
• Khattak, A., Polydoropoulou, A. and Ben-Akiva, M.1537. Modeling revealed and stated pre-trip travel response to advanced traveler information systems, Transportation Research Record, 2006, 46–54.
   Google Scholar
• Lam, W. H. K., Chan, K. S., Tam, L. M. and Shi, Z. W. J.2005. Short-term travel time forecasts for transport information system in Hong Kong, Journal of Advanced Transportation, 39, (3), 289–306.
   Web of Science ®Google Scholar
• Lam, W. H. K., Chan, S. K. and Shi, Z. W. J.2002. A traffic flow simulator for short-term travel time forecasting, Journal of Advanced Transportation, 36, (3), 265–291.
   Web of Science ®Google Scholar
• Levinson, D.2003. The value of advanced traveler information systems for route choice, Transportation Research Part C, 11, 75–87.
   Web of Science ®Google Scholar
• Li, J. and Huang, L.2012. Stochastic traffic assignment considering road guidance information, Journal of Transportation Systems Engineering and Information Technology, 12, (3), 31–35.
   Google Scholar
• Li, Z. H., Huang, J. H. and Lam, W. H. K.2012. Modelling heterogeneous drivers' responses to route guidance and parking information systems in stochastic and time-dependent networks, Transportmetrica, 8, (2), 105–129.
   Web of Science ®Google Scholar
• Maher, M.1992. SAM- a stochastic assignment model, in Mathematics in transport planning and control, (ed. GriffithsJ. D.., 121–132, Oxford University Press.
   Google Scholar
• Maher, M. and Hughes, C. P.1997. A probit based stochastic user equilibrium assignment model, Transportation Research, 31B, 341–355.
   Google Scholar
• Mahmassani, S. H. and Jayakrishnan, R.1991. System performance and user response under real time information in a congested traffic corridor, Transportation Research A, 25, 293–307.
   Google Scholar
• McFadden, D.1978a. Modeling the choice of residential location, in Spatial interaction theory and residential location, (eds. KarlqvistA., LundqvistL. and WeibullJ. W.., 75–96; Amsterdam, North Holland.
   Google Scholar
• McFadden, D.1978b. Modeling the choice of residential location, Transportation Research Record, No. 673, 72–77.
   Google Scholar
• Miva, T., Okada, Y. and Morikawa, T.2010. Applying a structured dispersion parameter to multiclass stochastic user equilibrium assignment model, Transportation Research Record, 2196, 142–149.
   Google Scholar
• Nguyen, S. and Dupuis, D.1984. An efficient method for computing traffic equilibria in networks with asymmetric transportation costs, Transportation Science, 18, 185–202.
   Web of Science ®Google Scholar
• Powell, W. B. and Sheffi, Y.1982. The convergence of equilibrium algorithms with predetermined step sizes, Transportation Science, 16, 45–55.
   Web of Science ®Google Scholar
• Prashker, J. N. and Bekhor, S.1645. Investigation of stochastic network loading procedures, Transportation Research Record, 1998, 94–102.
   Google Scholar
• Prashker, J. N. and Bekhor, S.1676. Stochastic user equilibrium formulations for extended logit assignment models, Transportation Research Record, 1999, 145–152.
   Google Scholar
• Prashker, J. N. and Bekhor, S.2000. Congestion, stochastic, and similarity effects in stochastic user-equilibrium models, Transportation Research Record: Journal of the Transportation Research Board, No. 1733, 80–87.
   Google Scholar
• Prato, C. G. and Bekhor, S.2006. Applying branch-and-bound technique to route choice set generation, in Transportation Research Record: Journal of the Transportation Research Board, No. 1985, 19–28; Washington, DC, Transportation Research Board of the National Academies.
   Google Scholar
• Pravinvongvuth, S. and Chen, A.2005. Adaptation of the paired combinatorial logit model to the route choice problem, Transportmetrica, 1, (3), 223–240.
   Web of Science ®Google Scholar
• Shahhoseini, Z., Haghani, M. and Sarvi, M.2014. Estimation and application of a multi-class multi-criteria mixed paired combinatorial logit model for transport networks analysis, Transportmetrica B: Transport Dynamics, 3, (1), 59–78.
   Web of Science ®Google Scholar
• Sheffi, Y. and Powell, B. W.1981. A comparison of stochastic and deterministic traffic assignment over congested networks, Transportation Research, 15B, 53–64.
   Google Scholar
• Sheffi, Y. and Powell, B. W.1982. An algorithm for the equilibrium assignment problem for random link times, Networks, 12, (2), 191–207.
   Web of Science ®Google Scholar
• Shiftan, Y., Bekhor, S. and Albert, G.2011. Route choice behavior with pre-trip travel time information, IET Intelligent Transport Systems, 5, (3), 183–189.
   Web of Science ®Google Scholar
• Smits, E., Bliemer, M., Pel, A. and Van Arem, B.2014. On route choice models with closed-form probability expressions, in TRB 2014 Annual Meeting; Washington, DC.
   Google Scholar
• Swait, J. and Bliemer, M.2013. A strategic perspective on work mode choice behaviour: the concept of commuting plans, in International Choice Modelling Conference; Sydney.
   Google Scholar
• Swait, J. and Marley, A. A. J.2013. Probabilistic choice (models) as a result of balancing multiple goals, Journal of Mathematical Psychology, 57, 1–14.
   Web of Science ®Google Scholar
• Tobin, R. L.1977. An extension of dial's algorithm utilizing a model of trip makers' perceptions, Transportation Research, 11, 337–342.
   Google Scholar
• Train, K. E.2009. Discrete choice methods with simulation; New York, Cambridge University Press.
   Google Scholar
• Von Falkenhausen, H.1966. Traffic assignment by a stochastic model, in Proceedings of the 4th International Conference on Operational Science, 415–421.
   Google Scholar
• Vovsha, P.1997. Application of cross-nested logit model to mode choice in Tel Aviv, Israel, metropolitan area, in Transportation Research Record, No. 1607, 6–15; Washington, DC, TRB: National Research Council.
   Google Scholar
• Wardrop, J. G.1952. Some theoretical aspects of road traffic research, Proceedings of the Institution of Civil Engineers, Part II, 1, (36), 352–378.
   Google Scholar
• Wen, C. and Koppelman, S. F.2001. The generalized nested logit model, Transportation Research Part B, 35, 627–641.
   Google Scholar
• Yagi, S. and Mohammadian, A. K.2010. An activity-based microsimulation model of travel demand in the Jakarta metropolitan area, Journal of Choice Modelling, 3, (1), 32–57.
   Google Scholar
• Yai, T. and Shimizu, T.1645. Multinomial probit with structured covariance for choice situations with similar alternatives, Transportation Research Record, 1998, 69–75.
   Google Scholar
• Yai, T., Iwakura, S. and Morichi, S.1997. Multinomial probit with structured covariance for route choice behavior, Transportation Research, 31B, 195–207.
   Google Scholar
• Yang, H.1998. Multiple equilibrium behaviors and advanced traveler information systems with endogenous market penetration, Transportation Research Part B, 32, (3), 205–218.
   Google Scholar
• Zhang, L. and Levinson, D.2009. Determinants of route choice and value of traveler information: a field experiment, Transportation Research Record: Journal of the Transportation Research Board, 2086, 81–92.
   Google Scholar
• Zhong, Z., Chen, A. and Bekhor, S.2012. C-logit SUE model: alternative formulations and solution algorithm, Transportmetrica, 8, (1), 17–41.
   Web of Science ®Google Scholar