Discrete Choice Models with Applications to Departure Time and Route Choice

Discrete choice methods are constantly evolving to accommodate the requirements of specific applications. This is an exciting field of research, where a deep understanding of the underlying theoretical assumptions is necessary both to apply the models and develop new ones. In this Chapter, we have summarized the fundamental aspects of discrete choice theory, and we have introduced recent model developments, illustrating their richness. A discussion on route choice and departure time choice applications have shown how specific aspects of real applications must be addressed.

[1]  Daniel McFadden,et al.  Modelling the Choice of Residential Location , 1977 .

[2]  C. Manski The structure of random utility models , 1977 .

[3]  Michael Scott Ramming,et al.  NETWORK KNOWLEDGE AND ROUTE CHOICE , 2002 .

[4]  A. Palma,et al.  TRIP TIMING FOR PUBLIC TRANSPORTATION: AN EMPIRICAL APPLICATION. IN: TRAVEL BEHAVIOUR RESEARCH. THE LEADING EDGE , 2000 .

[5]  Robert B. Dial,et al.  Algorithm 360: shortest-path forest with topological ordering [H] , 1969, CACM.

[6]  A. Tversky Elimination by aspects: A theory of choice. , 1972 .

[7]  M. Bierlaire,et al.  Discrete Choice Methods and their Applications to Short Term Travel Decisions , 1999 .

[8]  Andrea Papola,et al.  Random utility models with implicit availability/perception of choice alternatives for the simulation of travel demand , 2001 .

[9]  D. Bolduc A practical technique to estimate multinomial probit models in transportation , 1999 .

[10]  E. Martins,et al.  An algorithm for the ranking of shortest paths , 1993 .

[11]  Michel Bierlaire,et al.  On The Overspecification of Multinomial and Nested Logit Models Due to Alternative Specific Constants , 1997, Transp. Sci..

[12]  Michel Bierlaire A general formulation of the cross-nested logit model , 2001 .

[13]  Moshe Ben-Akiva,et al.  Incorporating random constraints in discrete models of choice set generation , 1987 .

[14]  A. Papola Some development on the cross-nested logit model , 2004 .

[15]  F. Koppelman,et al.  Alternative nested logit models: structure, properties and estimation , 1998 .

[16]  C Fontan,et al.  DEPARTURE TIME CHOICE AND HETEROGENEITY OF COMMUTERS , 2001 .

[17]  Carlos F. Daganzo,et al.  On Stochastic Models of Traffic Assignment , 1977 .

[18]  R. Duncan Luce,et al.  Individual Choice Behavior: A Theoretical Analysis , 1979 .

[19]  Andrew Daly,et al.  Estimating “tree” logit models , 1987 .

[20]  Moshe Ben-Akiva,et al.  STRUCTURE OF PASSENGER TRAVEL DEMAND MODELS , 1974 .

[21]  Shlomo Bekhor,et al.  Link-Nested Logit Model of Route Choice: Overcoming Route Overlapping Problem , 1998 .

[22]  Chris Hendrickson,et al.  The flexibility of departure times for work trips , 1984 .

[23]  D. S. Bunch,et al.  Estimability in the Multinomial Probit Model , 1989 .

[24]  K. Small A Discrete Choice Model for Ordered Alternatives , 1987 .

[25]  André L. Tits,et al.  On combining feasibility, descent and superlinear convergence in inequality constrained optimization , 1993, Math. Program..

[26]  Moshe Ben-Akiva,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1985 .

[27]  John E. Dennis,et al.  Numerical methods for unconstrained optimization and nonlinear equations , 1983, Prentice Hall series in computational mathematics.

[28]  E. Cascetta,et al.  A MODIFIED LOGIT ROUTE CHOICE MODEL OVERCOMING PATH OVERLAPPING PROBLEMS. SPECIFICATION AND SOME CALIBRATION RESULTS FOR INTERURBAN NETWORKS , 1996 .

[29]  Dimitri P. Bertsekas,et al.  Nonlinear Programming , 1997 .

[30]  Gary J. Russell,et al.  A Probabilistic Choice Model for Market Segmentation and Elasticity Structure , 1989 .

[31]  N. S. Cardell,et al.  Measuring the societal impacts of automobile downsizing , 1980 .

[32]  C. Bhat Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model , 2001 .

[33]  Joan L. Walker,et al.  Hybrid Choice Models: Progress and Challenges , 2002 .

[34]  Sang Nguyen,et al.  TRAFFIC ASSIGNMENT FOR LARGE SCALE TRANSIT NETWORKS , 1987 .

[35]  Michel Bierlaire,et al.  DISCRETE CHOICE MODELS , 1998 .

[36]  Brian Everitt,et al.  An Introduction to Latent Variable Models , 1984 .

[37]  Dinesh Gopinath,et al.  Modeling heterogeneity in discrete choice proceses : application to travel demand , 1995 .

[38]  E. Gumbel,et al.  Statistics of extremes , 1960 .

[39]  R. Caflisch,et al.  Quasi-Monte Carlo integration , 1995 .

[40]  F. Koppelman,et al.  The generalized nested logit model , 2001 .

[41]  Michel Bierlaire,et al.  DEMAND SIMULATION FOR DYNAMIC TRAFFIC ASSIGNMENT , 1997 .

[42]  M. Ben-Akiva,et al.  A Multinational Probit Formulation for Large Choice Sets , 1991 .

[43]  Kenneth A. Small,et al.  THE SCHEDULING OF CONSUMER ACTIVITIES: WORK TRIPS , 1982 .

[44]  Nicholas I. M. Gould,et al.  Trust Region Methods , 2000, MOS-SIAM Series on Optimization.

[45]  W. Greene,et al.  Specification and estimation of the nested logit model: alternative normalisations , 2002 .

[46]  Robert B. Dial,et al.  A PROBABILISTIC MULTIPATH TRAFFIC ASSIGNMENT MODEL WHICH OBVIATES PATH ENUMERATION. IN: THE AUTOMOBILE , 1971 .

[47]  D. McFadden,et al.  MIXED MNL MODELS FOR DISCRETE RESPONSE , 2000 .

[48]  Jerome Spanier,et al.  Quasi-Random Methods for Estimating Integrals Using Relatively Small Samples , 1994, SIAM Rev..

[49]  M. Bierlaire The Network GEV model , 2002 .

[50]  M. Ben-Akiva,et al.  Discrete choice models with latent choice sets , 1995 .

[51]  Yoshitsugu Hayashi,et al.  International Conference on Travel Behaviour , 1986 .

[52]  Seiji Iwakura,et al.  Multinomial probit with structured covariance for route choice behavior , 1997 .

[53]  Michel Gendreau,et al.  Implicit Enumeration of Hyperpaths in a Logit Model for Transit Networks , 1992, Transp. Sci..

[54]  D. Bolduc GENERALIZED AUTOREGRESSIVE ERRORS IN THE MULTINOMIAL PROBIT MODEL , 1992 .

[55]  Joffre Swait,et al.  Choice set generation within the generalized extreme value family of discrete choice models , 2001 .

[56]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[57]  D. McFadden A Method of Simulated Moments for Estimation of Discrete Response Models Without Numerical Integration , 1989 .

[58]  Joan L. Walker Extended discrete choice models : integrated framework, flexible error structures, and latent variables , 2001 .