An integrated, dynamic approach to travel demand forecasting

This paper presents a unified approach for improving travel demand models through the application and extension of supernetwork models of multi-dimensional travel choices. Proposed quite some time ago, supernetwork models solved to stochastic user equilibrium can provide a simultaneous solution to trip generation, distribution, mode choice, and assignment that is consistent with disaggregate models and predicts their aggregate effects. The extension to incorporate the time dimension through the use of dynamic equilibrium assignment methods is proposed as an enhancement that is necessary in order to produce realistic models. A variety of theoretical and practical problems are identified whose solution underlies implementation of this approach. Recommended future research includes improved algorithms for stochastic and dynamic equilibrium assignment, new methods for calibrating assignment models, and the use of Geographic Information Systems (GIS) technology for data and model management.

[1]  Charles F. Manski,et al.  SAMPLE DESIGN FOR DISCRETE CHOICE ANALYSIS OF TRAVEL BEHAVIOR , 1978 .

[2]  Christopher C. Hatton.  GIS-T7F:a geographic information system-data input module for the traffic signal simulation model transyt-7F , 1991 .

[3]  Michael Florian,et al.  Optimal strategies: A new assignment model for transit networks , 1989 .

[4]  Yosef Sheffi,et al.  Urban Transportation Networks: Equilibrium Analysis With Mathematical Programming Methods , 1985 .

[5]  David Mahalel,et al.  EQUILIBRIUM ASSIGNMENT METHOD FOR POINTWISE FLOW DELAY RELATIONSHIPS , 1993 .

[6]  P M Allaman,et al.  New approaches to understanding travel behavior , 1982 .

[7]  Moshe Ben-Akiva,et al.  HIGHWAY ASSIGNMENT METHOD BASED ON BEHAVIORAL MODELS OF CAR DRIVERS' ROUTE CHOICE , 1989 .

[8]  Bin Ran,et al.  A COMBINED DYNAMIC MODE/DEPARTURE TIME/ROUTE CHOICE MODEL WITH MULTIPLE GROUPS OF TRAVELERS , 1992 .

[9]  Bruce N Janson,et al.  QUASI-CONTINUOUS DYNAMIC TRAFFIC ASSIGNMENT MODEL , 1995 .

[10]  C. Daganzo,et al.  Multinomial Probit and Qualitative Choice: A Computationally Efficient Algorithm , 1977 .

[11]  E Deakin,et al.  TOWARD IMPROVED REGIONAL TRANSPORTATION MODELING PRACTICE , 1991 .

[12]  Carlos F. Daganzo,et al.  Stochastic network equilibrium with multiple vehicle types and asymmetric , 1983 .

[13]  Joel L. Horowitz,et al.  A UTILITY MAXIMIZING MODEL OF THE DEMAND FOR MULTI-DESTINATION NON-WORK TRAVEL , 1980 .

[14]  Moshe Ben-Akiva,et al.  JOINT-CHOICE MODEL FOR FREQUENCY, DESTINATION, AND TRAVEL MODE FOR SHOPPING TRIPS , 1976 .

[15]  Yosef Sheffi,et al.  Aggregation and equilibrium with multinomial logit models , 1984 .

[16]  P C Baguley,et al.  CONTRAM: A TRAFFIC ASSIGNMENT MODEL FOR PREDICTING FLOWS AND QUEUES DURING PEAK PERIODS , 1978 .

[17]  Carlos F. Daganzo,et al.  Computation of Equilibrium Over Transportation Networks: The Case of Disaggregate Demand Models , 1980 .

[18]  Jordan J. Louviere,et al.  CONJOINT ANALYSIS MODELLING OF STATED PREFERENCES , 1988 .

[19]  Deepak K. Merchant,et al.  A Model and an Algorithm for the Dynamic Traffic Assignment Problems , 1978 .

[20]  Warren B. Powell,et al.  An algorithm for the equilibrium assignment problem with random link times , 1982, Networks.

[21]  Carlos F. Daganzo,et al.  HYPERNETWORKS AND SUPPLY-DEMAND EQUILIBRIUM OBTAINED WITH DISAGGREGATE DEMAND MODELS , 1978 .

[22]  C. Daganzo.  Unconstrained Extremal Formulation of Some Transportation Equilibrium Problems , 1982 .

[23]  M. Replogle,et al.  INTEGRATION OF A GEOGRAPHIC INFORMATION SYSTEM WITH COMPUTER TRANSPORTATION MODELS FOR LAND USE AND TRANSPORTATION PLANNING , 1989 .

[24]  Bruce D Spear,et al.  GENERALIZED ATTRIBUTE VARIABLE FOR MODELS OF MODE CHOICE BEHAVIOR , 1976 .

[25]  Malachy Carey.  Nonconvexity of the dynamic traffic assignment problem , 1992 .

[26]  Hani S. Mahmassani,et al.  URBAN TRAFFIC NETWORK FLOW MODELS , 1987 .

[27]  Bruce N Janson,et al.  Dynamic traffic assignment for urban road networks , 1991 .

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

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

[30]  Frank Southworth,et al.  ESTIMATING DEPARTURE TIMES FROM TRAFFIC COUNTS USING DYNAMIC ASSIGNMENT , 1992 .

[31]  J D Fricker.  TWO PROCEDURES TO CALIBRATE TRAFFIC ASSIGNMENT MODELS , 1989 .

[32]  Mike Smith,et al.  A new dynamic traffic model and the existence and calculation of dynamic user equilibria on congested capacity-constrained road networks , 1993 .

[33]  Michael R Couture,et al.  ANALYZING TRAVELER ATTITUDES TO RESOLVE INTENDED AND ACTUAL USE OF A NEW TRANSIT SERVICE , 1981 .

[34]  Howard Slavin,et al.  RAILRIDER--A COMPREHENSIVE COMMUTER RAIL FORECASTING MODEL , 1988 .

[35]  Mark S. Daskin,et al.  An examination of convergence error in equilibrium traffic assignment models , 1988 .

[36]  Thomas J Adler,et al.  Modeling non-work travel patterns , 1976 .

[37]  Frank S. Koppelman,et al.  GUIDELINES FOR AGGREGATE TRAVEL PREDICTION USING DISAGGREGATE CHOICE MODELS , 1976 .

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

[39]  Omar Drissi-Kaïtouni,et al.  A Dynamic Traffic Assignment Model and a Solution Algorithm , 1992, Transp. Sci..

[40]  Chris Hendrickson,et al.  Schedule Delay and Departure Time Decisions in a Deterministic Model , 1981 .

[41]  Alan Wilson.  Urban and regional models in geography and planning , 1974 .

[42]  Peter R. Stopher,et al.  REMOTE SENSING, MEANS, MEDIANS, AND EXTREME VALUES: SOME IMPLICATIONS FOR REDUCING AUTOMOBILE EMISSIONS , 1993 .

[43]  Howard J Simkowitz,et al.  GEOGRAPHIC INFORMATION SYSTEMS: AN IMPORTANT TECHNOLOGY FOR TRANSPORTATION PLANNING AND OPERATIONS , 1989 .

[44]  D Damm,et al.  A Theory of Activity Scheduling Behavior , 1981 .

[45]  Suzanne P. Evans,et al.  DERIVATION AND ANALYSIS OF SOME MODELS FOR COMBINING TRIP DISTRIBUTION AND ASSIGNMENT , 1976 .

[46]  Ryuichi Kitamura,et al.  Practical Method for The Estimation of Trip Generation And Trip Chaining , 1990 .

[47]  Steven R. Lerman,et al.  The Use of Disaggregate Choice Models in Semi-Markov Process Models of Trip Chaining Behavior , 1979 .

[48]  P. Schmidt,et al.  Limited-Dependent and Qualitative Variables in Econometrics. , 1984 .

[49]  Ronald W Eash.  EQUILIBRIUM TRAFFIC ASSIGNMENT WITH HIGH-OCCUPANCY VEHICLE LANES , 1993 .

[50]  Kenneth A. Small,et al.  EFFICIENT ESTIMATION OF NESTED LOGIT MODELS , 1985 .

[51]  C. Daganzo.  On the traffic assignment problem with flow dependent costs—II , 1977 .

[52]  Thomas L. Magnanti,et al.  A Combined Trip Generation, Trip Distribution, Modal Split, and Trip Assignment Model , 1988, Transp. Sci..

[53]  M. Florian.  AN INTRODUCTION TO NETWORK MODELS USED IN TRANSPORTATION PLANNING , 1984 .

[54]  D Van Vliet.  SATURN - A MODERN ASSIGNMENT MODEL , 1982 .

[55]  Moshe Ben-Akiva,et al.  Dynamic model of peak period congestion , 1984 .

[56]  Sang Nguyen,et al.  On the Combined Distribution-Assignment of Traffic , 1975 .

[57]  Michael D Meyer,et al.  PC SOFTWARE FOR URBAN TRANSPORTATION PLANNING , 1992 .

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

[59]  Moshe Ben-Akiva,et al.  Dynamic network equilibrium research , 1985 .

[60]  Hani S. Mahmassani,et al.  Some numerical results on the diagonalization algorithm for network assignment with asymmetric interactions between cars and trucks , 1988 .

[61]  Gerald L. Thompson,et al.  A Dynamic Space-Time Network Flow Model for City Traffic Congestion , 1987, Transp. Sci..