Sensitivity analysis of the probit-based stochastic user equilibrium assignment model

Abstract The probit-based stochastic user equilibrium (SUE) model has the advantage of being able to represent perceptual differences in utility across the driver population, while taking proper account of the natural correlations in these utilities between overlapping routes within the network (which the simpler logit SUE is unable to do). Its main drawback is the potentially heavy computational demands, and this has previously been thought to preclude a consideration of the sensitivity analysis of probit-based SUE, whereby an approximation to changes in the equilibrium solution is deduced as its input parameters (specifically origin/destination (O–D) flows and link cost-flow function parameters) are perturbed. In the present paper, an efficient computational method for performing such an analysis for general networks is described. This approach uses information on SUE path flows, but is not specific to any particular equilibrium solution algorithm. Problems inherent in the consideration of general network topologies are identified, and methods proposed for overcoming them. The paper concludes with an application of the method to a realistic network, and compares the approximate solutions with those obtained by direct estimation methods.

[1]  Mike Smith,et al.  The existence, uniqueness and stability of traffic equilibria , 1979 .

[2]  Terry L. Friesz,et al.  Sensitivity Analysis for Equilibrium Network Flow , 1988, Transp. Sci..

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

[4]  M. A. Hall,et al.  Properties of the Equilibrium State in Transportation Networks , 1978 .

[5]  Hai Yang,et al.  An algorithm for the inflow control problem on urban freeway networks with user-optimal flows , 1994 .

[6]  P. Hughes,et al.  A PROBIT-BASED STOCHASTIC USER EQUILIBRIUM ASSIGNMENT MODEL , 1997 .

[7]  Hai Yang,et al.  TRAFFIC RESTRAINT, ROAD PRICING AND NETWORK EQUILIBRIUM , 1997 .

[8]  Carlos F. Daganzo,et al.  Multinomial Probit: The Theory and its Application to Demand Forecasting. , 1980 .

[9]  A. Nijenhuis Combinatorial algorithms , 1975 .

[10]  Fabien M Leurent SENSITIVITY AND ERROR ANALYSIS OF THE DUAL CRITERIA TRAFFIC ASSIGNMENT MODEL , 1998 .

[11]  Hai Yang,et al.  Sensitivity analysis for the elastic-demand network equilibrium problem with applications , 1997 .

[12]  Stephen D. Clark,et al.  Probit-Based Sensitivity Analysis for General Traffic Networks , 2000 .

[13]  Stella Dafermos,et al.  Traffic Equilibrium and Variational Inequalities , 1980 .

[14]  Joseph A. C. Delaney Sensitivity analysis , 2018, The African Continental Free Trade Area: Economic and Distributional Effects.

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

[16]  William H. Press,et al.  Numerical recipes in C , 2002 .

[17]  Yang Hai,et al.  Sensitivity analysis for queuing equilibrium network flow and its application to traffic control , 1995 .

[18]  Bin Ran,et al.  Dynamic Urban Transportation Network Models , 1994 .

[19]  Anna Nagurney,et al.  Sensitivity analysis for the asymmetric network equilibrium problem , 1984, Math. Program..

[20]  Hai Yang,et al.  Estimation of origin-destination matrices from link traffic counts on congested networks , 1992 .

[21]  Gary A. Davis,et al.  Exact local solution of the continuous network design problem via stochastic user equilibrium assignment , 1994 .

[22]  F Leurent AN ANALYSIS OF MODELLING ERROR, WITH APPLICATION TO A TRAFFIC ASSIGNMENT MODEL WITH CONTINUOUSLY DISTRIBUTED VALUES OF TIME , 1996 .

[23]  D. Watling Asymmetric problems and stochastic process models of traffic assignment , 1996 .

[24]  Benjamin Heydecker,et al.  Some Consequences of Detailed Junction Modeling in Road Traffic Assignment , 1983 .

[25]  Toshihide Ibaraki,et al.  Optimal scheduling policies in time sharing service systems , 1995 .

[26]  Thomas L. Magnanti,et al.  Network Design and Transportation Planning: Models and Algorithms , 1984, Transp. Sci..

[27]  Y Iida,et al.  Transportation Network Analysis , 1997 .