Abstract
Among different stochastic user equilibrium (SUE) traffic assignment models, the Logit-based stochastic user equilibrium (SUE) is extensively investigated by researchers. It is constantly formulated as the low-level problem to describe the drivers’ route choice behavior in bi-level problems such as network design, toll optimization et al. The Probit-based SUE model receives far less attention compared with Logit-based model albeit the assignment result is more consistent with drivers’ behavior. It is well-known that due to the identical and irrelevant alternative (IIA) assumption, the Logit-based SUE model is incapable to deal with route overlapping problem and cannot account for perception variance with respect to trips. This paper aims to explore the network capacity with Probit-based traffic assignment model and investigate the differences of it is with Logit-based SUE traffic assignment models. The network capacity is formulated as a bi-level programming where the up-level program is to maximize the network capacity through optimizing input parameters (O-D multiplies and signal splits) while the low-level program is the Logit-based or Probit-based SUE problem formulated to model the drivers’ route choice. A heuristic algorithm based on sensitivity analysis of SUE problem is detailed presented to solve the proposed bi-level program. Three numerical example networks are used to discuss the differences of network capacity between Logit-based SUE constraint and Probit-based SUE constraint. This study finds that while the network capacity show different results between Probit-based SUE and Logit-based SUE constraints, the variation pattern of network capacity with respect to increased level of travelers’ information for general network under the two type of SUE problems is the same, and with certain level of travelers’ information, both of them can achieve the same maximum network capacity.
Highlights
Network capacity aims to describe the maximum demand that can be accommodated by the road network
The main difficulty to solve problem (5) with the above steps is to obtain the derivatives of equilibrium link flow with respect to signal splits la; 8a 2 A" and O-D multiplier μrs,8r,s This could be done by operating the sensitivity analysis of Probit-based stochastic user equilibrium (SUE) problem (i.e., problem (5c))
It shows that when α = 0, at which condition the SUE problem turns into be deterministic user equilibrium (DUE) problem, the corresponding optimal O-D multiplies are uAB = 2.093;uCD = 1, the same as it is calculated by Gao and Song [3]
Summary
Network capacity aims to describe the maximum demand that can be accommodated by the road network. Wong and Yang [2] first proposed the concept of reserve capacity of a general signal-controlled road network under time-stationary conditions with deterministic user equilibrium (DUE) problem It is defined as the maximum common multiplier of existing O-D demands that the network can accommodate under certain constrains. They designed a bi-level programming model to describe the network reserve capacity problem and proposed a heuristic algorithm based on sensitivity analysis of DUE problem to find the optimal settings of signal splits to maximize the network capacity. Notice that a traffic assignment model that better captures driver route choice behavior is critical for practical value (such as optimal settings of signal splits, link capacity expansion etc.) of network design problems, the Probit-based SUE problem deserves more attention.
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