No abstract

No abstract

This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers' route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver's route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver's route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent.

The equilibrium trip distribution–assignment model with variable destination costs (ETDA-VDC) is critical for the modeling of evacuation strategies that consider transportation network capacity. The model is an improvement over the combined distribution–assignment model because it integrates the destination cost function. With mild requirements, a rectified restriction approach was developed to generate a restricted equilibrium problem, in which the applicability of the implicit function theorem was proved. Explicit expressions of the derivatives of model variables for perturbations of input variables and parameters of the ETDA-VDC model were derived. The results of a simple numerical example were used to demonstrate four applications: sensitivity-based algorithm for the bilevel network capacity model, analysis of paradox, identification of critical parameters, and access control. The usefulness and importance of the sensitivity expressions were also demonstrated.

In transportation planning works, critical links identification is helpful to evaluate the vulnerable parts of the designed network schemes. A new capacity-based network robustness index is presented for identifying critical links and evaluating the transportation system performance. It uses the change of the total network capacity as an evaluation measure. The advanced practical network capacity model is employed to estimate the throughput of transportation system. A sensitivity analysis based algorithm is also developed to solve the practical capacity model efficiently. The capacity-based network robustness index identifies the links which play critical roles in the transportation capacity of the whole network. The capacity-based network robustness index is an effective supplementary to the existing network evaluation indices. The experiments demonstrate the differences between the capacity-based network robustness index and the efficiencybased network robustness index. The capacity-based network robustness index can be used as a practical measure in the situations where the network robustness index is not significant.