Abstract
In this paper, we revisit the principle of bounded rationality applied to dynamic traffic assignment to evaluate its influences on network performance. We investigate the influence of different types of bounded rational user behavior on (i) route flows at equilibrium and (ii) network performance in terms of its internal, inflow, and outflow capacities. We consider the implementation of a bounded rational framework based on Monte Carlo simulation. A Lighthill-Whitham-Richards (LWR) mesoscopic traffic simulator is considered to calculate time-dependent route costs that account for congestion, spillback, and shock-wave effects. Network equilibrium is calculated using the Method of Successive Averages. As a benchmark, the results are compared against both Deterministic and Stochastic User Equilibrium. To model different types of bounded rational user behavior we consider two definitions of user search order (indifferent and strict preferences) and two settings of the indifference band. We also test the framework on a toy Braess network to gain insight into changes in the route flows at equilibrium for both search orders and increasing values of aspiration levels.
Highlights
The first notions of traffic assignment were introduced by Wardrop (1952)
According to the first Wardrop principle, users aim to minimize their personal route travel times. This leads to a network equilibrium called the Deterministic User Equilibrium (DUE) and it is that most commonly used in dynamic traffic assignment (DTA) problems
We investigated the influence of two types of bounded rational behavior, considering users preferences for the search order, on individual route flows and network performance
Summary
The first notions of traffic assignment were introduced by Wardrop (1952). According to the first Wardrop principle, users aim to minimize their personal route travel times. We focus on the application of the notion of bounded rationality in a dynamic context, by considering distributions of route travel times and a traffic simulator. To the authors knowledge, there is no study in the literature that investigates the influence of users preferences (indifferent and strict) for a bounded rational behavior on individual route flows and network performance in terms of the internal level of congestion and inflow and outflow capacities. To model bounded rationality behavior, we relax the definition of the search order of the DUE and SUE frameworks (Sheffi, 1985) In both the DUE and SUE cases, users are assigned to the routes with the minimum travel times based on an all-or-nothing procedure.
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