Effects of Users’ Bounded Rationality on a Traffic Network Performance: A Simulation Study

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.

Regional Dynamic Traffic Assignment Framework for Macroscopic Fundamental Diagram Multi-regions Models

“…This will allow to account for the variation of the trip length distributions variances in the calculation of the regional network equilibrium. We also plan to extend this methodological framework to account for different kinds of drivers' behavior, such as bounded rational (Mahmassani and Chang 1987, Di and Liu 2016, Batista, Zhao, and Leclercq 2018 and regret-aversion (Chorus 2014, Li andHuang 2016), as well as heterogeneous preferences for more reliable travel times.…”

“…Prato 2009 (Simon 1957, 1966, Mahmassani and Chang 1987, Di et al 2013, 2014, Batista, Zhao, and Leclercq 2018. The trip choices of drivers are driven by aspiration levels that represent a set of target variables that should be satisfied, i.e.…”

A Traffic Assignment Model Based on Link Densities

“…The precise formulation depends on how these factors are incorporated. Surveys of this class of models are found in Daganzo and Sheffi [17], Hazelton [18], Ramming [19], Prashker and Bekhor [20], Karoonsoontawong and Lin [21], Li and Huang [22], and Batista et al [23]. These formulations constitute an extension of the deterministic equilibrium models.…”

Graph-based ahead monitoring of vulnerabilities in large dynamic transportation networks

“…In fact, even in the presence of smart trip planners that take into account global and real-time traffic conditions, traffic unbalance still exists due to sudden appearance of disruptions and accidents. Similarly, travel information can direct the network state towards inefficient equilibria, due the presence of unequipped users’ as well as selfish or bounded-rational behaviors from equipped ones [ 1 , 2 ].…”