Liang-Chieh (Victor) Cheng, Heng Wang

Modeling User Equilibrium in Microscopic Transportation Simulation

Introduction

Modeling user equilibrium in microscopic transportation simulation. Model user equilibrium in microscopic transportation simulation using TRANSIMS. Develop heuristics for dynamic traffic assignment to achieve efficient system-wide equilibrium.

Abstract

User equilibrium refers to the network-wide state where individual travelers cannot gain improvement by unilaterally changing their behaviors. The Wardropian Equilibrium has been the focus of a transportation equilibrium study. This paper modifies the dynamic traffic assignment method through utilizing the TRANSIMS system to reach the dynamic user equilibrium state in a microscopic model. The focus of research is developing three heuristics in a Routing-Microsimulation-Equilibrating order for reaching system-wide equilibrium while simultaneously minimizing the computing burden and execution. The heuristics are implemented to a TRANSIMS model to simulate a subarea of Houston, TX.

Review

This paper addresses the significant challenge of modeling user equilibrium within the context of microscopic transportation simulations, a crucial area for advanced traffic management and planning. Focusing on the well-established Wardropian equilibrium principle, the authors propose a modification to dynamic traffic assignment (DTA) methods specifically tailored for the TRANSIMS system. The overall objective is to achieve a dynamic user equilibrium state, acknowledging the inherent complexities and computational intensity of working with detailed microscopic models. The core of the research lies in the development of three distinct heuristics, structured in a "Routing-Microsimulation-Equilibrating" order. This methodological sequence represents a key contribution, as it aims to guide the system towards equilibrium while simultaneously addressing the critical need to minimize computational burden and execution time. The practical implementation of these heuristics within a TRANSIMS model, applied to a subarea of Houston, TX, suggests a tangible application and validation of the proposed framework in a realistic setting. While the abstract clearly outlines the problem and the general approach, a reviewer would seek further details on the specific mechanisms of the developed heuristics and their quantitative impact on computational efficiency. A clearer exposition of how these heuristics achieve "system-wide equilibrium" and how their performance compares to other existing DTA algorithms in terms of convergence speed and quality of equilibrium would significantly enhance the paper's contribution. Nonetheless, the focus on practical applicability by reducing computational overhead in microscopic DUE is highly relevant and holds promise for advancing the field.

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