Simulation-Based Dynamic Traffic Assignment Model for Mixed Traffic Flows

TLDR: In this article, a simulation-based algorithm for dynamic traffic assignment problems under mixed traffic flow considerations is proposed, which consists of an inner loop that incorporates a direction finding mechanism for the search process for System Optimization (SO) and User Equilibrium (UE) classes based on the simulation results of the current iteration.

Abstract: Traffic assignment distributes Origin-Destination (OD) trips in a network, and determines the flow patterns in a traffic network. This research aims at developing simulation-based algorithm for dynamic traffic assignment problems under mixed traffic flow considerations. Four different physical vehicle types are explicitly considered and modeled, including car, bus, motorcycle, and truck. Four different behavioral rules, pre-specified-path driver, user-equilibrium driver, system-optimization driver, and real-time information driver, are considered in the solution procedure. The DTA algorithm consists of an inner loop that incorporates a direction finding mechanism for the search process for System Optimization (SO) and User Equilibrium (UE) classes based on the simulation results of the current iteration, including experienced vehicular trip times and marginal trip times. In order to understand tripmaker acceptance toward route guidance, a survey is conducted to explore possible behavioral classifications and associated percentages. Numerical experiments are conducted in a test network to illustrate the capabilities of the simulation-based DTA procedures, and to observe how system performs under multiple user classes conditions, including multiple user behavior rules and multiple physical vehicle classes.