Modeling and optimization of traffic flow

Abstract

As part of the Intelligent Transportation System (ITS), traffic flow modeling and optimization have become widely employed because of their significant economic efficiency, safety, repeatability, usability, and controllability properties. This study justifies the selection of Shenzhen and Qingdao as simulation sites and delves into the simulation approach, encompassing static road network modeling, vehicle movement modeling, output analysis, and control system research. The primary objective is to enhance traffic control strategies and boost public transportation efficiency. To achieve this, the research examines, refines, and tests an array of traffic control strategy models, including cycle optimization, green time optimization, and early green initiation. Building on these data adjustments, the control flow for single-phase active public transit priority and multi-phase operational public transit priority is optimized and assessed. Simulation and optimization of the two control strategies reveal that public transportation prioritization offers a more pronounced advantage on roads during peak hours, making it better suited for cities grappling with congestion during rush hours.