An Extended Variable Speed Limit Strategy for Intelligent Freeway Traffic Optimization

Abstract

Shockwaves induced by the converging of different traffic flows have extensive impacts on freeway traffic, causing capacity drops and congestion. Although other studies have introduced many traffic management schemes in the view of road construction and theoretical analytic method to dominate shockwaves, there are many limitations on those existing methods. In order to explore more efficient and flexible speed control strategies to relieve congestion and queues caused by shockwaves on freeway, the extended variable speed limit strategy is proposed in this paper. Firstly, we explore insights into the traffic evolution based on the macroscopic traffic model METANET and traffic fundamental diagram. By taking full advantages of intelligent vehicles and inter-vehicle systems on control and communication, the optimal speed limit scheme which is continuous in time and space then is investigated using genetic algorithm. Specially, the optimized scheme aims at improving the traffic evolution process not only on increasing discharge rates and alleviating capacity drops of bottlenecks, but also on restoring the free-flow traffic state and decreasing total travel time delay in traffic. Finally, compared with the uncontrolled case and a referenced analytic method, the extended variable speed limit strategy has demonstrated its potential benefits on relieving/solving congestion and queues caused by shockwaves in the freeway traffic.