Information Dynamics in Transportation Systems with Traffic Lights Control

Abstract

Due to recent advanced communication possibilities between traffic infrastructure, vehicles and drivers, the optimization of traffic lights control can be approached in novel ways. At the same time, this may introduce new unexpected dynamics in transportation systems. Our research aims to determine how drivers and traffic lights systems interact and influence each other when they are informed one about another's behaviour. In order to study this, we developed an agent based model to simulate transportation systems with static and dynamic traffic lights and drivers using information about the traffic lights behaviour. Experiments reveal that the system's performance improves when a bigger share of drivers receive information for both static and dynamic traffic lights systems. This performance improvement is due to drivers managing to avoid stopping at red light rather them adapting their speed to different distances to the traffic lights systems. Additionally, it is demonstrated that the duration of the fixed phases also influences the performance when drivers use speed recommendations. Moreover, the results show that dynamic traffic lights can produce positive effects for roads with high speed limits and high traffic intensity, while in the rest of the cases static control is better. Our findings can be used for building more efficient traffic lights systems.