Intelligent Traffic Light Management using Multi-Behavioral Agents

Abstract

Abstract-One of the biggest challenges in modern societies is to solve vehicular traffic problems. In this scenario, our proposal is to use a Multi-Agent Systems (MAS) composed of three types of agent: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. This third type of agent is able to change its behaviour between what we have called a selfish mode (the agent will try to influence the other neighbour agents of its type to achieve its goal) or an altruistic mode (the agent will take into consideration the other neighbour selfish agents indications). To validate our solution, we have developed a MAS emulator which communicates with the Simulation of Urban MObility (SUMO) traffic simulator using the Traci tool to realize the experiments in a realistic environment. The obtained results show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration.

Recent development of smart traffic lights

“…The proposed system is also able to recognize the traffic light cycle. In [15] proposes a system consisting of three agents, namely, traffic light management agents (TLAgents), traffic jam detection agents (TJamAgents) and agents that control traffic lights at intersections (IntersectionAgents). A TLAgent is placed at each traffic light to regulate the changes in the light signals.…”

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management

“…This paper is an extended version of the work presented in JITEL 2017 [ 1 ], where we proposed the use of a Multi-Agent System (MAS) composed of multi-behavioral agents to optimize the management of traffic lights. This work led us to focus our research on obtaining an optimal set of sensor locations in the network used to provide data to the MAS.…”