A self-organizing system for urban traffic control based on predictive interval microscopic model

Abstract

This paper introduces a self-organizing traffic signal system for an urban road network. The key elements of this system are agents that control traffic signals at intersections. Each agent uses an interval microscopic traffic model to predict effects of its possible control actions in a short time horizon. The executed control action is selected on the basis of predicted delay intervals. Since the prediction results are represented by intervals, the agents can recognize and suspend those control actions, whose positive effect on the performance of traffic control is uncertain. Evaluation of the proposed traffic control system was performed in a simulation environment. The simulation experiments have shown that the proposed approach results in an improved performance, particularly for non-uniform traffic streams.

29 pages, 8 figures

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• Self-Organizing Traffic Lights
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Cited by in corpus (3)

• Self-Organization in Traffic Lights: Evolution of Signal Control with Advances in Sensors and Communications
• Detection of malicious data in vehicular ad-hoc networks for traffic signal control applications
• Self-organising Urban Traffic control on micro-level using Reinforcement Learning and Agent-based Modelling