Agent-based Traffic Management and Reinforcement Learning in Congested Intersection Network

Agent-Based Traffic Management and Reinforcement Learning in Congested Intersections

Reinforcement learning-based multi-agent system for network traffic signal control

A challenging application of artificial intelligence systems involves the scheduling of traffic signals in multi-intersection vehicular networks. This paper introduces a novel use of a multi-agent system and reinforcement learning (RL) framework to obtain an efficient traffic signal control policy. The latter is aimed at minimising the average delay, congestion and likelihood of intersection cr...

Optimal Signal Control in Urban Road Networks with High Priority Congested Centers

Keeping the density of traffic flow and air pollution in an acceptable level and developing a good capacity for transit in the high priority areas of the city, is really a big deal in large and crowded cities. To address this problem, a new method of intersection signal optimization is presented in this paper. Based on network fundamental diagrams, an Internal–External Traffic Metering Strategy...

A Novel Self-Learning Intelligent Traffic Signal Control System for Congested Urban Areas

Population is steadily increasing worldwide resulting in intractable traffic congestion in urban dense areas. Adaptive Traffic Signal Control (ATSC) has shown strong potential to effectively alleviate urban traffic congestion by adjusting the signal timing plans in real-time in response to traffic fluctuations to achieve desirable objectives (e.g., minimize delay).The problem of coordinated ATS...

Improved Multi-Agent Reinforcement Learning for Minimizing Traffic Waiting Time

This paper depict using multi-agent reinforcement learning (MARL) algorithm for learning traffic pattern to minimize the traveling time or maximizing safety and optimizing traffic pattern (OTP). This model provides a description and solution to optimize traffic pattern that use multi-agent based reinforcement learning algorithms. MARL uses multi agent structure where vehicles and traffic signal...