Self-Organizing Traffic Lights

Abstract

Steering traffic in cities is a very complex task, since improving efficiency involves the coordination of many actors. Traditional approaches attempt to optimize traffic lights for a particular density and configuration of traffic. The disadvantage of this lies in the fact that traffic densities and configurations change constantly. Traffic seems to be an adaptation problem rather than an optimization problem. We propose a simple and feasible alternative, in which traffic lights self-organize to improve traffic flow. We use a multi-agent simulation to study three self-organizing methods, which are able to outperform traditional rigid and adaptive methods. Using simple rules and no direct communication, traffic lights are able to self-organize and adapt to changing traffic conditions, reducing waiting times, number of stopped cars, and increasing average speeds.

Added new self-organizing method, compared with other methods, improved references

References in corpus (8)

• Self Organization and a Dynamical Transition in Traffic Flow Models
• Optimizing Traffic Lights in a Cellular Automaton Model for City Traffic
• Self-organization of traffic jams in cities: effects of stochastic dynamics and signal periods
• Coherent Moving States in Highway Traffic (Originally: Moving Like a Solid Block)
• Characteristics of Vehicular Traffic Flow at a Roundabout
• Optimised Traffic Flow at a Single Intersection: Traffic Responsive signalisation
• When Can we Call a System Self-organizing?
• Autonomous Traffic Signal Control Model with Neural Network Analogy

Cited by in corpus (16)

• Self-Control of Traffic Lights and Vehicle Flows in Urban Road Networks
• A comparative study of Macroscopic Fundamental Diagrams of arterial road networks governed by adaptive traffic signal systems
• A Market-Inspired Approach for Intersection Management in Urban Road Traffic Networks
• Decentralised control of material or traffic flows in networks using phase-synchronisation
• When slower is faster
• Measuring the Complexity of Self-organizing Traffic Lights
• A self-organizing system for urban traffic control based on predictive interval microscopic model
• Integrating independent and centralized multi-agent reinforcement learning for traffic signal network optimization
• Signal optimization in urban transport: A totally asymmetric simple exclusion process with traffic lights
• Self-organizing urban transportation systems
• Traffic disruption and recovery in road networks
• Self-Organization in Traffic Lights: Evolution of Signal Control with Advances in Sensors and Communications
• An Open-Source Framework for Adaptive Traffic Signal Control
• Crowding effects in vehicular traffic
• Towards Self-organizing Bureaucracies
• Requisite Variety, Autopoiesis, and Self-organization