Traffic optimization in transport networks based on local routing

Abstract

Congestion in transport networks is a topic of theoretical interest and practical importance. In this paper we study the flow of vehicles in urban street networks. In particular, we use a cellular automata model to simulate the motion of vehicles along streets, coupled with a congestion-aware routing at street crossings. Such routing makes use of the knowledge of agents about traffic in nearby roads and allows the vehicles to dynamically update the routes towards their destinations. By implementing the model in real urban street patterns of various cities, we show that it is possible to achieve a global traffic optimization based on local agent decisions.

4 pages, 5 figures

References in corpus (1)

• Dynamics of jamming transitions in complex networks

Cited by in corpus (11)

• Mobility and Congestion in Dynamical Multilayer Networks with Finite Storage Capacity
• Traffic flow on realistic road networks with adaptive traffic lights
• A model to identify urban traffic congestion hotspots in complex networks
• Local Empathy provides Global Minimization of Congestion in Communication Networks
• Decongestion of urban areas with hotspot-pricing
• Traffic flow in a Manhattan-like urban system
• A minimal model for congestion phenomena on complex networks
• Smart random walkers: the cost of knowing the path
• Theoretical approach and impact of correlations on the critical packet generation rate in traffic dynamics on complex networks
• A link model approach to identify congestion hotspots
• Obscuring digital route choice information prevents delay-induced congestion