DeepAI AI Chat
Log In Sign Up

Self-organising Urban Traffic control on micro-level using Reinforcement Learning and Agent-based Modelling

by   Stefan Bosse, et al.

Most traffic flow control algorithms address switching cycle adaptation of traffic signals and lights. This work addresses traffic flow optimisation by self-organising micro-level control combining Reinforcement Learning and rule-based agents for action selection performing long-range navigation in urban environments. I.e., vehicles represented by agents adapt their decision making for re-routing based on local environmental sensors. Agent-based modelling and simulation is used to study emergence effects on urban city traffic flows. An unified agent programming model enables simulation and distributed data processing with possible incorporation of crowd sensing tasks used as an additional sensor data base. Results from an agent-based simulation of an artificial urban area show that the deployment of micro-level vehicle navigation control just by learned individual decision making and re-routing based on local environmental sensors can increase the efficiency of mobility in terms of path length and travelling time.


page 8

page 18


Learning to Communicate with Reinforcement Learning for an Adaptive Traffic Control System

Recent work in multi-agent reinforcement learning has investigated inter...

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

This paper introduces a self-organizing traffic signal system for an urb...

How Routing Strategies Impact Urban Emissions

Navigation apps use routing algorithms to suggest the best path to reach...

Tangramob: an agent-based simulation framework for validating urban smart mobility solutions

Estimating the effects of introducing a range of smart mobility solution...

A multiagent urban traffic simulation

We built a multiagent simulation of urban traffic to model both ordinary...

VLUC: An Empirical Benchmark for Video-Like Urban Computing on Citywide Crowd and Traffic Prediction

Nowadays, massive urban human mobility data are being generated from mob...