A Decentralised Car Traffic Control System Simulation Using Local Message Propagation Optimised with a Genetic Algorithm

This paper describes a car traffic control simulation realised in a decentralised way by message propagations: congested nodes (roads intersections) send speed-up or slow-down messages to neighbouring nodes. Different types of journeys have been modelled: regular car journeys, accidents and emergency cars journeys. These journeys have different lengths and speeds, and affect the system differently. Optimal values of parameters, used during the simulations for controlling the cars, have been determined through the use of a genetic algorithm (GA). This paper reports as well a preliminary experiment on different simulations realised with parameters values derived from the GA.

• Type: Conference
• Year: 2006
• Where: ESOA
• Authors: Martin Kelly, Giovanna Di Marzo Serugendo
• Keywords: Car Traffic Control, Emergency Cars Journeys, ESOA 2006, Neural Networks, Regular Car Journeys