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

机译:基于遗传算法优化的局部消息传播的分散式汽车交通控制系统仿真

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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.
机译:本文描述了一种通过消息传播以分散方式实现的汽车交通控制仿真:拥塞的节点(道路交叉口)将加速或减速的消息发送到相邻节点。对不同类型的旅程进行了建模:常规汽车旅程,事故和紧急汽车旅程。这些旅程具有不同的长度和速度,并且对系统的影响也不同。通过使用遗传算法(GA)确定了在仿真过程中用于控制汽车的最佳参数值。本文还报告了使用从GA导出的参数值实现的不同模拟的初步实验。

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