Research on public traffic control of multi-agents system based on grey disaster predication

Chen Tao, Chen Senfa, Zhu Jinfeng
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Abstract

In the multi-agents public traffic control system, the problem about being comfortable is very important. The challenge is to find solutions to achieve the objective minimized amount of vehicles in overload. This paper proposes a solution algorithm for keeping comfortable of public traffic based on grey disaster prediction through principled cooperation between agents that represent traffic command center, traffic operators, and drivers. It is deduced that the algorithm is practical and adaptable to a variety of public traffic networks.
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基于灰色灾害预测的多智能体系统公共交通控制研究
在多智能体公共交通控制系统中,舒适性问题非常重要。我们面临的挑战是找到解决方案,以实现最小化车辆超载的目标。本文提出了一种基于灰色灾害预测的公共交通舒适解决算法,该算法通过代表交通指挥中心、交通运营商和驾驶员的agent之间的原则合作来实现。结果表明,该算法具有实用性,适用于多种公共交通网络。
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