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Intelligent parking management system by multi-agent approach: The case of urban area of Tunis

机译:基于多智能体的智能停车管理系统:以突尼斯市区为例

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By coordination and cooperation between multi-agents, this paper proposes the network of intelligent agents which can reduce the search time needed to finding a parking place. Based on multi-agents model, the fined solution is designed to help drivers in finding a parking space at anytime and anywhere. Three services are offered: the search for a vacant place, directions to a parking space and booking a place for parking. The results of this study generated by the platform MATSim transport simulation, show that our approach optimizes the operation of vehicles in a parking need with the aim of reducing congestion, and improve traffic flow in urban area. A comparison between the first method where the vehicles are random and the second method where vehicles are steered to vacant parking spaces shows that the minimization of time looking for a parking space could improve circulation by reducing the number of cars in the morning of 2% and 0.7% of the evening. In addition, the traffic per hour per day was reduced by approximately 4.17%.
机译:通过多智能体之间的协调与协作,提出了一种智能智能体网络,可以减少寻找停车位所需的搜索时间。罚款解决方案基于多主体模型,旨在帮助驾驶员随时随地寻找停车位。提供三种服务:搜索空位,前往停车位的方向以及预订停车位。由MATSim平台运输模拟产生的这项研究结果表明,我们的方法优化了有停车需求的车辆的运行,目的是减少交通拥堵,并改善市区的交通流量。对第一种方法(车辆是随机的)和第二种方法(车辆被引导到空置的停车位)之间的比较表明,将寻找停车位的时间最小化可以通过将早晨的汽车数量减少2%来改善交通状况。晚上的0.7%。此外,每天每小时的流量减少了约4.17%。

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