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Anticipatory Vehicle Routing in Stochastic Networks Using Multi-Agent System

机译:使用多智能体系统的随机网络中的预期车辆路径

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In this paper, we consider an anticipatory vehicle routing problem. We investigate the architecture of a multiagent routing system wherein each vehicle is represented by an agent that interacts with the road infrastructure. We use a route reservation approach, whereby each vehicle reserves a space-time slot on the road segments included in the route. It makes it possible to predict the load of the segments and estimate the travel time with higher accuracy. To estimate the travel time, it is proposed to take into account the stochastic properties of the network. In this paper, we consider not only the average travel time but also its variance. The proposed approach is compared with alternative routing strategies: uncontrolled routing and anticipatory routing in a deterministic transport network. We evaluate the proposed model using the microscopic simulation of a real-world traffic environment with SUMO modeling software.
机译:在本文中,我们考虑了预期的车辆路径问题。我们研究了多主体路由系统的体系结构,其中每辆车都由与道路基础设施交互的主体表示。我们使用路线保留方法,即每辆车在路线中包含的路段上保留一个时空时隙。这样可以预测路段的负载并以更高的精度估算行驶时间。为了估计行程时间,建议考虑网络的随机特性。在本文中,我们不仅考虑平均旅行时间,还考虑其方差。将所提出的方法与替代路由策略进行比较:确定性传输网络中的不受控制的路由和预期的路由。我们使用带有SUMO建模软件的真实交通环境的微观仿真来评估提出的模型。

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