动态车辆路径问题是物流学中的一个重要研究领域。
Dynamic vehicle routing problem is an important area in logistics.
对于诱导控制，则分别运用静态和动态最短路算法解决了救援车辆和其它单车诱导路径的确定问题。
For induce control, it respectively USES static and dynamic shortest path algorithms to solve the relief vehicles 'and the other vehicle 'route problem.
论文主体部分主要对时间依赖网络车辆路径问题进行了分析研究，分为确定需求和动态需求两部分。
The main body of this paper researches TDVRP, which is made up with two parts—deterministic demands and dynamic demands. The first part analyzes the TDVRP with deterministic demand.
针对已有路径选择模型缺乏选择决策过程的问题，给出基于决策场理论的车辆路径选择过程框架，建立面向过程的车辆动态路径选择模型。
In this paper, the decision field theory (DFT) is used as the theoretical basis to develop a framework and to model the process-oriented vehicle dynamic route choice.
交通网络模型、路径规划算法以及交通流预测是车辆导航动态路径规划需要解决的重点问题。
The key problems of vehicle navigation dynamic path planning are traffic network model, path planning algorithm and traffic flow prediction.
交通网络模型、路径规划算法以及交通流预测是车辆导航动态路径规划需要解决的重点问题。
The key problems of vehicle navigation dynamic path planning are traffic network model, path planning algorithm and traffic flow prediction.
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