Vehicle path planning plays a key role in the car navigation system. In actual urban traffic, the time spent at intersections accounts for a large proportion of the total time and cannot be ignored. Therefore, studying the shortest path planning problem considering node attributes has important practical significance. In this article, we study the vehicle path planning problem in time-invariant networks, with the minimum travel time from the starting node to the destination node as the optimization goal (including node time cost). Based on the characteristics of the problem, we construct the mathematical model. We propose a Reverse Order Labeling Algorithm (ROLA) based on the traditional Dijkstra algorithm to solve the problem; the correctness of the proposed algorithm is proved theoretically, and we analyse and give the time complexity of the ROLA and design a calculation example to verify the effectiveness of the algorithm. Finally, through extensive simulation experiments, we compare the performance of the proposed ROLA with several other existing algorithms. The experimental results show that the proposed algorithm has good stability and high efficiency.

中文翻译：

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时不变网络下考虑节点属性的汽车导航路径优化算法

车辆路径规划在汽车导航系统中起着关键作用。在实际的城市交通中，在十字路口花费的时间占总时间的很大一部分，因此不能忽略。因此，研究考虑节点属性的最短路径规划问题具有重要的现实意义。在本文中，我们研究时不变网络中的车辆路径规划问题，以从起始节点到目标节点的最小行驶时间作为优化目标（包括节点时间成本）。根据问题的特征，我们构建数学模型。我们提出了一种基于传统Dijkstra算法的逆序标注算法（ROLA）来解决该问题；理论上证明了该算法的正确性，并分析并给出了ROLA的时间复杂度，并设计了计算实例来验证算法的有效性。最后，通过广泛的仿真实验，我们将建议的ROLA与其他几种现有算法的性能进行了比较。实验结果表明，该算法具有良好的稳定性和高效率。