论文部分内容阅读
人对所处客观世界的认识具有显著的空间层次特征,可指导出行路径规划过程。常用的层次空间推理的分层路径计算方法,虽顾及了路网的层次性特征,但道路规划等级与人对路网的层次性认知往往并不一致。而道路网络自身的拓扑结构可客观反映道路重要程度,以及出行者对道路的层次性认知经验。本文以拓扑结构指标表达道路的层次性特征,以此规划驾车出行路径,并通过与出租车行驶路径的匹配度及距离最短路径耗时比评价路径规划结果的合理性。研究结果表明,基于路网拓扑层次性表达的规划路径优于距离最短路径、动态时间最短路径、基于道路等级的静态时间最短路径及基于动态中介中心性分层的距离最短路径,与基于出租车经验建模的路径规划结果相当。但本文所提出的方法不需出租车经验建模所依赖的浮动车系统支持,更利于部署应用。
People's understanding of the objective world they live in has significant spatial-level features that guide the travel path planning process. The commonly used hierarchical path computation method of spatial reasoning, although taking into account the hierarchical nature of the road network, but the level of road planning and people on the road network level of understanding is often not the same. The topological structure of the road network can objectively reflect the importance of the road and the traveler's level of cognitive experience on the road. In this paper, we use the topological structure indicators to express the hierarchical features of roads to plan driving travel paths, and evaluate the rationality of the path planning results by the matching degree with the taxi driving path and the time-consuming ratio of the shortest distance route. The research results show that the planning path based on hierarchical representation of road network topology is superior to the shortest distance path, the shortest dynamic path, the shortest static path based on road grade and the shortest distance based on dynamic intermediary centralization, Path planning experience modeling results quite. However, the method proposed in this paper does not need the support of the floating car system on which taxi empirical modeling relies, which is more beneficial to deployment applications.