基于K-短路径的路网关键路段集合的辨识与分析

Identification and analysis of road network key segments set based on K-shortest path

为了提高高速公路网络化运营监管与公众服务的水平,需要准确可靠地辨识出综合多种因素的关键路段,采用交通分配理论及K-短路径算法研究了路网运行关键路段集的辨识问题。综合考虑路网结构、交通需求影响、出行行为特征等多方面因素,以系统内所有用户的旅行时间为交通网络性能度量指标,建立了路网运行关键路段评价模型;考虑多路段失效的联合效应,提出了路段集的重要度评估模型及其求解算法。该模型相对于传统的结构可靠性模型,考虑了出行者路径选择行为影响和多路段失效的联合效应,更符合路网运行管理的实际需求。研究结果表明:在相同交通需求的OD对之间,结构密度较低的区域,被选中为关键路段集的概率大;合理的K取值得到的关键路段集与全路网分配所得结果相近,可有效提升计算效率;多路段失效情况下,路段的联合效应明显。

In order to improve the level of highway network operation monitoring and public service, the key segments should be identified accurately and reliably based on comprehensive factors. This paper studies the key segments set identification problem by using traffic assignment theory and K-shortest path algorithm. The key segments evaluation model is proposed in this paper, which considers many aspects such as network structure, traffic demand influence, travel behavior and takes total travel time as network performance index. The importance degree evaluation model of key segments set and the solving algorithm are introduced with the consideration of the combined effect of multi-segment failure. Compared with traditional structure reliability model, the proposed model is more suitable for real network management because the route choice and the combined effect of multi-segment failure are taken into account. The results show that under the same traffic load, the segments with lower structural density have higher probability to be selected as key segments; The results from reasonable K value assignment and whole network assignment are much close, which means K-shortest path algorithm could improve the computational efficiency; the segments combine effect is much clear under multi-segment failure condition. 6 tabs, 2 figs, 16 refs.