摘要
针对高密度路网诱导路径选择问题,基于图论对路网进行结构化选取,构建高密度路网模型。从节点评估的角度出发,提出综合考虑结构属性和交通运行状态属性的节点承载力指标。采用均质性、连通性2个指标评价路网节点结构属性,采用流量裕度、通行效率2个指标评价路网节点交通运行状态属性,提出一种基于TOPSIS算法(Technique for Order Preference by Similarity to Ideal Solution,优劣解距离法)的综合评价方法,实现对节点承载力的综合量化。基于节点承载力,构造路段承载力指标,采用重力模型和交通分配的方法将节点间的承载力分配到节点相连构成的路段上,并用路段实际交通条件修正即得到路段承载力。基于节点承载力和路段承载力,提出高密度路网诱导路径的确定方法。为证明本研究提出的高密度路网诱导路径选择方法的有效性,构建一高密度路网结构模型,同时采用本算法和传统Dijkstra算法规划诱导路径。结果表明:Dijkstra算法规划的路径虽为数学意义上的最优路径,但该路径途经低级节点,且需频繁切换道路进行交通转换,不符合驾驶员行车期望;本研究提出的基于节点承载力的高密度路网诱导路径选择方法得出的路径虽比Dijkstra算法稍长,但路径均由高等级节点和道路组成,这样的规划结果更符合实际交通诱导系统需求,更能体现驾驶人员选路偏好。
In order to solve the guidance route selection problem of high-density road network,the road network is structural selected based on graph theory,and a high-density road network model is established.From the perspective of node evaluation,the node bearing capacity indicator that comprehensively considers the structural attributes and the traffic operating state attributes is proposed.The structural attributes of road network is evaluated by adopting homogeneity and connectivity,the traffic operating state attributes of road network is evaluated by adopting traffic volume margin and traffic efficiency.A comprehensive evaluation method based on Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)is proposed to quantify the node capacity.Based on the node bearing capacity,the section capacity indicator is constructed,the capacity between the nodes is distributed to the road sections connected by the nodes by the gravity model and the traffic distribution method,which is modified by the actual traffic condition of the road section to obtain the capacity.A method for determining the guidance route of the high-density road network is proposed based on the node capacity and the road capacity.In order to verify the effectiveness of the proposed guidance route selection method,a high-density road network model is constructed,and the guidance route is planned by both the proposed method and the traditional Dijkstra algorithm.The result shows that the(1)Although the route planned by Dijkstra algorithm is the optimal one in the mathematical sense,it passes through low-level nodes and needs frequently road,failing to meet the driver’s driving expectations.(2)Although the routes obtained by the proposed high-density road network guidance route selection method based on node capacity is slightly longer than the Dijkstra algorithm,the routes are all composed of high-level nodes and roads.Such planning result is more in line with the actual traffic guidance system requirements,it can better reflect the driver’s routing preference.
作者
周昆
荆迪菲
荆林立
宋佳康
陈跃文
ZHOU Kun;JING Di-fei;JING Lin-li;SONG Jia-kang;CHEN Yue-wen(Shandong Hi-speed Construction Management Group Co.,Ltd.,Jinan Shandong 250014,China;Key Laboratory of Road and Traffic Engineering of Ministry of Education,Tongji University,Shanghai 201804,China;Dali-Yongsheng Expressway Construction Headquarters,Zhaotong Yunnan 657305,China)
出处
《公路交通科技》
CAS
CSCD
北大核心
2021年第7期124-130,共7页
Journal of Highway and Transportation Research and Development
基金
山东省交通运输厅科技项目(2019B32)。