An Allocation Method and a Checking System for of Highway Tolls: A Case Study in Hubei Province
-
摘要: 为提升高速公路收费管理水平,推动湖北经济社会发展,提出了湖北高速公路收费清分方法并搭建了清分校核系统.针对湖北高速公路基础设施建设和运营的现状,提出了AD-DFS算法识别车辆争议路径.这一算法采用车牌抓拍的基本原理,在标识站资源有限和约束路径长度的条件下,利用车辆通行数据识别其可能的通行路径作为争议路径,在标识站数据异常的特殊情况下,仍能从争议路径中有效识别车辆清分路径的方法.针对不同类型的清分路径和通行车辆,采用自适应通行费清分方法,能科学合理地将通行费拆分至各相关单位.在前述通行费清分方法基础上,搭建了全国首例针对省级通行分清分提供全面校核功能的平台,即湖北省高速收费清分校核系统,自推广应用以来为湖北省64条高速公路、351个高速收费站、104家经营单位,提供了高效的清分校核功能并收到良好反馈,同时以多层次、多维度数据可视化分析的方式提供了管理与决策支持.Abstract: Tolling highway is one of the major contributions to promoting economic and social development in Hubei province, with the purpose to effectively managing highway tolling systems, a method to allocate tolls is proposed, and a system for checking accuracy of allocation is developed as well.An AD-DFS algorithm is studied to identify dispute paths of vehicles based on the current situation of infrastructure construction and operation of Highways in Hubei province.Under the condition of limited flag stations and restriction of the length of paths, the AD-DFS algorithm captured vehicles'' license plates at first.Then with these positioning data of vehicles, the algorithm identifies possible paths of vehicles as their dispute paths.An algorithm for identifying vehicles'' allocation methods from identified dispute paths is also developed, which is still effective even under a circumstance of abnormal data recorded in flag-stations.For different types of vehicles and allocation methods, an adaptive method is proposed to precisely and fairly allocate the tolls to corresponding management units.Based on the aforementioned methods, a system for checking them is also developed in Hubei province, which is the first province-level platform in China that offers the function of checking the allocation of highway tolls.After being implemented in 64 highways, 351 toll stations and 104 management units in Hubei province, the results indicate that the system has high efficiency, and receives positive feedbacks.It can offer management and decision supports with multi-level and multi-dimensional data visualization analyses.
点击查看大图
计量
- 文章访问数: 303
- HTML全文浏览量: 61
- PDF下载量: 2
- 被引次数: 0