基于收费数据的高速公路交通状态判别方法

发布时间：2018-06-30 10:06

本文选题：高速公路 + 模糊C-均值　；参考：《华南理工大学学报(自然科学版)》2014年12期

【摘要】：目前高速公路交通数据资源未得到充分利用,使得管理和建设成本较高的高速公路联网收费系统只能实现车辆记录、联网收费等初级功能,导致交通数据资源的严重浪费.为此设计了基于高速公路联网收费数据的路段行程时间估计方法,提出以大、小车速度变化情况为基础,采用模糊C-均值聚类方法对高速公路交通状态进行判别,并应用VISSIM软件分别对上述两种方法验证分析.结果表明,路段行程时间估计方法能够获得高质量的路段行程时间数据,同时交通状态判别方法也能够准确判别出道路上所呈现的交通状态,可为历史数据更新提供技术支持,为高速公路交通管理部门提供精确的决策依据.
[Abstract]:At present, the highway traffic data resources have not been fully utilized, making the expressway network toll system with high cost of management and construction can only realize the primary function of vehicle record, network charge and so on, which leads to the serious waste of traffic data resources. Therefore, a road travel time estimator based on the toll data of high-speed public road network is designed. On the basis of the change of the speed of large and small cars, the fuzzy C- means clustering method is used to distinguish the traffic state of the expressway, and the above two methods are verified and analyzed with the VISSIM software. The results show that the link travel time estimation method can obtain the high quality section travel time data, and the traffic state is judged at the same time. The other methods can also accurately identify the traffic status on the road, providing technical support for the updating of historical data and providing accurate decision-making basis for the highway traffic management department.
【作者单位】：吉林大学汽车仿真与控制国家重点实验室;吉林大学交通学院;
【基金】：国家科技支撑计划项目(2014BAG03B03) 山东省省管企业科技创新项目(20122150251-5)
【分类号】：U491

【参考文献】