基于浮动车数据的区域路网交通状态评价
发布时间：2019-06-06 20:39
【摘要】：城市道路拥堵现象已经对公众的生活产生严重影响,如何快速有效地发现并及时处理交通拥堵现象已成为交通发展中的重中之重。浮动车数据作为交通状态检测的新来源,在交通状态检测领域有着广阔的应用前景。通过浮动车数据估算路段最大排队长度,并将其与路段车辆行驶速度、路段行程延误时间作为区域内交通状态评价参数,基于模糊综合评价算法,给出了一种在不同时间段内路段及区域交通状态评价方法。最后通过实际浮动车数据进行实例验证。实验结果表明该算法对于能够较好地检测区域路网交通状态,具有较好的实用性。
[Abstract]:The phenomenon of urban road congestion has had a serious impact on the life of the public, how to quickly and effectively detect and deal with the phenomenon of traffic congestion in time has become the most important thing in the development of traffic. As a new source of traffic condition detection, floating car data has a broad application prospect in the field of traffic condition detection. The maximum queue length of the road section is estimated by floating car data, and the travel speed and delay time of the road section are taken as the evaluation parameters of the traffic state in the area, based on the fuzzy comprehensive evaluation algorithm. An evaluation method of road section and regional traffic condition in different time periods is presented. Finally, an example is given to verify the actual floating car data. The experimental results show that the algorithm can detect the traffic state of the regional road network and has good practicability.
【作者单位】： 中国航天系统工程有限公司;
【基金】：交通运输部2014年度科技项目(14CNIC03-8119)资助
【分类号】：U491
[Abstract]:The phenomenon of urban road congestion has had a serious impact on the life of the public, how to quickly and effectively detect and deal with the phenomenon of traffic congestion in time has become the most important thing in the development of traffic. As a new source of traffic condition detection, floating car data has a broad application prospect in the field of traffic condition detection. The maximum queue length of the road section is estimated by floating car data, and the travel speed and delay time of the road section are taken as the evaluation parameters of the traffic state in the area, based on the fuzzy comprehensive evaluation algorithm. An evaluation method of road section and regional traffic condition in different time periods is presented. Finally, an example is given to verify the actual floating car data. The experimental results show that the algorithm can detect the traffic state of the regional road network and has good practicability.
【作者单位】： 中国航天系统工程有限公司;
【基金】：交通运输部2014年度科技项目(14CNIC03-8119)资助
【分类号】：U491
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