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。
Urban traffic congestion has seriously affected the daily lives of residents how to quickly and efficiently find and reduce traffic congestion has become the major goal of urban traffic development.Floating car data as a new source of traffic state detection,is widely used into traffic condition detection.The traffic condition detection of a road or area in different time is based on the fuzzy comprehensive evaluation algorithm of the maximum queue length estimated by the floating car data,vehicle＇ s speed and delay time.Finally,an actual floating car data as an example was used.The results show that the algorithm based on GPS data has better detection and practicability for the traffic state.
出处
《科学技术与工程》
北大核心
2017年第7期270-274,共5页
Science Technology and Engineering
基金
交通运输部2014年度科技项目(14CNIC03-8119)资助
关键词
浮动车数据
路段最大排队长度
模糊综合评价
交通状态评价
floating car data
maximum queue length estimation
fuzzy comprehensive evaluation
congestion evaluation
