摘要
在固定检测器和浮动车数据的路段行程时间估计基础上,利用两种估计方法数据之间的互补性,应用自适应加权平均融合算法对估计结果进行融合处理,从而实现对路段行程时间更为精确的动态估计。以大连市中心城区为主要研究对象,通过交通调查和VISSIM仿真环境实现对固定检测器和浮动车的数据收集和行程时间估计。结果显示自适应加权平均融合能够有效提高路段行程时间估计精度,且适用于不同流量状态下的路段行程时间估计。
According to the complementary characteristics of loop detectors and probe vehicles both in time and space, the adaptive weighted average fusion model was employed in this paper in order to realize more accurate link travel time estimation. The city center of Dalian was chosen as the research area and traffic conditions were monitored for preparing for the VISSIM simulation environment. Fixed sensor data and probe vehicle data through VISSIM simulation were collected for link travel time estimation. Results show that the adaptive weighted average fusion model could improve the accuracy of link travel time estimation and is appropriate for that under different traffic conditions.
出处
《交通标准化》
2014年第15期38-42,共5页
Communications Standardization
基金
国家自然科学青年基金(51008050)
中央高校基本科研业务费专项资金(DUT12ZD203)
教育部-中国移动科研基金项目(MCM20122071)
教育部留学回国启动基金(第46批)
