计算机科学
浮动车数据
交通拥挤
模糊逻辑
流量(计算机网络)
智能交通系统
数据挖掘
运输工程
实时计算
人工智能
工程类
计算机网络
作者
Hongfei Jia,Yunlong Tan,Xiaoyan Fu
标识
DOI:10.1109/icoip.2010.126
摘要
Based on the massive floating car data and traffic flow detector data of intelligent movement platform, the average travel speed, the average delay per unit distance and the saturation of road sections are selected to build traffic congestion evaluation system. The accuracy of floating car data is validated with field observations of the typical roads in Guangzhou, the validation result shows that the accuracy of floating car data is more than 86%, which shows that the floating car data may reflect the road traffic information well. The evaluation criteria of three indexes are determined by the regression analysis of floating car data. Because the weight decided by traditional fuzzy evaluation method is random, in order to make the conclusion more objective, the principal components analysis method is applied to define the weigh which is based on the monitoring sample information, and the expert scoring method is supplemented to do some amendments. The multi-ingredient assessment is transformed into the single-object decision by the improved fuzzy comprehensive evaluation model, and the traffic congestion index concept is proposed. Finally, the traffic congestion evaluation system is conducted on the traffic improvement planning in Tianhe district.
科研通智能强力驱动
Strongly Powered by AbleSci AI