Automated vehicle identification tag-matching algorithms for estimating vehicle travel times - Comparative assessment

被引:5
作者
Hellinga, B [1 ]
机构
[1] Univ Waterloo, Dept Civil Engn, Waterloo, ON N2L 361, Canada
来源
ARTIFICIAL INTELLIGENCE AND INTELLIGENT TRANSPORTATION SYSTEMS: PLANNING AND ADMINISTRATION | 2001年 / 1774期
关键词
D O I
10.3141/1774-13
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The computational complexity associated with three candidate automated vehicle identification (AVI) tag-matching algorithms that could be used to obtain individual vehicle travel time data in real time is examined. These algorithms are suitable for application to a linear roadway facility using transponder tags that do not have programmable memory. Analytical expressions are derived to estimate the worst-case and average computational load associated with each algorithm. A simulation is conducted to test the validity of the assumptions made in these derivations and to perform a sensitivity analysis on several key system parameters, including the rate of flow of AVI-equipped vehicles, the mean travel time between tag reader stations, the coefficient of variation of travel time, and the proportion of vehicles that pass the upstream tag readers.
引用
收藏
页码:106 / 114
页数:9
相关论文
共 4 条
[1]  
Baase Sara, 1988, Computer Algorithms: Introduction to Design and Analysis, V2
[2]  
BURRIS M, 1999, 6 ITS C TOR ONT CAN
[3]  
MOUSKOS K, 1999, 6 ITS C TOR ONT CAN
[4]  
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