期刊
JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS
卷 14, 期 4, 页码 232-250出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/15472450.2010.517477
关键词
Advanced Traveler Information; Intelligent Transportation Systems; Transportation Modeling; Time Travel Reliability
资金
- Mid-Atlantic University Transportation Center
The estimation of path or trip travel-time reliability is critical to any advanced traveler information system. The state-of-practice procedures for estimating path travel-time reliability assume that travel times follow a normal distribution and that segment travel times are independent (i.e., trip variance is a summation of segment variances). The present study analyzes Automatic Vehicle Identification (AVI) data from San Antonio, Texas, and simulated data to demonstrate through goodness-of-fit tests that a log-normal travel-time distribution is valid only under steady-state conditions, whereas a normal distribution is not valid. In the present article, the authors propose five methods for the estimation of path travel-time variance from its component segment travel-time variances. The analysis demonstrates that computing the trip travel-time coefficient of variation as the conditional expectation over all realizations of roadway segments provides estimates within 70% of trip travel-time variance for both uncongested and congested conditions.
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