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ESTIMATING TRAVEL TIME MEAN AND VARIANCE FOR ITS DATA SOURCES.
| 题名： | ESTIMATING TRAVEL TIME MEAN AND VARIANCE FOR ITS DATA SOURCES. |
| 作者： | Eisele-William-L; Rilett-Laurence-R |
| 关键词： | Automatic-vehicle-identification; Loop-detectors; Traffic-estimation; Travel-time |
| 摘要： | This paper describes recently completed research investigating corridor travel time mean and variance estimation. Simultaneous travel time data were collected along two corridors from several sources including instrumented test vehicles, commercial vehicles, and an ITS data source. The ITS data source included automatic vehicle identification (AVI) in Houston, Texas and inductance loop detectors in San Antonio, Texas spaced every 0.5 mile (0.8 kilometer). This paper identifies several important findings. First, ITS travel time data sources, such as AVI in Houston, were found to provide a very cost-effective data collection method. They also provide accurate travel time mean estimates while providing more confidence in the travel time estimate. Second, commercial vehicles were found to have longer travel times than those reported by the ITS data sources. This demonstrates that it may be reasonable to provide travel time maps and information in real-time specifically; for commercial vehicles for just-in-time or fleet operations. Third, the difficulty of using spot-speed measurements (i.e., estimates from loop detectors) for corridor travel time estimates is also identified. Finally, the correlation between adjacent links along a corridor was investigated. It was found that the covariance is generally non-zero and positive with the Houston AVI data. This indicates that the link variances cannot simply be summed to calculate corridor variance. |
| 总页数： | ITS America. Meeting (12th : 2002 : Long Beach, Calif.). Securing our future : ITS America 12th Annual Meeting and Exposition 2002 : conference proceedings. 2002. pp16 |
| 报告类型： | 科技报告 |
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