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Model to Forecast Peak Spreading.
| 题名： | Model to Forecast Peak Spreading. |
| 作者： | J. S. Miller; |
| 关键词： | traffic models, transportation management, traffic management, travel demand, trends, traffic volumes |
| 摘要： | As traffic congestion increases, the K-factor, defined as the proportion of the 24-hour traffic volume that occurs during the peak hour, may decrease. This behavioral response is known as peak spreading: as congestion grows during the peak travel times, motorists may shift their departure time to a non-peak hour. Knowing whether K-factors will remain constant or will change will affect the estimation of travel demand, and the resultant transportation performance, since the traffic volume during a given hour may affect travel speed and vehicle emissions. The purpose of this study was to develop a model for forecasting peak spreading whereby peak spreading is measured as change in the K-factor. Data were collected from 32 continuous count stations in the six Northern Virginia counties of Arlington, Fairfax, Fauquier, Loudoun, Prince William, and Stafford for the period 1997-2010. Because some stations gave twodirectional counts and some gave only one-directional counts, there were 52 station-direction combinations, or sites, for analysis purposes. The data collected showed that the average annual K-factor adjusted for months for which data were not available decreased by an average of 0.006 (p < 0.01), from 0.103 to 0.097, during the period. The 24-hour volume-to-capacity ratio, which is a surrogate for travel congestion, increased by an average of 0.7 (p < 0.01), from 7.3 to 8.0. Both changes were statistically significant. |
| 总页数： | 56p |
| 报告类型： | 科技报告 |
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