The randomness of freeway capacity has been analyzed in a large number of studies. In contrast, relatively little attention has been paid to the critical density at capacity and its relationship to breakdown occurrence, although density is used as a quality of service criterion for freeways. In the paper, distributions of freeway capacity and critical density are estimated and compared based on traffic data samples from 38 freeway bottleneck sections in the U.S. and Germany. It is shown that the well-established methods for stochastic capacity analysis can be applied to estimate critical density distributions by replacing volume with density in the corresponding mathematical models. Comparison of the estimated capacity and critical density distribution functions reveals that the relative variability of the capacity is lower than the variability of the critical density. This suggests that traffic volume is the more appropriate parameter to represent the trigger of traffic breakdowns than traffic density. The empirical results also show that the rather smooth traffic flow on U.S. freeways leads to a smaller variance of both the capacity and the critical density distribution compared with German freeways, whereas the average capacity per lane is roughly the same.
Comparison of Stochastic Estimates of Capacity and Critical Density for U.S. and German Freeways
Transportation Research Record: Journal of the Transportation Research Board
Transportation Research Record: Journal of the Transportation Research Board ; 2673 , 8 ; 388-396
2019-04-04
Article (Journal)
Electronic Resource
English
Optimum Capacity of Freeways: A Stochastic Approach
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