Deterministic and Stochastic Freeway Capacity Analysis Based on Weather Conditions
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 145, Issue 5
Abstract
In this paper, a fundamental diagram is calibrated for observed traffic data on a freeway segment using triangular regression analysis and the fixed capacity of the freeway is derived. Stochastic capacity analysis is then conducted to investigate the nature of the breakdown phenomenon and its effect on freeway capacity. The Weibull distribution function as a generalized extreme value distribution model is fit to the data. For both deterministic and stochastic capacity analysis, the influence of the weather is evaluated for four types of weather conditions that include clear, rainy, snowy, and low visibility. The statistical analysis results show that weather conditions have a significant effect on both the fixed and stochastic value of freeway capacity. One of the other important findings of this study is that jam density is shown to be significantly affected by weather conditions and needs to be incorporated when developing advanced freeway control and management strategies such as queue detection and management schemes.
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Acknowledgments
This study was financially supported by the Urban Alliance Professorship Fund with the City of Calgary and by an Alberta Motor Association—Alberta Ingenuity Technology Future (AMA-AITF) Collaborative Grant in Smart Multimodal Transportation Systems.
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Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 145 • Issue 5 • May 2019
Copyright
©2019 American Society of Civil Engineers.
History
Received: Jan 2, 2018
Accepted: Oct 9, 2018
Published online: Mar 8, 2019
Published in print: May 1, 2019
Discussion open until: Aug 8, 2019
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