Characterization of vehicle time headway in clear and rainy weather

Date

2018-12-14

Authors

Tangestanipour, Atousa

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Abstract

Adverse weather has a direct effect on traffic congestion, capacity, and road safety. Rain can influence traffic flow and headway. Thus, it is important to study the impact of weather conditions on traffic. In this thesis, headway data from a north-south highway in Tehran is categorized according to weather conditions and traffic flow. A statistical analysis of this data is presented which show that the mean time headway increases in rainy weather and the traffic flow rate is lower. The probability density functions fit to the headway data and these distributions are then evaluated using the Chi-Squared (C-S) and Kolmogorov- Smirnov (K-S) tests to determine which is the most suitable. To generalize results for different traffic flow rates, another highway was selected for data collection. The results obtained show that the Burr distribution is the best to model the headway data in clear and rainy weather with a higher traffic flow. Moreover, the generalized extreme value distribution is the best to model the headway data in clear and rainy weather with a lower traffic flow. This justifies the use of different time headway distributions in rainy and clear weather conditions and different traffic flow rates for traffic modeling.

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Keywords

Vehicle Headway Time, Burr distribution, Generalized extreme value distribution, Statistical model

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