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Analysis of vehicle-type-specific headways on two-lane roads with mixed traffic

    Rupali Roy Affiliation
    ; Pritam Saha Affiliation

Abstract

Time headway is an important microscopic traffic flow parameter, which affects safety, level-of-service, capacity and traffic simulation. It is, therefore, important to know the specific distribution for a particular roadway and traffic condition. Further, headway between two vehicles depends on the type of lead vehicle and is influenced by its size and dynamics. Such impact is considerably high on two-lane roads with mixed traffic composed of a wide variety of vehicle types. This paper identified sixteen combinations of vehicle pairs and analysed vehicle-type-specific headways using field data. Appropriate distribution functions were fitted to field data and predictive models were used in understanding carfollowing behaviour. Observations indicate that quite often bike riders become reluctant in obeying lane discipline. However, car drivers show conservative attitude and usually, keep safe distance from the lead vehicle except the case when they follow another car. In addition, while following Non-Motorized Vehicles (NMV), most of the drivers keep reasonably safe distances. In this paper, a comparison of computed headway probabilities was also made with those obtained from more or less homogeneous traffic. It was found that values obtained in current study are high in most of the instances. This indicates risk-taking behaviour of driver population, which eventually affects safety of such roads. The present study, thus, demonstrates the need of investigating vehicle-type-specific headways under mixed traffic based on comprehensive field data.


First published online 7 January 2021

Keyword : two-lane road, mixed traffic, vehicle-type-specific headway, distribution, goodness-of-fit

How to Cite
Roy, R., & Saha, P. (2020). Analysis of vehicle-type-specific headways on two-lane roads with mixed traffic. Transport, 35(6), 588-604. https://doi.org/10.3846/transport.2020.14136
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Dec 31, 2020
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