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.
Highlights
Time headway is defined as the time interval, usually measured in seconds, between successive vehicles in the traffic flow
Important to know the specific distribution for a particular roadway and traffic condition
Headway between two vehicles depends on the type of lead vehicle and is influenced by its size and dynamics
Summary
Time headway is defined as the time interval, usually measured in seconds, between successive vehicles in the traffic flow. It is an important characteristic of traffic, which affects capacity estimation, safety analysis and microscopic simulation (Ye, Zhang 2009). Performance of a simulation model is largely affected by inputs and generation of inter-arrival times or time headways is considered as a key component in regard to this (Jang et al 2011). Estimated headways can be used in gap acceptance analysis and car-following behaviour studies (Ye, Zhang 2009). Mei and Bullen (1993) reported the use of lognormal distribution at car-following situation
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