The availability of accurate estimates for the headway distribution for specific lanes and classes during diverse periods of the day is of dominant importance for several applications in ITS. For instance, these estimates can be used for realistic multiclass multilane vehicle generation in microscopic traffic simulation tools, online lane-specific capacity and person-car-equivalents estimation - and consequent ITS applications, infrastructural design and planning - safety analysis, and gap-acceptance behaviour. Recently, a new statistical technique was developed, enabling fast, accurate and robust estimation of cornposite headway distribution models. In this paper, the estimation procedure is generalised towards headway observations that are disaggregated with respect to the roadway lanes, the vehicle types and the periods of the day. Consequently, the parameters of the new lane-specific mixed vehicle-type headway distribution model are estimated. Distinction of lanes, vehicle-types and sample periods provides insight into the plausibility of the headway distributions and parameter values, as well as into the lane-specific car-following behaviour of the distinct vehicle-classes varying across the different periods. By applying the new estimation procedure to motorway traffic data, the estimated headway distributions are compared with real-life data. It is shown that headway distributions can be accurately described using the proposed headway distribution model. Significant differences between the different periods of the day, the roadway lanes, and the vehicle types are found. These differences are interpreted from different viewpoints, such as vehicle characteristics, travel purpose, and time of day. Using these estimates the passenger-car-equivalents with respect to capacity for trucks on the roadway lanes are determined and analysed.
Samenvatting