Abstract

This paper deals with the speed choice behaviour of driver on a two-lane bidirectional highway in a heterogeneous traffic environment of a developing country. The major contribution of the paper is the identification and quantification of significant attributes influencing speed choice of a driver at micro-level of the road under study. The latter explored the use of ordinary least square (OLS) and random parameter (RPM) regression models as an alternative methodological approach to relate factors such as road geometry, roadside environment, traffic mix and operational characteristics with driver speed choice at the small segmental level. The comparison of the empirical results shows the RPM model outperforms its fixed parameter-based OLS counterpart. The approach justifies the need to take into account the potential heterogeneity in the impact of factors at the micro-level speed choice behaviour analysis. The analysis used data collected from a section of a major national highway in Bangladesh. Speed data extracted second-by-second was analysed for a range of short road segments. The critical segment length, from the point of view of speed analysis, was identified using different statistical tests. The paper details the data collection method used, as well as the speed-related statistics analysis performed. The results obtained could be used to better understand the speed choice factors of drivers. The findings could also be used to inform policy decisions for managing the appropriate homogeneity of speed among the motorized vehicles of two-lane highways in developing countries, a prerequisite for ensuring safe movement of road users.

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