The distribution characteristics of vehicle speeds on multilane highways approaching major and metropolitan cities, using a six-lane segment of the M-05 Kyiv – Odesa highway as a case study, are investigated in this paper. The research methodology is based on field observations employing frame-by-frame video analysis with an accuracy of 0.04 seconds, enabling precise identification of time headways between vehicles and calculating their instantaneous speeds. Both theoretical and empirical speed distribution curves were constructed. Typical speed ranges for different traffic lanes were identified, and the conformity of the observed data to the normal distribution law was statistically verified.
The research identified several key analytical directions in the study of vehicle speed distribution on multilane highways. Specifically, the investigation focused on assessing the conformity of empirical data to the normal distribution model, establishing characteristic speed ranges by vehicle type, and evaluating the influence of traffic volume and traffic flow composition on speed parameters. The authors also examined the spatiotemporal structure of traffic flow, including the daily distribution of traffic volumes, lane-by-lane and directional variation, and empirical and theoretical speed distribution curves. Relationships among key traffic parameters – volume, density, and speed – were analyzed. A linear regression method was applied to describe the lane-wise distribution of vehicles, enabling the derivation of analytical dependencies N₁, N₂, and N₃ on total traffic volume N using the least squares method.
The results showed that the speed distribution on the studied highway segment aligns well with the normal distribution, with observed deviations being random. The obtained 85th percentile speed (98 km/h) can serve as a reference for setting recommended speed limits, modeling roadway capacity, and developing intelligent traffic management systems components
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