Mixed Traffic Behaviour in Heavy Flow: Two-Lane Road Insights

Abstract

The current paper outlines a comprehensive methodology for modeling speed data on two-lane
roads during periods of heavy traffic characterized by heterogeneous vehicle types. In such
scenarios, the presence of diverse vehicle types causes a significant departure from the normal
speed distribution model. This deviation becomes particularly pronounced during heavy traffic
flows due to the frequent interactions among vehicles within the traffic stream. Consequently,
there arises a necessity to develop a modeling approach specifically tailored to such flow
conditions. Drawing upon empirical data collected from a major intercity road in India, this study
uncovers a notable skewness in speed data under heavy traffic conditions. This skewness primarily
stems from the formation of vehicle platoons within the traffic stream, exerting a substantial
influence on their speed characteristics. By scrutinizing the distribution of this data, the study
concludes that a logarithmic transformation effectively aligns with the assumption of normality.
This assertion is supported by various goodness-of-fit metrics, affirming the suitability of the
proposed modeling approach for capturing the intricacies of speed behavior in heterogeneous
traffic environments.