Understanding the interactions and dynamics of vehicles in discretionary lateral movement process under disordered traffic conditions

Shivachethan Venkateshappa and Gowri Asaithambi

Physica A: Statistical Mechanics and its Applications, 2025, vol. 660, issue C

Abstract: The disordered nature of traffic in Southeast Asian countries, characterized by a diverse mix of vehicles with no strict lane discipline, leads to frequent lateral movements across the width of the road. These movements exhibit distinct lateral shift characteristics compared to the lane changes observed in ordered traffic, where vehicles (predominantly cars) follow lane discipline. Lateral shift characteristics and movement patterns are influenced by surrounding vehicles; however, this influence of surrounding vehicles is often neglected in existing related studies. The definition of lateral shift (LS) proposed in literature does not account for the surrounding vehicles, and this omission leads to the underestimation of LS frequency and overestimation of LS parameters, consequently affecting the identification of the exact LS time window. Moreover, studies on understanding LS patterns and classifying them are also limited. This study proposes a generalized definition for lateral shift based on the lateral positioning of the subject vehicle and its front vehicle and identifies the exact LS time window using a trajectory dataset collected in Chennai city using multiple unmanned aerial vehicles. Additionally, the study explores the characteristics of successful and failed LSs, analyzing the factors contributing to success or failure. Furthermore, the influence of lateral shifts on surrounding vehicles is examined. Lateral shifts are classified into four types: normal, forced, cooperative, and competitive, based on variations in the target follower’s acceleration before and during the LS. Statistical tests are conducted to assess the statistical independence of these classifications. The findings provide insights into driving behavior in disordered traffic, offering valuable input for developing microscopic traffic simulators and connected and autonomous vehicle systems for such traffic conditions.

Keywords: Lateral movements; Successful lateral shifts; Failed lateral shifts; Lateral shift classification; Trajectory data; Disordered traffic (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:660:y:2025:i:c:s0378437124008343

DOI: 10.1016/j.physa.2024.130324

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