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<p>Unsignalized intersections in India present significant challenges due to heterogeneous traffic flows and the absence of lane discipline, leading to inefficiencies and safety concerns. This study investigates traffic dynamics at such intersections using field data from Warangal city and the VISSIM micro-simulation model. Field measurements included traffic volume, speed, and vehicle arrival patterns, which revealed Poisson and negative exponential distributions for arrivals and headways, respectively. Key parameters such as critical gaps and follow-up times were estimated through regression analysis, forming the basis for capacity estimation using the highway capacity manual (HCM), Indo-HCM and Drew’s methods. Simulation results, validated with field data, demonstrated the impact of vehicle composition and conflicting volumes on intersection capacity and delay. The calibrated VISSIM model provided reliable predictions, highlighting the influence of heavy vehicles on reducing capacity. The findings emphasize the importance of vehicle-specific modeling and adherence to traffic regulations for improved intersection performance. Recommendations include enhancing lane discipline and exploring the potential for signalization at complex intersections.</p>

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Simulation-Based Capacity and Delay Analysis of Unsignalized Intersections in Mixed Traffic Conditions

  • 期刊论文

  • 发表日期：

    2025年6月22日

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  • Sruthi Sekhar Pallela,
  • Ramesh Babu Kota

摘要

Unsignalized intersections in India present significant challenges due to heterogeneous traffic flows and the absence of lane discipline, leading to inefficiencies and safety concerns. This study investigates traffic dynamics at such intersections using field data from Warangal city and the VISSIM micro-simulation model. Field measurements included traffic volume, speed, and vehicle arrival patterns, which revealed Poisson and negative exponential distributions for arrivals and headways, respectively. Key parameters such as critical gaps and follow-up times were estimated through regression analysis, forming the basis for capacity estimation using the highway capacity manual (HCM), Indo-HCM and Drew’s methods. Simulation results, validated with field data, demonstrated the impact of vehicle composition and conflicting volumes on intersection capacity and delay. The calibrated VISSIM model provided reliable predictions, highlighting the influence of heavy vehicles on reducing capacity. The findings emphasize the importance of vehicle-specific modeling and adherence to traffic regulations for improved intersection performance. Recommendations include enhancing lane discipline and exploring the potential for signalization at complex intersections.