Optimal Weaving Lengths for Improved Traffic Flow Efficiency on Urban Arterial Roads: Case Study, Sulaymaniyah City, Kurdistan Region, Iraq

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Authors: Bakhtiar Tahir Tofiq Al barznji, Hirsh Muhammad Majid
Cited by: 0

Abstract

Efficient design of weaving sections is critical for maintaining smooth traffic flow on urban arterial roads. This study investigates optimal weaving lengths (WL) for improving traffic flow efficiency using two weaving sections located on Malik Mahmud Ring Road in Sulaymaniyah City, Kurdistan Region, Iraq, as a case study. Traffic and geometric data were collected through drone footage and processed using data from Sky Viewer to extract detailed vehicle trajectories. A calibrated and validated microsimulation model was developed in PTV VISSIM 2024 to replicate real-world traffic conditions. A full factorial experimental design tested the effects of WL, mainline traffic volume, and weaving volume on section performance. The results demonstrated that WL significantly influences both capacity and level of service (LOS). Shorter sections constrained lane-changing maneuvers, while longer sections enhanced throughput and improved LOS; however, excessive length beyond 750 m for Section A and 350 m for Section B yielded diminishing returns. Regression analysis confirmed that the interaction between WL and volume ratio (VR) positively and significantly affected capacity, while higher VRs independently reduced efficiency. Section A achieved a stronger model fit (R² = 0.771) compared to Section B (R² = 0.650), reflecting site-specific geometric and traffic characteristics. The findings suggest that WLs of approximately 750 m for Section A and 350 m for Section B represent optimal design values for balancing roadway capacity and operational efficiency. This research provides a methodological framework for capacity estimation in weaving sections and offers practical insights for transportation planners and engineers in developing urban contexts.

Fields of Study & Subjects

Traffic control and management Traffic and Road Safety Traffic Prediction and Management Techniques

Publication details

Journal / source
Journal of Engineering
Volume
32
Issue
1
Pages
38–55
Publication date
1 January 2026