Evaluation of Traffic Congestion Mitigation Techniques Using an Entropy-TOPSIS Integrated Method

Hussain, Daniyal; Jamal, Arshad; Farooq, Asim; Almoshaogeh, Meshal; Alharbi, Fawaz; Farooq, Danish · 2025 · Crossref

DOI: 10.21203/rs.3.rs-6868367/v1

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Summary

This study addresses the critical issue of urban traffic congestion in Peshawar, Pakistan, where road transport handles 96% of freight and rapid population growth has overwhelmed infrastructure. The research aims to identify, evaluate, and rank major congestion hotspots using a novel integrated framework combining Geographic Information Systems (GIS) with Multi-Criteria Decision-Making (MCDM) techniques. Specifically, the authors sought to move beyond conventional statistical methods by applying Shannon Entropy and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to objectively assess congestion severity and guide targeted mitigation strategies. The methodology involved a two-stage approach focused on a 16-kilometer arterial corridor in Peshawar. First, ArcGIS was used for Important Zones Analysis, assigning weights to factors such as built-up areas, educational facilities, and markets to identify high-priority traffic zones. Within these zones, four major congestion hotspots—Amin Hotel, PC Hotel, Army Stadium, and Jalil Kabab House—were selected for detailed field analysis. Data collection included volume studies, spot speed measurements, and Passenger Car Unit (PCU) calculations based on Highway Capacity Manual standards. Additionally, volume-to-capacity (V/C) ratios and Level of Service (LOS) were computed. To rank the hotspots, the study employed the Shannon Entropy method to objectively determine criterion weights (avoiding subjective expert bias) and applied Fuzzy TOPSIS to calculate closeness coefficients for each location. The results confirmed severe congestion at all four sites, with peak hour PCU values exceeding allowable capacity limits. Amin Hotel recorded the highest congestion, with a peak hour PCU of 8,650 against a capacity of 5,504, resulting in a V/C ratio of 1.65. PC Hotel, Army Stadium, and Jalil Kabab House also exceeded capacity, with V/C ratios of 1.32, 1.35, and 1.50, respectively. The Shannon Entropy analysis identified "total traffic" (weight 0.40) and "V/C ratio" (weight 0.22) as the most influential criteria. The final TOPSIS ranking placed Amin Hotel as the most congested location (Rank 1, closeness coefficient 0.85), followed by PC Hotel, Jalil Kabab House, and Army Stadium. Key contributing factors identified through field observation and surveys included BRT corridor narrowing, inadequate parking, poor lane markings, and improperly placed police checkpoints. The significance of this study lies in its provision of a replicable, data-driven framework for urban mobility planning in developing countries. By integrating spatial analysis with objective MCDM techniques, the research offers a robust method for prioritizing traffic interventions. The findings serve as a benchmark for policymakers to implement targeted remedial measures, such as infrastructure improvements and enforcement strategies, to mitigate congestion and enhance sustainable urban mobility in similar contexts.

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• traffic density