Evaluation of traffic congestion mitigation techniques using an entropy-TOPSIS integrated method.

Area of Science:

• Urban planning and transportation engineering.
• Geographic Information Systems (GIS) and spatial analysis.
• Traffic management and policy development.

Background:

• Road traffic congestion is a critical challenge in developing nations, notably Pakistan, where road transport dominates freight.
• Peshawar faces significant traffic issues, impacting daily commutes and economic activities.
• Existing infrastructure and urban design contribute to severe traffic bottlenecks.

Purpose of the Study:

• To identify and analyze critical traffic routes and congestion hotspots in Peshawar, Pakistan.
• To rank congestion severity using integrated multi-criteria decision-making techniques.
• To provide data-driven insights for effective traffic mitigation strategies.

Main Methods:

• Utilized ArcGIS for Important Zones Analysis to identify key routes.
• Employed Passenger Car Unit (PCU) analysis, volume-to-capacity ratios, and Level of Service (LOS) calculations.
• Integrated Shannon Entropy and Fuzzy TOPSIS methods for ranking congestion areas.

Main Results:

• Identified 'Amin Hotel Point' as the most congested location (Rank-1), followed by 'PC Hotel' and 'Jalil Kabab House'.
• Peshawar's major roads exceed capacity during peak hours, causing significant blockages.
• Key contributing factors include BRT infrastructure, insufficient parking, poor lane markings, and fixed obstructions.

Conclusions:

• The study provides a robust methodology for ranking traffic congestion hotspots in urban areas.
• Findings offer a benchmark for implementing targeted traffic interventions and policy measures.
• The research supports sustainable urban mobility and congestion mitigation in developing countries.