Traffic Congestion in Sharjah: Strategies Between Urban Growth and Innovation

Abstract

This study employs a mixed-methods approach to diagnose the causes and impacts of traffic congestion in Sharjah, UAE, and propose technology-driven mitigation strategies. A systematic literature review was supplemented with a field survey of 134 residents and visitors, utilizing stratified sampling to ensure representation. GIS kernel density analysis identified critical congestion hotspots at Al Ittihad Road and Al Wahda Street. Key findings reveal primary drivers include rapid population growth (1.8 million, 2023), high private vehicle dependency (85.8%), and peak-hour bottlenecks. The proposed solution, Nasaq (NSQ), is an AI-integrated platform leveraging IoT sensors and real-time data analytics, theoretically framed within smart mobility and behavioral change models. Recommendations include digital infrastructure upgrades, public transport expansion, and pedestrian-centric urban redesign, aligning with UAE's AI Strategy 2031 and Net Zero 2050 framework.