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.

References

1. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
2. Al-Madani, A. A., Al-Madani, F., Mohammed, S. I., Othman, W., Al-Madani, M., & Hussain, S. I. (2023). Traffic management in smart cities: A sustainable framework based on IoT and ITS. Sustainability, 15(13), 9859.
3. Department of Statistics & Community Development (DSCD). (2023). Statistical Yearbook. Sharjah Government.
4. Balwan, M., Varghese, T., & Nadeera, S. (2021). Urban traffic control system review - A Sharjah City case study. 2021 9th International Conference on Traffic and Logistic Engineering (ICTLE). IEEE.
5. Choudhary, A., Gokhale, S., Kumar, P., Pradhan, C., & Sahu, S. K. (2022). Urban traffic congestion: its causes-consequences-mitigation. Research Journal of Chemistry and Environment, 26(12), 164–176.
6. Mainali, S., Regmi, S., Wagle, K., & Bhele, R. (2024). Unraveling the traffic congestion due to bottleneck: A review. International Journal on Engineering Technology (InJET), 2(1), 71–79.