Traffic congestion in Shimla: a smart city in the Himalayan mountain landscape—analyzing socioeconomic impacts from the perspectives of drivers and passengers

This study investigates the socio-economic impacts of traffic congestion in Shimla, a Smart City in the Indian Himalayan region undergoing rapid urbanization. Employing a mixed-methods design, it integrates structured surveys (n = 720), direct field observations, GIS-based spatial analysis, and real-time IoT sensor data. Quantitative analysis through descriptive statistics, ordinal logistic regression, t-tests, ANOVA, and Kruskal – Wallis tests revealed that congestion significantly affects travel times, stress levels, accident risks, and operational costs, with impacts varying across age, income, occupation, and gender groups. Thematic analysis of open-ended responses emphasized psychological stress, work disruptions, and family time loss as key concerns. Spatial regression (R2 = 0.76) identified major congestion hotspots such as Victory Tunnel and ISBT Crossing, linking physical delays with perceived socio-economic burdens. A cost – benefit analysis of proposed mitigation strategies – including adaptive traffic control, dedicated bus lanes, park-and-ride facilities, and seasonal traffic management – demonstrated strong feasibility and potential to reduce congestion delays by up to 30%. The findings offer actionable insights for sustainable urban mobility planning, emphasizing the need for targeted, data-driven interventions to enhance transport resilience in mountainous cities like Shimla. The study also contributes to broader discussions on Smart City development and sustainable urbanization in topographically constrained environments.