Evaluating the Impact of Smart Traffic Signal Systems on Urban Congestion: A Case Study of Denver

Abstract

Urban traffic congestion remains a pressing global challenge, exacerbated by increasing population densities and limited infrastructure investments. This study employs a combination of empirical methods, including real-time traffic data analytics and simulation modeling, to evaluate the efficacy of smart traffic signal systems implemented in Denver. The analysis, conducted over a six-month period, utilized quantitative measures such as average vehicle delay reduction, intersection throughput improvements, and emissions reductions. Findings indicate that the implementation of smart signals resulted in a 27% improvement in traffic flow and a 15% decrease in vehicular emissions, highlighting the potential for intelligent infrastructure solutions in mitigating urban congestion. Additionally, qualitative interviews with traffic management officials provided insights into operational challenges and strategic implications for scalability across other urban settings.