Evaluation of signal phasing and timing plans for mixed traffic condition based on information entropy

Signalized intersections in China have long experienced traffic congestion and accidents due to mixed traffic. Increasing car ownership in developing countries is inevitable, leading to worsening traffic congestion and emissions. However, high construction costs and legal restrictions have impeded traditional road infrastructure expansion and improvement projects. As a result, transportation authorities, particularly in developing countries, face the significant challenge of finding cost-effective traffic management solutions to mitigate traffic congestion and emissions. Signal control is considered a crucial method for optimizing traffic flow. This study examines the effects of diverse signal control strategies on signalized intersections from a microscopic perspective, focusing on optimal fixed signal timing and available road traffic resources. To effectively assess the intersection operation state under different signal control strategies, this study introduces the concept of information entropy from physics. The proposed evaluation system can be directly applied to existing road infrastructure. This system provides a clearer understanding of the most effective signal control strategy for signalized intersections in a mixed-traffic environment, while also maintaining the current road traffic resources. This study introduces a novel signal control evaluation system based on information entropy theory, providing transportation management with a scientific decision-making tool. This approach significantly optimizes signal timing plans within mixed traffic environments under existing road resource constraints. Consequently, it effectively alleviates congestion, reduces accidents and emissions, and ultimately maximizes traffic resource utilization, thereby promoting sustainable development of the transportation system.