Traffic Control Problem with Z-Number-Based Reasoning

Traffic congestion remains a significant challenge in urban areas, leading to wasted time, increased pollution, and decreased quality of life. This paper presents an approach to address traffic control problems by using a Z-information-based approach. Within this approach, a Z-reasoning and Z-regression apparatus allowing consideration of the accuracy and reliability of information from traffic cameras was employed. In real city conditions, various factors (weather conditions, illumination, etc.) impact the quality of camera-generated inputs. Traffic is managed by changing the green time and for this purpose, Z-number-based IF-THEN rules are suggested. By leveraging the power of modern traffic cameras and employing the Z-numbers paradigm to enhance the accuracy of input data, this approach offers a reliable and efficient traffic control system. The utilization of Z-number-based rules ensures a comprehensive consideration of relevant factors, leading to more informed decision-making. The integration of traffic cameras, similarity-based Z-reasoning engine, and Z-regression module implemented in Z-lab software, and the proposed solutions of increased green time and variable speed limits offer a practical and sustainable approach to alleviate traffic congestion and improve the overall traffic management process.