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.
Traffic Control Problem with Z-Number-Based Reasoning
Lect. Notes in Networks, Syst.
International Conference on Theory and Applications of Fuzzy Systems and Soft Computing ; 2023 ; Antalya, Türkiye September 14, 2023 - September 15, 2023
16th International Conference on Applications of Fuzzy Systems, Soft Computing and Artificial Intelligence Tools – ICAFS-2023 ; Kapitel : 7 ; 28-36
15.11.2024
9 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Decision-Theoretic Reasoning for Traffic Monitoring and Vehicle Control
British Library Conference Proceedings | 1995
|Traffic control and the traffic problem
Engineering Index Backfile | 1925
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