Machine Learning for Autonomous Vehicle Real-time Traffic Monitoring and Analysis
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[1]
Dr. Alexandre Bayen, “Machine Learning for Autonomous Vehicle Real-time Traffic Monitoring and Analysis”, Journal of Bioinformatics and Artificial Intelligence, vol. 1, no. 1, pp. 40–53, Jun. 2024, Accessed: Nov. 21, 2024. [Online]. Available: https://biotechjournal.org/index.php/jbai/article/view/20

Abstract

This paper intends to provide a state-of-the-art literature review that covers topics pertinent to autonomous vehicles and real-time traffic monitoring and analyse research relating to these areas. Several autonomous vehicle topics were recognised including, but not limited to the following: fine pattern concerning the simulation, validation research and control techniques for unexpected autonomous vehicle movement, disaster response considerations and their enhancements, a Pavelbravo obstacle avoiding algorithm, ant colony system improved technical strategies and implementation plan development for sub-micrometer precision. Moreover autonomous vehicle topics were found influencing real-world visions, delivery traffic organisation, an everyday modification of car sales and traffic accident forecast. This review finds an analysis of contemporary research across these pertinent areas can be used to identify knowledge challenges and potential measures to overcome such challenges.

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