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Behavior Prediction of Traffic Actors for Intelligent Vehicle Using Artificial Intelligence Techniques: A Review

Suresh KolekarComputer Science and Information Technology Department, Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune 412115, IndiaShilpa GiteComputer Science and Information Technology Department, Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune 412115, India and Symbiosis Centre of Applied AI (SCAAI), Symbiosis International (Deemed) University, Pune 412115, India. (e-mail: [email protected])Biswajeet PradhanCentre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Ultimo, NSW 2007, Australia and Earth Observation Center, Institute of Climate Change, UniversitiKebangsaan Malaysia, 43600 UKM, Bangi, Selangor, MalaysiaKetan KotechaComputer Science and Information Technology Department, Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune 412115, India and Symbiosis Centre of Applied AI (SCAAI), Symbiosis International (Deemed) University, Pune 412115, India
2021en
ABI

Аннотация

Intelligent vehicle technology has made tremendous progress due to Artificial Intelligence (AI) techniques. Accurate behavior prediction of surrounding traffic actors is essential for the safe and secure navigation of the intelligent vehicle. Minor misbehavior of these vehicles on the busy roads may lead to an accident. Due to this, there is a need for vehicle behavior research work in today’s era. This research article reviews traffic actors’ behavior prediction techniques for intelligent vehicles to perceive, infer, and anticipate other vehicles’ intentions and future actions. It identifies the key strategies and methods for AI, emerging trends, datasets, and ongoing research issues in these fields. As per the authors’ knowledge, this is the first systematic literature review dedicated to the vehicle behavior study examining existing academic literature published by peer review venues between 2011 and 2021. A systematic review was undertaken to examine these papers, and five primary research questions have been addressed. The findings show that using sophisticated input representation that includes traffic rules and road geometry, artificial intelligence-based solutions applied to behavior prediction of traffic actors for intelligent vehicles have shown promising success, particularly in complex driving scenarios. Finally, the paper summarizes the most widely used approaches in behavior prediction of traffic actors for intelligent vehicles, which the authors believe serves as a foundation for future research in behavior prediction of surrounding traffic actors for secure and accurate intelligent vehicle navigation.

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