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Autonomous vehicle perception: The technology of today and tomorrow
Institution:1. Advanced Control and Intelligent Systems Laboratory, University of British Columbia, Kelowna, British Columbia, Canada;2. Laboratoire sur les Interactions Vehicules, Infrastructure, Conducteurs (LIVIC), IFSTTAR-CoSys-LIVIC, 25 alle des Marronniers, 78000 Versailles, France;1. Canadian Institute for Cybersecurity, Faculty of Computer Science, University of New Brunswick, Canada;2. School of Information Technology and Engineering, Vellore Institute of Technology, India;3. Department of Electrical and Computer Engineering, Lebanese American University, Byblos, Lebanon;4. School of Computer Science and Technology, University of Bedfordshire, United Kingdom;5. Department of Electrical and Electronic Engineering, University of Sri Jayewardeneprua, Sri Lanka;6. School of Computer Science, University Collage Dublin, Ireland;7. Centre for Wireless Communications, University of Oulu, Finland;1. Department of Management and Humanities, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak, Malaysia;2. Economics Department, Indiana University Bloomington, United States;3. Department of HRM, Faculty of Economics and Administration, King Abdulaziz University, P.O Box 80201, Jeddah 21589, Saudi Arabia;1. The University of Utah, Department of Civil & Environmental Engineering, 110 Central Campus Drive, Salt Lake City, UT 84112, United States;2. The University of Texas at Austin, Department of Civil, Architectural and Environmental Engineering, 301 E. Dean Keeton St., Austin, TX 78712, United States
Abstract:Perception system design is a vital step in the development of an autonomous vehicle (AV). With the vast selection of available off-the-shelf schemes and seemingly endless options of sensor systems implemented in research and commercial vehicles, it can be difficult to identify the optimal system for one’s AV application. This article presents a comprehensive review of the state-of-the-art AV perception technology available today. It provides up-to-date information about the advantages, disadvantages, limits, and ideal applications of specific AV sensors; the most prevalent sensors in current research and commercial AVs; autonomous features currently on the market; and localization and mapping methods currently implemented in AV research. This information is useful for newcomers to the AV field to gain a greater understanding of the current AV solution landscape and to guide experienced researchers towards research areas requiring further development. Furthermore, this paper highlights future research areas and draws conclusions about the most effective methods for AV perception and its effect on localization and mapping. Topics discussed in the Perception and Automotive Sensors section focus on the sensors themselves, whereas topics discussed in the Localization and Mapping section focus on how the vehicle perceives where it is on the road, providing context for the use of the automotive sensors. By improving on current state-of-the-art perception systems, AVs will become more robust, reliable, safe, and accessible, ultimately providing greater efficiency, mobility, and safety benefits to the public.
Keywords:Automotive sensors  Autonomous vehicles  Intelligent vehicles  Localization and mapping  Machine vision  Sensor fusion
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