Artificial intelligence applications in the development of autonomous vehicles: a survey
By Yifang Ma, Zhenyu Wang, Hong Yang, Lin Yang. IEEE/CAA Journal of Automatica Sinica, 2020
491 citations recorded by the source corpus.
The advancement of artificial intelligence ( AI ) has truly stimulated the development and deployment of autonomous vehicles ( AVs ) in the transportation industry. Fueled by big data from various sensing devices and advanced computing resources, AI has become an essential component of AVs for perceiving the surrounding environment and making appropriate decision in motion. To achieve goal of full automation ( i.e., self-driving ( , it is important to know how AI works in AV systems. Existing research have made great efforts in investigating different aspects of applying AI in AV development. However, few studies have offered the research community a thorough examination of current practices in implementing AI in AVs. Thus, this paper aims to shorten the gap by providing a comprehensive survey of key studies in this research avenue. Specifically, it intends to analyze their use of AIs in supporting the primary applications in AVs: 1) perception; 2) localization and mapping; and 3) decision making. It investigates the current practices to understand how AI can be used and what are the challenges and issues associated with their implementation. Based on the exploration of current practices and technology advances, this paper further provides insights into potential opportunities regarding the use of AI in conjunction with other emerging technologies: 1) high definition maps, big data, and high performance computing; 2) augmented reality( AR ) / virtual reality ( VR ) enhanced simulation platform; and 3) 5G communication for connected AVs. This paper is expected to offer a quick reference for researchers interested in understanding the use of AI in AV research.
Subfields: Automotive Engineering, Building and Construction
View Paper: https://www.semanticscholar.org/paper/2bd20336dd0b024eff47fd4b1bfd8d57b3553794
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In Automotive Engineering
Citations in the corpus
- A Survey on Trajectory-Prediction Methods for Autonomous Driving (2022, background): “A UTONOMOUS driving is attracting more and more atten-tionfrombothacademiaandindustrialsectors[1],because of its promising merits to solve many long-term transportation challenges related to safety, congestion, energy-saving, and so on [2], [3].”
- Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys (2023, unknown): “All the surveys are categorized into several sub-sections, including the overall [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], localization [14], [15], [16], [17], [18], [19],”