Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys
arXiv:2303.17220 · doi:10.1109/TIV.2022.3223131
Abstract
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits. Although a number of surveys have reviewed research achievements in this field, they are still limited in specific tasks, lack of systematic summary and research directions in the future. Here we propose a Survey of Surveys (SoS) for total technologies of AD and IVs that reviews the history, summarizes the milestones, and provides the perspectives, ethics, and future research directions. To our knowledge, this article is the first SoS with milestones in AD and IVs, which constitutes our complete research work together with two other technical surveys. We anticipate that this article will bring novel and diverse insights to researchers and abecedarians, and serve as a bridge between past and future.
13 pages, 3 tables, 0 figure
References in corpus (15)
- Deep Learning-based Vehicle Behaviour Prediction For Autonomous Driving Applications: A Review
- Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives
- Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review
- A Review on Energy, Environmental, and Sustainability Implications of Connected and Automated Vehicles
- A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving
- A Survey of End-to-End Driving: Architectures and Training Methods
- A2D2: Audi Autonomous Driving Dataset
- One Thousand and One Hours: Self-driving Motion Prediction Dataset
- One Million Scenes for Autonomous Driving: ONCE Dataset
- Ford Multi-AV Seasonal Dataset
- A Commute in Data: The comma2k19 Dataset
- Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies
- PandaSet: Advanced Sensor Suite Dataset for Autonomous Driving
- LiDAR Odometry Methodologies for Autonomous Driving: A Survey
- Validation Frameworks for Self-Driving Vehicles: A Survey
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