Perception and sensing for autonomous vehicles under adverse weather conditions: A survey
Nagoya University · Gifu University
Abstract
Automated Driving Systems (ADS) open up a new domain for the automotive industry and offer new possibilities for future transportation with higher efficiency and comfortable experiences. However, perception and sensing for autonomous driving under adverse weather conditions have been the problem that keeps autonomous vehicles (AVs) from going to higher autonomy for a long time. This paper assesses the influences and challenges that weather brings to ADS sensors in a systematic way, and surveys the solutions against inclement weather conditions. State-of-the-art algorithms and deep learning methods on perception enhancement with regard to each kind of weather, weather status classification, and remote sensing…
Citation impact
- FWCI
- 54.37
- Percentile
- 100%
- References
- 290
Authors
4Topics & keywords
- Adverse weather
- Perception
- Field (mathematics)
- Computer science
- Automotive industry
- Autonomy
- Domain (mathematical analysis)
- Extreme weather