Object Detection in Autonomous Vehicles under Adverse Weather: A Review of Traditional and Deep Learning Approaches

• Published in: Algorithms Vol. 17; no. 3; p. 103
• Main Authors: Tahir, Noor Ul Ain, Zhang, Zuping, Asim, Muhammad, Chen, Junhong, ELAffendi, Mohammed
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.03.2024
• Subjects: Algorithms; Artificial intelligence; Automatic vehicle identification systems; Automation; Autonomous vehicles; Computer vision; Deep learning; Driverless cars; Evolution; Fatalities; Fog; Image processing; intelligent transportation system; Intelligent transportation systems; Literature reviews; Machine learning; Neural networks; object detection; Object recognition; Pedestrians; Roads & highways; Sensors; Snow; Surveillance; System effectiveness; traditional approaches; Traffic accidents & safety; Transportation planning; Weather; United Kingdom; Germany

Enhancing the environmental perception of autonomous vehicles (AVs) in intelligent transportation systems requires computer vision technology to be effective in detecting objects and obstacles, particularly in adverse weather conditions. Adverse weather circumstances present serious difficulties for...