EureCar turbo: A self-driving car that can handle adverse weather conditions

Autonomous driving technology has made significant advances in recent years. In order for self-driving cars to become practical, they are required to operate safely and reliably even under adverse driving conditions. However, most current autonomous driving cars have only been shown to be operationa...

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Bibliographic Details
Main Authors: Unghui Lee, Jiwon Jung, Seunghak Shin, Yongseop Jeong, Kibaek Park, Shim, David Hyunchul, In-so Kweon
Format: Conference Proceeding
Language:English
Subjects:
Cameras
Laser radar
Lasers
Meteorology
Roads
Sensors
Vehicles
Online Access:Request full text
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Summary:Autonomous driving technology has made significant advances in recent years. In order for self-driving cars to become practical, they are required to operate safely and reliably even under adverse driving conditions. However, most current autonomous driving cars have only been shown to be operational under amiable weather conditions, i.e., on sunny days on dry roads. In order to enable autonomous cars to handle adverse driving conditions such as rain and wet roads, the algorithm must be able to detect roads within a tolerable margin of error using sensors such as cameras and laser scanners. In this paper, we propose a sensor fusion algorithms that is able to operate under a variety of weather conditions, including rain. Our algorithm was validated when a strong shower occurred during the 2014 Hyundai Motor Company's Autonomous Car Competition. In this paper, we present the competition results that were collected on the same course on both sunny and rainy days. Based on the comparison, we propose the future directions to improve the autonomous driving capability under adverse environmental conditions.
ISSN:2153-0866
DOI:10.1109/IROS.2016.7759359