Research Article
Challenges in Object Detection Under Rainy Weather Conditions
@INPROCEEDINGS{10.1007/978-3-030-14757-0_5, author={Sinan Hasirlioglu and Andreas Riener}, title={Challenges in Object Detection Under Rainy Weather Conditions}, proceedings={Intelligent Transport Systems, From Research and Development to the Market Uptake. Second EAI International Conference, INTSYS 2018, Guimar\"{a}es, Portugal, November 21--23, 2018, Proceedings}, proceedings_a={INTSYS}, year={2019}, month={2}, keywords={Object detection Camera Lidar Radar Perception Rain Adverse weather condition Vehicle safety Autonomous driving}, doi={10.1007/978-3-030-14757-0_5} }- Sinan Hasirlioglu
Andreas Riener
Year: 2019
Challenges in Object Detection Under Rainy Weather Conditions
INTSYS
Springer
DOI: 10.1007/978-3-030-14757-0_5
Abstract
Intelligent vehicles use surround sensors which perceive their environment and therefore enable automatic vehicle control. As already small errors in sensor data measurement and interpretation could lead to severe accidents, future object detection algorithms must function safely and reliably. However, adverse weather conditions, illustrated here using the example of rain, attenuate the sensor signals and thus limit sensor performance. The indoor rain simulation facility at CARISSMA enables reproducible measurements of predefined scenarios under varying conditions of rain. This simulator is used to systematically investigate the effects of rain on camera, lidar, and radar sensor data. This paper aims at (1) comparing the performance of simple object detection algorithms under clear weather conditions, (2) visualizing/discussing the direct negative effects of the same algorithms under adverse weather conditions, and (3) summarizing the identified challenges and pointing out future work.
