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Performance Test of Autonomous Vehicle Lidar Sensors Under Different Weather Conditions

Li Tang, Yunpeng Shi, Qing He, Adel W. Sadek, Chunming Qiao

2020Transportation Research Record Journal of the Transportation Research Board75 citationsDOI

Abstract

This paper intends to analyze the Light Detection and Ranging (Lidar) sensor performance on detecting pedestrians under different weather conditions. Lidar sensor is the key sensor in autonomous vehicles, which can provide high-resolution object information. Thus, it is important to analyze the performance of Lidar. This paper involves an autonomous bus operating several pedestrian detection tests in a parking lot at the University at Buffalo. By comparing the pedestrian detection results on rainy days with the results on sunny days, the evidence shows that the rain can cause unstable performance and even failures of Lidar sensors to detect pedestrians in time. After analyzing the test data, three logit models are built to estimate the probability of Lidar detection failure. The rainy weather still plays an important role in affecting Lidar detection performance. Moreover, the distance between a vehicle and a pedestrian, as well as the autonomous vehicle velocity, are also important. This paper can provide a way to improve the Lidar detection performance in autonomous vehicles.

Topics & Concepts

LidarRangingPedestrianComputer scienceKey (lock)Pedestrian detectionRemote sensingObject detectionEnvironmental scienceReal-time computingArtificial intelligenceTransport engineeringEngineeringGeographyTelecommunicationsPattern recognition (psychology)Computer securityVehicle emissions and performanceAutonomous Vehicle Technology and SafetyRemote Sensing and LiDAR Applications
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