Autonomous driving paper index
A Risk Level Assessment Method for Traffic Scenarios Based on BEV Perception
One-line summary
In this study, aimed at the test scenarios of autonomous vehicle, we propose a lidar-camera fusion approach for traffic environment sensing.
Engineering notes
Key topics: autonomous driving, autonomous vehicle, bev perception, bev, lidar, perception. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
How to fully test the safety and functionality under different driving scenarios is a key issue for the development and application of autonomous vehicles. In this study, aimed at the test scenarios of autonomous vehicle, we propose a lidar-camera fusion approach for traffic environment sensing. Based on the successful Lift-Splat-Shoot (LSS) model, we propose a unique data enhancement strategy to develop the fusion accuracy. Through building a test dataset with the highprecision acquisition vehicle, the proposed method is verified that the new fusion authorism proposed in this paper can accurately distinguish the translation, scale, orientation and velocity of the target. This study can promote test scenario generation methods.
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