Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds

2019-05-13 · Qi Chen, Sihai Tang, Qing Yang, Song Fu

Autonomous vehicles may make wrong decisions due to inaccurate detection and recognition. Therefore, an intelligent vehicle can combine its own data with that of other vehicles to enhance perceptive ability, and thus improve detection accuracy and driving safety. However, multi-vehicle cooperative perception requires the integration of real world scenes and the traffic of raw sensor data exchange far exceeds the bandwidth of existing vehicular networks. To the best our knowledge, we are the first to conduct a study on raw-data level cooperative perception for enhancing the detection ability of self-driving systems. In this work, relying on LiDAR 3D point clouds, we fuse the sensor data collected from different positions and angles of connected vehicles. A point cloud based 3D object detection method is proposed to work on a diversity of aligned point clouds. Experimental results on KITTI and our collected dataset show that the proposed system outperforms perception by extending sensing area, improving detection accuracy and promoting augmented results. Most importantly, we demonstrate it is possible to transmit point clouds data for cooperative perception via existing vehicular network technologies.

📄 PDF Abstract BibTeX arXiv:1905.05265

Code (1)

DerrickXuNu/OpenCOOD pytorch

Tasks

3D Object Detection Autonomous VehiclesDiversityobject-detection Object Detection

How the Fusion of Onboard Sensors and V2X Data can Improve (or not) the Cooperative Perception of Connected Automated Vehicles

2026-07-08 · Amir Mohammadisarab, Miguel Sepulcre, Luca Lusvarghi, Javier Gozalvez arxiv

Automated vehicles rely on onboard sensors to perceive their surroundings and navigate autonomously. However, sensor performance may degrade under adverse weather conditions or when line-of-sight is obstructed. Cooperati…

CoBEVFusion: Cooperative Perception with LiDAR-Camera Bird's-Eye View Fusion

2023-10-09 · Donghao Qiao, Farhana Zulkernine

Autonomous Vehicles (AVs) use multiple sensors to gather information about their surroundings. By sharing sensor data between Connected Autonomous Vehicles (CAVs), the safety and reliability of these vehicles can be impr…

3D Object Detection Autonomous Vehicles object-detection Object Detection+1

F-Cooper: Feature based Cooperative Perception for Autonomous Vehicle Edge Computing System Using 3D Point Clouds

2019-09-13 · Qi Chen

Autonomous vehicles are heavily reliant upon their sensors to perfect the perception of surrounding environments, however, with the current state of technology, the data which a vehicle uses is confined to that from its …

3D Object Detection Autonomous Driving Autonomous Vehicles Edge-computing+4

SiCP: Simultaneous Individual and Cooperative Perception for 3D Object Detection in Connected and Automated Vehicles

2023-12-08 · Deyuan Qu, Qi Chen, Tianyu Bai, HongSheng Lu 외

Cooperative perception for connected and automated vehicles is traditionally achieved through the fusion of feature maps from two or more vehicles. However, the absence of feature maps shared from other vehicles can lead…

3D Object Detection object-detection Object Detection

Cooperative Perception with Deep Reinforcement Learning for Connected Vehicles

2020-04-23 · Shunsuke Aoki, Takamasa Higuchi, Onur Altintas

Sensor-based perception on vehicles are becoming prevalent and important to enhance the road safety. Autonomous driving systems use cameras, LiDAR, and radar to detect surrounding objects, while human-driven vehicles use…

Autonomous Driving Deep Reinforcement Learning reinforcement-learning Reinforcement Learning+1