The proposed approach has been verified on an autonomous vehicle platform. Introduction Research on autonomous vehicles such as driverless cars has received great attention in the past ten years, pedestrian recognition and tracking, as one of the most important issues for autonomous vehicles, also ...
Additionally, the volume of input data for object detection is very large, which makes it difficult to meet the real-time and high uncertainty requirements of autonomous driving. Therefore, it is necessary for autonomous driving to conduct further research and achieve reliable and real-time object ...
This paper discusses current developments and research on MEMS-based lidars. The LiDcAR project is introduced for bringing precise and reliable MEMS-based lidars to enable safe and reliable autonomous driving. As a part of development in this project, a test bench for the characterization and ...
Ford autonomous vehicle research has been ongoing for about a decade, and the company said it’s working toward fully autonomous driving capability, which, as defined by SAE International Level 4, does not require the driver to intervene and take control of the vehicle. Ford said it will tri...
Simon Ritchie, based in London is tracking the democratisation of Lidar Surveying, but his research shows that the pace is still slow, despite the emergence of the price crushing, autonomous vehicle market. Introduction Lidar has been used for land surveying for fifty years or more. In days gon...
Alexander Carballo, PhD, Senior Research Fellow, Tier IV “The Automotive LIDAR conference provides a direct line to key R&D experts, which is profound considering the pace of development in this sector. The digital platform used by the conference organizers is very well suited for the presentation...
In this paper, we review the latest finding in 3D LIDAR localization for autonomous driving cars, and analyze the results obtained by each method, in an effort to guide the research community towards the path that seems to be the most promising....
AUTONOMOUS vehiclesRADARDETECTORSMULTIPLE target trackingMultitarget tracking based on multisensor fusion perception is one of the key technologies to realize the intelligent driving of automobiles and has become a research hotspot in the field of intelligent driving. However, most current autono...
Alexander Carballo, PhD, Senior Research Fellow, Tier IV “The Automotive LIDAR conference provides a direct line to key R&D experts, which is profound considering the pace of development in this sector. The digital platform used by the conference organizers is very well suited for the presentation...
本研究中使用的传感器是Velodyne HDL - 64E S3、Point Gray Research公司的Grashhopper 2 GS2 - GE - 50S 5C - C摄像机和Axis通信P1214 - E网络摄像机。传感器融合以10Hz运行,与LiDAR同步。每个融合数据对的目标检测推断时间约为250毫秒。优化框架,如NVIDIA的TenSORT [ 23,可能会大大减少推理时间。