Infrastructure-Based LiDAR Monitoring for Assessing Automated Driving Safety
2022-01-0086
03/29/2022
- Event
- Content
- The successful deployment of automated vehicles (AVs) could include the use of off-board sensors for assessments to be made of AV operational safety. Many intersections and roadways have monocular cameras used primarily for traffic monitoring; however, monocular cameras may not be sufficient to allow for useful AV operational safety assessments to be made in all operational design domains (ODDs) such as low ambient light and inclement weather conditions. Additional sensor modalities such as Light Detecting And Ranging (LiDAR) sensors allow for a wider range of scenarios to be accommodated, but may also provide improved measurements of the Operational Safety Assessment (OSA) metrics previously introduced by the Institute of Automated Mobility (IAM). Building on earlier work from the IAM in creating an infrastructure-based sensor system to evaluate the OSA metrics in real-world scenarios, this paper presents an approach for real-time localization and velocity estimation for AVs using a network of LiDAR sensors. The LiDAR data are captured by a network of three Luminar LiDAR sensors at an intersection in Anthem, AZ, while camera data are collected from the same intersection. Using the collected LiDAR data, the proposed method uses a distance-based clustering algorithm to detect 3D bounding boxes for each vehicle passing through the intersection. Subsequently, the positions and velocities of each detected bounding box is tracked over time using a combination of two filters. The accuracy of localization and velocity estimation using LiDAR is assessed by comparing the LiDAR estimated state vector and the differential GPS position and velocity measurements from a test vehicle passing through the intersection, as well as against the camera-based algorithm results. It is shown that the proposed method, taking advantage of simultaneous data capture from multiple LiDAR sensors, offers great potential for fast, accurate operational safety assessment of AVs.
- Citation
- Srinivasan, A., Mahartayasa, Y., Jammula, V., lu, D. et al., "Infrastructure-Based LiDAR Monitoring for Assessing Automated Driving Safety," SAE Technical Paper 2022-01-0086, 2022, .