In transportation, LiDAR sensors have been primarily used in surveying and autonomous driving as a major onboard sensing device to detect field objects. Recently, with reduced price and increased demand from real-time and trajectory-level traffic detection, LiDAR technology sees great potential for becoming a mainstream means of infrastructure-based traffic detection other than only being used onboard. In addition to its many advanced features, LiDAR is much less impacted by illumination conditions compared to video sensors and significant in data processing speed, which makes it ideal for real-time traffic detection. The research team has conducted a wealth of studies to investigate the feasibility of installing LiDAR sensors at the roadside to obtain trajectories of automobiles and pedestrians at a frequency of 10 Hz. While our findings on how to process roadside LiDAR data have been presented in other literatures, this paper reveals our findings on another important issue regarding roadside LiDAR application–installation strategies to achieve the best performance. The authors first developed a theoretical approach based on the analysis of the built-in features of the applied LiDAR sensors and followed the results to install the sensors in our testbed. Then, experimental studies were conducted onsite and examined the theoretical results accordingly. As a result, a technical guidance for proper installation of LiDAR sensors at the roadside for the best real-time and trajectory-level traffic detection was produced. This study helps researchers and practitioners in better preparing for future deployment of roadside LiDAR sensors as part of the connected vehicles and infrastructures.
|Journal||Journal of Intelligent Transportation Systems: Technology, Planning, and Operations|
|State||Accepted/In press - 2020|
- Detection range
- roadside LiDAR