Towards application of light detection and ranging sensor to traffic detection: an investigation of its built-in features and installation techniques

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.

Automated summary

LiDAR sensors are widely used in transportation for surveying and autonomous driving. They have great potential for infrastructure-based traffic detection due to their reduced price and increased demand. Compared to video sensors, LiDAR is less affected by illumination and has faster data processing speed, making it ideal for real-time traffic detection. This study presents findings on the installation strategies of roadside LiDAR sensors for the best performance in real-time and trajectory-level traffic detection, providing guidance for future deployment.