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LiDAR-Based Urban Autonomous Platooning Simulation
Technical Paper
2020-01-0717
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
The technological advancements of Advanced Driver Assistance Systems (ADAS) sensors enable the ability to; achieve autonomous vehicle platooning, increase the capacity of road lanes, and reduce traffic. This article focuses on developing urban autonomous platooning using LiDAR and GPS/IMU sensors in a simulation environment. Gazebo simulation is utilized to simulate the sensors, vehicles, and testing environment. Two vehicles are used in this study; a Lead vehicle that follows a preplanned trajectory, while the remaining vehicle (Follower) uses the LiDAR object detection and tracking information to mimic the Lead vehicle. The LiDAR object detection is handled in multiple stages: point cloud frame transformation, filtering and down-sampling, ground segmentation, and clustering. The tracking algorithm uses the clustering information to provide position and velocity of the Lead vehicle which allows for vehicle platooning. This paper covers the LiDAR object detection and tracking algorithms as well as the autonomous platooning control algorithms which were tested in a simulation environment. Test results illustrate that the Follower vehicle was able to attain the autonomous platooning based on the LiDAR data.
Citation
Alzu'bi, H. and Tasky, T., "LiDAR-Based Urban Autonomous Platooning Simulation," SAE Technical Paper 2020-01-0717, 2020, https://doi.org/10.4271/2020-01-0717.Also In
References
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