LIDAR Placement Optimization Using a Multi-Criteria Approach

Details

• Creators:
  Saka, Zainab A
• Corporate Creators:
  Purdue University
• Subject/TRT Terms:
  Autonomous Vehicle Handover Autonomous Vehicles Laser Radar Simulation Wireless Sensor Networks
• Resource Type:
  Thesis
• Geographical Coverage:
  United States
• Corporate Publisher:
  Purdue University
• Abstract:
  Most road fatalities are caused by human error. To help mitigate this issue and enhance overall transportation safety, companies are turning to advanced driver assistance systems and autonomous vehicle development. Perception, a key module of these systems, mostly uses light detection and ranging (LiDAR) sensors and enables object detection and environmental mapping. Extensive research on the use of LiDAR for autonomous driving has been documented in the literature. Yet still, several researchers and practitioners have advocated continued investigation of LiDAR placement on autonomous vehicles. To address this research need, this thesis begins with a comprehensive review of sensor technologies – camera, radio detection and ranging, global positioning system, and inertial measurement units – and exploring their strengths and limitations. Next, the thesis developed a methodological multiple criteria framework and implemented it in LiDAR placement optimization.
• Format:
  PDF
• Funding:
  69A3551747105
• Collection(s):
  University Transportation Centers Autonomous Vehicles
• Main Document Checksum:
  urn:sha-512:6e151bcfd3d3dfaf84be38ad5d613cee55283405adcc36a308fe8224da9ca450b3b681a2d155cd44451958dabdf58bacbc551739134ef9deb556485d68309407
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/74010/dot_74010_DS1.pdf
• File Type:
  [PDF - 3.22 MB ]