Vehicle Lateral Offset Estimation Using Infrastructure Information for Reduced Compute Load
Accurate perception of the driving environment and a highly accurate position of the vehicle are paramount to safe Autonomous Vehicle (AV) operation. AVs gather data about the environment using various sensors. For a robust perception and localization system, incoming data from multiple sensors is usually fused together using advanced computational algorithms, which historically requires a high-compute load. To reduce AV compute load and its negative effects on vehicle energy efficiency, we propose a new infrastructure information source (IIS) to provide environmental data to the AV. The new energy–efficient IIS, chip–enabled raised pavement markers are mounted along road lane lines and are able to communicate a unique identifier and their global navigation satellite system position to the AV. This new IIS is incorporated into an energy efficient sensor fusion strategy that combines its information with that from traditional sensor. IIS reduce the need for camera imaging, image processing, and LIDAR use and point cloud processing. We show that IIS, when combined with traditional sensors, results in more accurate perception and localization outcomes and a reduced AV compute load.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/01487191
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Supplemental Notes:
- Abstract reprinted with permission of SAE International.
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Authors:
- Sharma, Sachin
- Fanas Rojas, Johan
- Ekti, Ali Riza
- Wang, Chieh (Ross)
- Asher, Zachary
- Meyer, Rick
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Conference:
- WCX SAE World Congress Experience
- Location: Detroit Michigan, United States
- Date: 2023-4-18 to 2023-4-20
- Publication Date: 2023-4-11
Language
- English
Media Info
- Media Type: Web
- Features: References;
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Serial:
- SAE Technical Paper
- Publisher: Society of Automotive Engineers (SAE)
- ISSN: 0148-7191
- EISSN: 2688-3627
- Serial URL: http://papers.sae.org/
Subject/Index Terms
- TRT Terms: Actuators; Autonomous vehicles; Cloud computing; Energy conservation; Mathematical models; Navigation systems; Sensors; Visualization
- Subject Areas: Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01880014
- Record Type: Publication
- Source Agency: SAE International
- Report/Paper Numbers: 2023-01-0800
- Files: TRIS, SAE
- Created Date: Apr 20 2023 9:56AM