Vehicle Lateral Offset Estimation Using Infrastructure Information for Reduced Compute Load Western Michigan University

Format:

Book

Conference/Event

Author/Creator:

Sharma, Sachin, author.

Contributor:

Asher, Zachary

Ekti, Ali Riza

Fanas Rojas, Johan

Meyer, Rick

Wang, Chieh Ross

Conference Name:

WCX SAE World Congress Experience (2023-04-18 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2023

Summary:

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 energyefficient IIS, chipenabled 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

Notes:

Vendor supplied data

Publisher Number:

2023-01-0800

Access Restriction:

Restricted for use by site license