A Sensor Fusion and Localization System for Improving Vehicle Safety in Challenging Weather Conditions

Singh, Abhay P.; Vegamoor, Vamsi Krishna; Rathinam, Sivakumar

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A Sensor Fusion and Localization System for Improving Vehicle Safety in Challenging Weather Conditions

2021-12-01
By Singh, Abhay P. ; Vegamoor, Vamsi Krishna ; Rathinam, Sivakumar

File Language:

English

Details

Creators:

Singh, Abhay P. ; Vegamoor, Vamsi Krishna ; Rathinam, Sivakumar
Corporate Creators:

Safety through Disruption (Safe-D) University Transportation Center (UTC) ; Texas A&M Transportation Institute
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:
Publication/ Report Number:

04-117
Resource Type:

Tech Report
Geographical Coverage:

United States;Texas
Edition:

Final Report
Corporate Publisher:

Safety through Disruption (Safe-D) University Transportation Center (UTC)
Abstract:

SAE Level 5 autonomy requires the autonomous vehicle to be able to accurately sense the environment and detect obstacles in all weather and visibility conditions. This sensing problem becomes significantly challenging in weather conditions that include such events as sudden change in lighting, smoke, fog, snow, and rain. There is no standalone sensor currently on the market that can provide reliable perception data in all conditions. We demonstrate that a combination of Long Wave Infrared (LWIR) cameras with radar provide a viable sensing system that is robust to adverse visibility conditions. We have validated this prototype system both in simulation as well as in real-world traffic using a 2017 Lincoln MKZ operating in College Station, TX.
Format:

PDF
Funding:

69A3551747115/ Project 04-117
Download URL:

https://rosap.ntl.bts.gov/view/dot/60996/dot_60996_DS1.pdf
File Type:

[PDF - 1.91 MB]
Collection(s):

Autonomous Vehicles ; University Transportation Centers
Main Document Checksum:

urn:sha-512:21be9fa69127b8448db0241a6431345bd13efb1088a2611ac411f306c5a4741fc8321d1f056ff5381d3f955d328d17f2487dd51d82a018cbf7f8087db10f1fa9

File Language:

English

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