Response of Autonomous Vehicles to Emergency Response Vehicles (RAVEV)

Nayak, Abhishek; Rathinam, Sivakumar; Gopalswamy, Swaminathan

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Response of Autonomous Vehicles to Emergency Response Vehicles (RAVEV)

2020-06-01
By Nayak, Abhishek ; Rathinam, Sivakumar ; Gopalswamy, Swaminathan

File Language:

English

Details

Creators:

Nayak, Abhishek ; Rathinam, Sivakumar ; Gopalswamy, Swaminathan
Corporate Creators:

Safety through Disruption (Safe-D) University Transportation Center (UTC) ; Texas A&M University. College Station
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 ; State of Texas
Subject/TRT Terms:
Publication/ Report Number:

03-051
Resource Type:

Tech Report
Geographical Coverage:

Texas;United States
Edition:

Final Report
Corporate Publisher:

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

The objective of this project was to explore how an autonomous vehicle identifies and safely responds to emergency vehicles using visual and other onboard sensors. Emergency vehicles can include police, fire, hospital and other responders’ vehicles. An autonomous vehicle in the presence of an emergency vehicle must have the ability to accurately sense its surroundings in real-time and be able to safely yield to the emergency vehicle. This project used machine learning algorithms to identify the presence of emergency vehicles, mainly through onboard vision, and then maneuver an in-path non-emergency autonomous vehicle to a stop on the curbside. Two image processing frameworks were tested to identify the best combination of vision-based detection algorithms, and a novel lateral control algorithm was developed for maneuvering the autonomous vehicle.
Format:

PDF
Funding:

69A3551747115
Download URL:

https://rosap.ntl.bts.gov/view/dot/64739/dot_64739_DS1.pdf
File Type:

[PDF - 1.95 MB]
Collection(s):

Autonomous Vehicles ; University Transportation Centers
Main Document Checksum:

urn:sha-512:723e29b17123209238344eab016dadab97e9b4d9c2ea2a57cfec848b2ab23afec4374d231ec43b0f8bce73388cef60236cd86d94e68ee31ff6398bd66664c2a6

File Language:

English

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