Connected Vision for Increased Pedestrian Safety (CVIPS)

Bhagavatula, VIjayakumar; Sankaranarayanan, Aswin; Shenkut, Dereje; Carnegie Mellon University; Carnegie Mellon University. Traffic21 Institute. Safety21 University Transportation Center (UTC)

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Connected Vision for Increased Pedestrian Safety (CVIPS)

2024-07-31
Datasets Available
By Bhagavatula, VIjayakumar ; Sankaranarayanan, Aswin ; Shenkut, Dereje

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English

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Creators:

Bhagavatula, VIjayakumar ; Sankaranarayanan, Aswin ; Shenkut, Dereje

Bhagavatula, VIjayakumar ; Sankaranarayanan, Aswin ; Shenkut, Dereje Less -
Corporate Creators:

Carnegie Mellon University ; Carnegie Mellon University. Traffic21 Institute. Safety21 University Transportation Center (UTC)

Carnegie Mellon University ; Carnegie Mellon University. Traffic21 Institute. Safety21 University Transportation Center (UTC) Less -
Corporate Contributors:

United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology ; United States. Department of Transportation. University Transportation Centers (UTC) Program

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

[+]

Algorithms Cameras Communication Machine Vision Mobile Communication Systems Pedestrian Detectors Pedestrians Pedestrian Safety Perception Vulnerable Road Users
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final Report (July 1, 2023-June 30, 2024)
Corporate Publisher:

Carnegie Mellon University. Traffic21 Institute. Safety21 University Transportation Center (UTC)
Abstract:

Pedestrian safety has become a critical concern due to the higher risk of serious injury they are prone to in traffic accidents. To improve traffic safety, one promising approach is to advance the level of autonomy in vehicles. This report presents the results of a preliminary investigation of the limitations of single agent-based perception systems for pedestrian detection and the potential of collaborative or cooperative perception to further improve pedestrian detection, and the impact of communication on collaborative perception.
Format:

PDF
Funding:

69A3552344811
Collection(s):

University Transportation Centers
Main Document Checksum:

[+]

urn:sha-512:46eaeb73ab0ff74fdb80444f5213bd95b6269fa05ae1b359139288f2a16509afb0a4adbfdf0d810c08360a861c0d2c980b69c98989e35b874754c426649b86d4
Download URL:

https://rosap.ntl.bts.gov/view/dot/77491/dot_77491_DS1.pdf
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Connected Vision for Increased Pedestrian Safety (CVIPS)

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