Image Processing Approaches to Traffic Situation Understanding, Risk Assessment, and Safety

Yang, Dongfang; Ozguner, Umit; Redmill, Keith; Yurtsever, Ekim; Capito, Linda; Zhang, Haolin; Mobility21, Carnegie Mellon University

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ROSA P serves as an archival repository of USDOT-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by USDOT or funded partners. As a repository, ROSA P retains documents in their original published format to ensure public access to scientific information.

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Image Processing Approaches to Traffic Situation Understanding, Risk Assessment, and Safety

2023-07-28
By Yang, Dongfang ; Ozguner, Umit ; Redmill, Keith ; ...

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English

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Details:

Creators:

Yang, Dongfang ; Ozguner, Umit ; Redmill, Keith ; Yurtsever, Ekim ; Capito, Linda ; ... More +

Yang, Dongfang ; Ozguner, Umit ; Redmill, Keith ; Yurtsever, Ekim ; Capito, Linda ; Zhang, Haolin Less -
Corporate Creators:

Mobility21, Carnegie Mellon University
Corporate Contributors:

University of Pennsylvania ; Community College of Allegheny County ; Ohio State University

University of Pennsylvania ; Community College of Allegheny County ; Ohio State University Less -
Subject/TRT Terms:

[+]

Autonomous Vehicles Behavior Drivers Image Processing Machine Learning Private Passenger Vehicles Risk Assessment Traffic Flow Theory Traffic Lanes Traffic Safety Transit Buses
Resource Type:

Tech Report
Geographical Coverage:

United States
Corporate Publisher:

Mobility21 (UTC)
Abstract:

This project will explore several potential applications of image processing, including NN/deep learning technologies, to the analysis of traffic scenes involving passenger and transit vehicles. The project team outlines three potential applications below- the exact distribution of effort and topics addressed will depend on the availability of student and research staff. (1) Traffic scene risk assessment and driver behavior understanding (2) Methodologies for extracting information from transit vehicle video for traffic flow estimation (3) Optical flow for automated vehicle lane following
Format:

PDF
Funding:

69A3551747111
Collection(s):

University Transportation Centers
Main Document Checksum:

[+]

urn:sha256:80686d2a641dcbe92600fde1efeb6c80115de068550bd623cea719accfc51a68
Download URL:

https://rosap.ntl.bts.gov/view/dot/68477/dot_68477_DS1.pdf
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Image Processing Approaches to Traffic Situation Understanding, Risk Assessment, and Safety

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