Next Generation Traffic Data and Incident Detection from Video

Preisen, Linda; Deeter, Dean

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Next Generation Traffic Data and Incident Detection from Video

2014-09-01
By Preisen, Linda ; Deeter, Dean

File Language:

English

Details

Creators:

Preisen, Linda ; Deeter, Dean
Corporate Creators:

Athey Creek Consultants
Corporate Contributors:

Evaluating New Technologies for Roads Program Initiatives in Safety and Efficiency (ENTERPRISE) Transportation Pooled Fund Study TPF-5 (231) ; Michigan. Department of Transportation
Subject/TRT Terms:
Publication/ Report Number:

ENT-2014-2
Resource Type:

Research Paper
Geographical Coverage:

Iowa;Missouri;Ontario
Corporate Publisher:

Athey Creek Consultants
Abstract:

The term Video Analytics refers to the capability of analyzing video feeds to determine events that are not based on a single image. A number of commercially available Video Analytics systems are available that are capable of processing video streams from fixed and pan-tilt-zoom traffic cameras and then automatically creating alerts for conditions such as traffic incidents, stopped/slow moving vehicles, wrong-way vehicle movements, wildlife, and debris in real-time. Additionally, data collected by these systems can include traffic volume by lane, speed, vehicle classification, and lane occupancy. The Ministry of Transportation of Ontario (MTO) partnered with the ENTERPRISE Transportation Pooled Fund Program to conduct a project to research and document the potential for Video Analytics as a tool for traffic operations centers (TOCs) and for traffic data collection. This report summarizes the testing results of several systems in the United States (Iowa, Missouri) and in Ontario, Canada, under real-world environments.
Format:

PDF
Funding:

(C) 2010-0316 (Auth) Z14;TPF-5(231)
Download URL:

https://rosap.ntl.bts.gov/view/dot/61483/dot_61483_DS1.pdf
File Type:

[PDF - 1.44 MB]
Collection(s):

US Transportation Collection
Main Document Checksum:

urn:sha-512:282fcfc039bc13b3e1ef29a5370e1afacf9af564735d918e393690fc80c73011aac4d20edd54437cc24177e79fac2145b788072d5a255585cbb5717718740771

File Language:

English

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