Intelligent Traffic Anomaly Diagnosis Through the Integration of Diverse Information Sources: Final Report

Peckham, Joan; Hunter, Chris; DiPippo, Lisa; Herve, Jean-Yves; University of Rhode Island. Department of Computer Science and Statistics

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Intelligent Traffic Anomaly Diagnosis Through the Integration of Diverse Information Sources: Final Report

2005-05-01
By Peckham, Joan ; Hunter, Chris ; DiPippo, Lisa ; ...

[PDF-332.17 KB]

English

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Creators:

Peckham, Joan ; Hunter, Chris ; DiPippo, Lisa ; Herve, Jean-Yves

Peckham, Joan ; Hunter, Chris ; DiPippo, Lisa ; Herve, Jean-Yves Less -
Corporate Creators:

University of Rhode Island. Department of Computer Science and Statistics
Corporate Contributors:

University of Rhode Island. Transportation Center ; University Transportation Centers Program (U.S.)

University of Rhode Island. Transportation Center ; University Transportation Centers Program (U.S.) Less -
Subject/TRT Terms:

[+]

Algorithms Data Banks Data Collection Data Integration Global Positioning System Highways I72: Traffic And Transport Planning I73: Traffic Control Intelligent Transportation Systems Loop Detectors Monitoring Operations And Traffic Management Planning And Forecasting Real Time Information Reports Self-driving Vehicles Simulation Software Terminals And Facilities Traffic Control Centers
Publication/ Report Number:

URITC FY01-09
Resource Type:

Tech Report
Geographical Coverage:

United States ; Rhode Island

United States ; Rhode Island Less -
TRIS Online Accession Number:

1002823
OCLC Number:

61103884
Edition:

Final report
Corporate Publisher:

University of Rhode Island. Transportation Center
Abstract:

While most transportation centers have the capability to collect and access various types of information such as planned and unplanned traffic incidents, and real-time and archived sensor data, many have not integrated this information in a coherent fashion. Information about anomalous highway situations can be collected from a variety of (currently) standalone sources and if integrated, would allow presentation of this data to transportation professionals and the traveling public, thereby enabling real-time and long term planning. The goal of this project was to simulate incoming data as it would be collected by a transportation agency from various sources such as inductive loop detectors, global positioning system devices, human reporters monitoring the system, emergency management personnel, and planned incident reports. In this project, a software prototype was developed that integrates incoming information about the roadway and uses this information in a centralized and intelligent computer algorithm that can provide transportation experts with accurate and timely diagnoses of traffic anomalies.
Format:

PDF
Funding:

URI 536159
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:8f8724821ca60dfa98529a33cba34c90269f38d4ed944631adc2c5e65cd62843
Download URL:

https://rosap.ntl.bts.gov/view/dot/38494/dot_38494_DS1.pdf
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Intelligent Traffic Anomaly Diagnosis Through the Integration of Diverse Information Sources: Final Report

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