Using Time-Series Analysis to Precisely Identify and Rank Road Hotspots
Over the past decades, many ranking methods have been proposed. However, results vary from method to method, and one of the issues behind ranking is the element of subjectivity. One approach to resolve these issues is the use of combined models. One of the combined models is the Enhanced Empirical Bayesian (EB) method that incorporates the use of the similarity measure based on the Proportion Discordance Ratio (PDR). This model is developed to assess and objectively quantify similarity among road segments based on crash patterns, each of which contains a unique combination of selected crash-related features. The goal of this project is to identify a group of similar road segments for the estimation of road segment safety levels and to identify and rank road hotspots for a particular highway at certain hours of the day and days of the week. Based on this assessment, USDOT can find the root cause of the high risk of crash occurrences, and recommendations can be effectively made on a case-by-case basis to reduce such risk. This project addresses the themes of “Developing Data, Models, and Tools” and “Improving Multi-Modal Planning and Shared Use of Infrastructure”.
- Record URL:
Language
- English
Project
- Status: Completed
- Funding: $15000
-
Contract Numbers:
NITC 1180
69A3551747112
-
Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
TREC at Portland State University
1900 SW Fourth Ave, Suite 175
P.O. Box 751
Portland, Oregon United States 97201 -
Project Managers:
Hagedorn, Hau
-
Performing Organizations:
College of Architecture, Planning, and Landscape Architecture
PO Box 210075
Tucson, AZ United States 85721 -
Principal Investigators:
Lee, Alexander
Lin, Wei
- Start Date: 20171204
- Expected Completion Date: 20181205
- Actual Completion Date: 20200110
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: High risk locations; Highway safety; Ranking (Statistics); Time periods; Time series analysis
- Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;
Filing Info
- Accession Number: 01651398
- Record Type: Research project
- Source Agency: National Institute for Transportation and Communities
- Contract Numbers: NITC 1180, 69A3551747112
- Files: UTC, RIP
- Created Date: Nov 21 2017 9:46PM