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Title:

High Collision Concentration Location Identification Method Based on Optimization Technique

Accession Number:

01664106

Record Type:

Component

Abstract:

High Collision Concentration Location (HCCL) identification approach based on the highest number of excessive collisions included within the limited covered length of hotspots has been proposed in this paper. A bi-criteria optimization model is created to maximize Potential for Safety Improvement (PSI) and to minimize the covered length by detected sites after considering the bias that can be introduced in the model due to the regression-to-the-mean phenomenon. The model is solved using Dynamic Programming-based Screening (DPS) techniques. The algorithm is computationally feasible to the size of historic collision data and applied to two freeways sites in San Francisco, California. The performance of the proposed model has also been compared with Sliding Moving Window (SMW) and Continuous Risk Profile (CRP) methods are compared to the DPS. Findings indicate that DPS can outperform both SMW and CRP in selecting sites with maximum PSI per unit distance.

Supplemental Notes:

This paper was sponsored by TRB committee ANB10 Standing Committee on Transportation Safety Management.

Report/Paper Numbers:

18-05114

Language:

English

Authors:

Lee, Jinwoo
Papakonstantinou, Ilia
Chung, Koohong
Kim, Dong-Kyu

Pagination:

7p

Publication Date:

2018

Conference:

Transportation Research Board 97th Annual Meeting

Location: Washington DC, United States
Date: 2018-1-7 to 2018-1-11
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References (20) ; Tables

Geographic Terms:

San Francisco (California)

Subject Areas:

Data and Information Technology; Highways; Safety and Human Factors

Source Data:

Transportation Research Board Annual Meeting 2018 Paper #18-05114

Files:

TRIS, TRB, ATRI

Created Date:

Jan 8 2018 11:17AM