Safety Support System for HRGCs
As a result of the considerable differences in mass between vehicles and trains, crashes at highway-rail grade crossings (HRGCs) often result in severe injuries and fatalities. Therefore, HRGC safety is considered a crucial transportation safety issue. Transportation decision makers and agencies need an efficient safety decision-making framework that is able to predict crash occurrence and severity likelihoods in the same prediction model, identify and quantify contributors and their marginal effects, quantify geometric and countermeasures’ safety improvement effectiveness, and rank the priorities for the crossings in terms of their safety improvement needs. This study proposed a statistical approach for HRGC crash analysis. The proposed method is competing risk model and the approach is Cox proportional hazard regression. This predictive method was well established in the bioscience area but never utilized in the transportation area. Competing risk model (CRM) is a special type of survival analysis to accommodate the competing nature of multiple outcomes from the same event of interest; in transportation safety analysis, the competing multiple outcomes are accident severity levels while the event of interest is accident occurrence. Transportation decision makers need a prioritization system to categorize crossings’ risk level based on their expected crash frequency and crash severity simultaneously. Therefore, with a hazard-ranking approach, which considers a crossing’s crash severity and frequency output, transportation decision makers are able to ensure that federal and state funds for grade crossing improvement projects are spent at crossings that are considered the most in need of improvement. Moreover, significant contributors, including geometric contributors and countermeasures, are identified, and their marginal effectiveness is also summarized. In this study, the hazard ranking model based on crash likelihoods resulted by the proposed CRM method is used to classify grade crossings and crossing locations based on their crash frequency and severity likelihood simultaneously. The risk analysis is conducted by using the risk matrix and spatial risk analysis. Finally, an interactive app that incorporates all the findings of the research is developed for agencies to use as a simulation tool.
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- Summary URL:
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Supplemental Notes:
- This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program. Cover title: Safety Support System for Highway Rail Grade Crossings
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Corporate Authors:
North Dakota State University, Fargo
Fargo, ND United States 58105 North Dakota State University
Fargo, ND United States 58108Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Authors:
- Lu, Pan
- Tolliver, Denver
- Keramati, Amin
- Ren, Yihao
- Zheng, Zijian
- Zhou, Xiaoyi
- Publication Date: 2023-2
Language
- English
Media Info
- Media Type: Digital/other
- Edition: Final Report
- Features: Figures; References; Tables;
- Pagination: 37p
Subject/Index Terms
- TRT Terms: Crash risk forecasting; Crash severity; Decision support systems; Highway safety; Railroad grade crossings; Railroad safety; Risk analysis
- Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Railroads; Safety and Human Factors;
Filing Info
- Accession Number: 01875821
- Record Type: Publication
- Report/Paper Numbers: MPC-23-493
- Contract Numbers: MPC-550
- Files: UTC, NTL, TRIS, ATRI, USDOT
- Created Date: Mar 20 2023 9:35AM