Optimizing First Responder Routes Based on Railroad Crossings and Street Traffic Information

Qian, Yu; Chen, Yuche; Wu, Xuanke

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Optimizing First Responder Routes Based on Railroad Crossings and Street Traffic Information

2026-09-11
By Qian, Yu ; Chen, Yuche ; Wu, Xuanke

File Language:

English

Details

Creators:

Qian, Yu ; Chen, Yuche ; Wu, Xuanke
Corporate Creators:

University of South Carolina
Corporate Contributors:

United States. Department of Transportation. Federal Railroad Administration. Office of Research, Development and Technology
Subject/TRT Terms:
Publication/ Report Number:

DOT/FRA/ORD-26/20
Resource Type:

Tech Report
Geographical Coverage:

United States
Contracting Officer:

Jacobini, Francesco Bedini
Corporate Publisher:

United States. Department of Transportation. Federal Railroad Administration
Description:

From August 2021 to August 2023, the Federal Railroad Administration funded a research team from the University of South Carolina, in partnership with the city of Columbia, South Carolina, and CSX to develop an optimized dispatching strategy to assist 911 dispatch centers in identifying optimal routes for emergency responders. In this research, the team specifically studied potential delays caused by railroad grade crossing blockages. To address these challenges, the research team developed a shortest-path optimization model designed to minimize overall response times for emergency dispatch operations. This model incorporates a dynamic framework that predicts grade crossing blockages by estimating train arrival and departure times, and creating time windows to account for expected closure periods. Additionally, the model integrates real-time traffic information to improve dispatch accuracy.
Format:

PDF
Download URL:

https://rosap.ntl.bts.gov/view/dot/93428/dot_93428_DS1.pdf
File Type:

[PDF - 2.03 MB]
Collection(s):

Federal Railroad Administration
Main Document Checksum:

urn:sha-512:cc1964810f8c81d91621371f20d25e2d392af3e03962248c01df18a1a30046412d2cc8e56522e2a2ca67f3169f44ac3c608bf2f771765786b68a6a7d458177ee

File Language:

English

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