AI-Enabled Intelligent Vibration Sensor for Active Highway-Rail Grade Crossings

Highway-Rail Grade Crossings (HRGCs) have many safety challenges due to the potential collisions between oncoming trains and road users, including vehicles, bicycles, and pedestrians. The implementation of Positive Train Control (PTC) technology is regarded as a promising solution to reduce rail accidents. However, its effectiveness is hindered at HRGCs, especially in rural regions, where radio and Global Positioning System (GPS) communication can be unreliable or lost (dark territory). To mitigate the risk of catastrophe, it is imperative for road users to detect trains early and maintain a safe distance allowing sufficient reaction time. This can be challenging especially in rural regions where it is difficult to supply enough power for advanced and heavy train detection sensors. This research seeks to develop an Artificial Intelligence (AI)-enabled vibration sensing system capable of identifying and tracking approaching trains from a considerable distance upstream. This advancement enables road users to preemptively initiate responsive actions within a secure timeframe. The system’s design is especially tailored for deployment in remote areas where there is limited access to electric power sources required for conventional vibration sensors.

• Record URL:
  https://www.utrgv.edu/railwaysafety/_files/documents/research/exhibit-d_utcrs_utrgv_ai-enabled-vibration-sensor-for-hrgc_2023.pdf
• Supplemental Notes:
  • Rio Valley Switching Company is a partner in this project.

Language

• English

Project

• Status: Active
• Funding: $86702
• Contract Numbers:

  69A3552348340

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590

  University of Texas Rio Grande Valley

  1201 W. University Dr
  Edinburg, TX  United States  78539
• Managing Organizations:

  University of Texas Rio Grande Valley

  1201 W. University Dr
  Edinburg, TX  United States  78539
• Project Managers:

  Stearns, Amy

• Performing Organizations:

  University of Texas Rio Grande Valley

  1201 W. University Dr
  Edinburg, TX  United States  78539
• Principal Investigators:

  Amjadian, Mohsen

  Tarawneh, Constantine

• Start Date: 20230901
• Expected Completion Date: 20240831
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Artificial intelligence; Detection and identification systems; Railroad grade crossings; Sensors; Vibration
• Subject Areas: Data and Information Technology; Railroads; Safety and Human Factors;

Filing Info

• Accession Number: 01898073
• Record Type: Research project
• Source Agency: University Transportation Center for Railway Safety
• Contract Numbers: 69A3552348340
• Files: UTC, RIP
• Created Date: Oct 31 2023 7:18PM