Utilizing Emergency Management Audio Messages for Traffic Incident Management Performance Measures

Details

• Creators:
  Vajpayee, Vihaan ; Gartner, Christopher ; Desai, Jairaj C. ; Bullock, Darcy M.
• Corporate Creators:
  Purdue University. Joint Transportation Research Program
• Corporate Contributors:
  United States. Department of Transportation. Federal Highway Administration ; Indiana Department of Transportation
• Subject/TRT Terms:
  Advanced Traffic Management Systems Automatic Speech Recognition Case Studies Emergency Management Incident Management Intelligent Transportation Systems Performance Measurement Public Safety Answering Point Safety Speech Recognition Traffic Incident Management Traffic Safety

  More +
• Publication/ Report Number:
  FHWA/IN/JTRP-2026/15
• DOI:
  https://doi.org/10.5703/1288284318623
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States ; Indianapolis (Indiana) ; Chicago (Illinois)
• Edition:
  Final Report
• Corporate Publisher:
  Purdue University. Joint Transportation Research Program
• Abstract:
  Timely and accurate information regarding roadway incidents is critical for Traffic Management Centers (TMCs) to maintain safety and mobility. While Intelligent Transportation Systems (ITS) cameras and crowdsourced data provide significant visibility, rural interstate corridors often suffer from coverage gaps, or "blind spots," where incidents go undetected until significant queuing occurs. Public safety radio communications serve as the primary coordination method for first responders, creating a "verbal infrastructure" that contains vital information regarding incident location and severity. This study evaluates the feasibility of using Automatic Speech Recognition (ASR) to bridge these gaps by monitoring and analyzing radio traffic. The project developed and validated a prototype system capable of capturing, transcribing, and geolocating public safety radio transmissions for Traffic Incident Management (TIM) along a 71-mile segment of I-65 between Indianapolis and Chicago. The findings include a system latency assessment, transcription accuracy analysis, noise filtering, and a case study. Further recommendations are made based on the findings for improving results and larger implications.
• Format:
  PDF
• Funding:
  SPR-4931
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:0ded175c2cb42f9aff9b86d3baff5b2f3aea8a78ccc4607d1875f92d35bec9dcdb6befcd0cd41207074abe3b86667a1e5f91b7669a032f9861a410c5dd566824
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/92708/dot_92708_DS1.pdf
• File Type:
  [PDF - 14.82 MB ]