2013 Session: 614

• Evaluation of Effectiveness of Automatic Crash Information Notification Systems on Freeways
  Abstract: The automatic crash information notification system (ACINS) is a well-known technology with promising potential to reduce the crash response time (CRT) of emergency medical services. Reducing CRT will contribute to saving the lives of and alleviating the severity of injuries for crash victims. To fully operate the ACINS, it is important to quantify the safety benefits, which is fundamental for justifying public investment. This study proposed a methodology for quantifying the effectiveness of the ACINS and applied the methodology to the Korean freeway system. The proposed methodology consists of three steps. Fist, a statistical model was developed to predict injury severity using ordered logistic regression. Second, the amount of reduced CRT that would result from the ACINS was estimated. The effectiveness of the ACINS, which are defined as the number of reduced fatalities and severe injuries, were derived after considering the market penetration rate (MPR). When the proposed methodology is applied to 2010 freeway crash data, the result that fatalities are reduced by 11.8-18.1% when there is a 100% MPR. The outcomes of this study support decision making for public investments and for establishing relevant traffic safety policies.
  Authors: Jeong, Eunbi; Oh, Cheol; Kim, Taehyung; Kim, Ikki
  Authors: Jeong, Eunbi; Oh, Cheol; Kim, Taehyung; Kim, Ikki
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 614
  Paper Number: 13-1269
• Benefit-Cost Analysis of Investing in Data Systems and Processes for Data-Driven Safety Programs
  Abstract: Deciding to invest in data is often a challenge for transportation agencies. State transportation agencies often face budget constraints and pressure to use their limited resources on more tangible projects than data and information collection. Data investments often compete for funding with safety improvements to the infrastructure and roadway projects. Infrastructure improvements are visible to the driving public and often have immediate safety impacts; the impact of data investments may not be as obvious to the public. Investments in safety data, however, inform States’ decision-making process regarding which safety improvements can have the most impact and where those improvements can be most effective. The Federal Highways (FHWA) Office of Safety commissioned this research to develop guidance on the methodologies that can be applied to determine the benefits of investing in data, data systems, and processes for achieving a data-driven safety program. The components of this research included a Safety Data Investment Benefit-Cost Analysis Methodology, which established a methodology to quantify the potential impacts of investment in safety data improvement, a Decision-making Guidebook, which provided a step-by-step approach for representatives of State transportation agencies to follow and customize the methodology based on their level of existing data, and a Final Report, which detailed each phase of the research process and included the results of a comprehensive literature review on the economic costs and benefits of investing in roadway safety data.
  Authors: Lawrence, Michael Fitzpatrick; Cartwright-Smith, Devon; Lefler, Nancy X.; Mans, Janine; Nguyen, Paul
  Authors: Lawrence, Michael Fitzpatrick; Cartwright-Smith, Devon; Lefler, Nancy X.; Mans, Janine; Nguyen, Paul
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 614
  Paper Number: 13-4486
• Benefit-Cost Analysis of Investing in Data Systems and Processes for Data-Driven Safety Programs
  Authors: Cartwright-Smith, Devon
  Authors: Cartwright-Smith, Devon
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology
  Session: 614
  Paper Number: 13-4486
• Evaluation of Effectiveness of Automatic Crash Information Notification Systems on Freeways
  Authors: Jeong, Eunbi
  Authors: Jeong, Eunbi
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology
  Session: 614
  Paper Number: 13-1269