Proactive Five-Step Process Model for Effective Tribal Crash Reporting

Underreporting or no reporting of crash data that involves crashes on Tribal lands creates a significant void in data necessary to support State Department of Transportation (DOT) and Tribal safety programs. This paper presents a proactive process model developed for improving tribal crash reporting with self-assessment tools. The process model includes five steps, namely, self-assessment; establishing and maintaining communication and relationship between tribes and states; building Tribal crash data collection system; implementing State-Tribal crash data sharing; and improving Tribal traffic safety with crash data. The process can be used in a proactive way by both state and tribal agencies. A user begins with completing the self-assessment as the first step. Completing the self-assessment simply involves answering a few questions designed to identify areas of strength and areas that need improvement when evaluating an effective tribal crash reporting system. The results of the self-assessment will then lead the user to different remaining steps, depending upon the result of the self-assessment. In each step of the process, detail guidelines for improving the practice of this step are provided. The guidelines are based on best practices, success stories, lessons learned, published literature, and data from Tribes and States that were involved in a nationwide data collection. After improvement is carried out in practice based on guidelines, the user can later redo the self-assessment and identify whether that weakness has been addressed. In summary, the five-step process with self-assessment offers a proactive approach will lead tribal and state agencies in a successful direction in improving crash reporting.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ABE80 Standing Committee on Native American Transportation Issues.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Li, Zhixia
  • Noyce, David A
  • Bill, Andrea R
  • Chesnik, Kevin
  • Qin, Xiao
  • Macy, Alyssa
• Conference:
  • Transportation Research Board 95th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2016-1-10 to 2016-1-14
• Date: 2016

Language

• English

Media Info

• Media Type: Digital/other
• Features: References; Tables;
• Pagination: 14p
• Monograph Title: TRB 95th Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Crash data; Crash reports; Data collection; Traffic safety
• Uncontrolled Terms: Tribal lands
• Subject Areas: Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01593781
• Record Type: Publication
• Report/Paper Numbers: 16-4606
• Files: TRIS, TRB, ATRI
• Created Date: Mar 16 2016 9:36AM