GIS-Based Instructional Tool for Crash Prediction Methods

The first version of the Highway Safety Manual (HSM) was released in 2010 and is currently being deployed by several states as the primary methodology for performing predictive analysis to identify critical segments of the network and to evaluate the benefits of countermeasures. In this context, it is critical to train the current and future professionals on the underlying theory behind these methods and the effective application of the same. Although the HSM methods rely on vast amounts of spatial data (roadway network and geometry, geo-coded crashes etc.), the training materials rely mostly on spreadsheet-based tools for application of the methods and the HSM software is also non-spatial and does not directly integrate with Geographic Information Systems (GIS). The intent of this study was to develop a GIS-based instructional tool which can be used by both graduate students and current professionals to learn about the HSM-based predictive methods. The GIS platform of the tool is immensely beneficial so that the students can appreciate (visually) the context in which these methods are being applied. As such, this study contributes to both the educational and technology transfer goals of the Southeastern Transportation Research Innovation, Development and Education Center (STRIDE). The overall project methodology comprises two steps. First, the HSM crash-prediction methods are coded into the Signal Four Software for selected facility types. This involved coding in the appropriate Safety Performance Functions and Crash Modification Factors. Next, an Instructional Module provides overviews of both the software and the analytical methods in addition to providing step-by-step guidance for segment- and intersection-level analyses. The result is that this project developed an interactive GIS web-based instructional tool for Crash Prediction Models. Included is a self-instructing tutorial which can be used by students either independently or in the context of a course. These tutorials use data from Florida, however, since the software is web-based, the tool can be accessed and used easily by anyone within the region. The GIS-environment facilitates the students appreciating the context in which the data are obtained and methods applied and thereby leads to improved understanding of the methods. The project directly contributes to enhancing the goals of transportation safety within the region. The instructional module will facilitate improved understanding of the HSM-based predictive methods and the appropriate application of the same. In the longer term, the authors envision that the consistency checks and comparative analysis capabilities supported by the software will also lead to improvements in data and methods, which in turn, would translate into better predictive capabilities. The instructional module is designed to allow future scalability into a full crash prediction feature of the Signal Four Analytical system in order to support the needs of researchers and practitioners in the traffic safety improvements efforts.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Maps; Tables;
  • Pagination: 48p

Subject/Index Terms

Filing Info

  • Accession Number: 01677483
  • Record Type: Publication
  • Report/Paper Numbers: Project # 2013-030
  • Files: UTC, TRIS, RITA, ATRI, USDOT
  • Created Date: Aug 1 2018 11:11AM