Journal Article
Xiaoyu Guo, Yongxin Peng, and Chaolun Ma
Dec-20
Guo, X., Peng, Y., & Ma, C. (2020). Safety Criteria for Selecting a Smart Corridor: Random Forest Approach Using HSIS Data from Washington State. ITE Journal, 90(12), pp 35-44.
This article reports on a study that demonstrated a use of the Highway Safety Information System (HSIS) database to determine safety criteria for selecting a smart corridor using random forest, a machine-learning approach. HSIS contains a rich dataset, which includes various variables from many aspects of transportation. In this study, the authors implemented the random forest algorithm to finalize 13 safety criteria for selecting a smart corridor out of 111 variables in the HSIS and the Highway Performance Monitoring System (HPMS) from Washington State.
ITE Journal
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HSIS Summary Reports are two to eight pages in length and include a brief description of the issue addressed, data used, methodology applied, significant results, and practical implications.
A variety of research studies have been performed using data from HSIS. Many of the final reports prepared are now available electronically.
Research reports are often summarized in executive summaries, technical briefs, or other abbreviated formats. Included here are those road safety summaries that involved research using HSIS data.
In addition to conducting research, HSIS resources are also used to develop products that can be used by practitioners in the analysis of safety problems.
HSIS data are sometimes used in research studies that result in other types of finished products, such as dissertations, theses, and conference proceedings.
