Center for Safety Equity in Transportation

rural • isolated • tribal • indigenous

Extracting Rural Crash Injury and Fatality Patterns Due to Changing Climates in RITI Communities Based on Enhanced Data Analysis and Visualization Tools

  • Active

    CSET Project #: 1805

    Project Funding: CSET and University of Hawai'i - Manoa

  • Start Date: July 2018

    End Date: September 2019

    Budget: $115,138

Principal Investigator(s)

Guohui Zhang

The PIs has emphasized their research on crash severity formulation, analysis, and mitigation in the transportation program at the University of Hawaii. Zhang has conducted several relevance projects: 1) Alcohol Influenced Driver Injury Severity Mitigation in Intersection-Related Crashes in New Mexico; 2) Exploratory Multinomial Logit Regression Model-based Teenage and Adult Driver Injury Severity Analyses in Rear-End Crashes; and 3) Mixed Logit Model-based Driver Injury Severity Investigations in Single- Vehicle and Multi-Vehicle Crashes on Two-lane Rural Highways. The first project provides valuable insights in driver behavior analysis under the influence of alcohol in intersection-related crashes. Findings of the second project can be beneficial to better understand the difference between teenage and adult drivers, and their specific attributes in rear-end crashes. The third project enhances our understanding of single-vehicle and multi-vehicle involved crashes and advances crash severity research methodology. All these projects would provide solid contributions to the proposed project. The modeling approaches used in those three projects can be helpful to this study. Our experiences and findings from these three projects will make the proposed project start at a higher level. Guided by the USDOT’s priorities to promote the safe, efficient and environmentally sound movement of goods and people, this project will develop crash record database and research findings are helpful for transportation agencies to develop cost-effective solutions to reduce crash severities and improve traffic safety performance in RITI communities. 

Panos Prevedouros

Panos D. Prevedouros, PhD is a Professor of Transportation and Chairman of the Department of Civil Engineering at the University of Hawaii at Manoa where and he developed and manages UH’s Traffic and Transportation Laboratory. He’s a Subcommittee Chair of the Transportation Research Board (TRB), a unit of the National Academies. Prevedouros is a registered Professional Engineer in the European Union, a Court-qualified Traffic and Transportation Engineering expert in Hawaii and Illinois, and an Envision Sustainability Professional (ENV SP). Prevedouros has expertise in urban road network management, traffic safety including incident management, traffic flow simulation, traffic signal optimization, intelligent transportation systems, demand forecasting and alternatives analysis, sustainable infrastructure including transportation, energy, policies and regulation. As of September 2017, Dr. Prevedouros has published 49 Technical Reports, 48 Academic Journal Papers, 45 Conference Refereed Papers, 35 Proceedings Papers, and co-authored the 2nd and 3rd editions of internationally adopted textbook Transportation Engineering and Planning (Prentice Hall, 1993 and 2001.) He has pioneered effective traffic solutions for Honolulu such as traffic underpasses and reversible flow lanes. He’s also developed a realistic plan for Hawaii’s energy future. He blogs on Hawaii’s infrastructure challenges at fixoahu.blogspot.com.

David T.Ma

  • Structural Health Monitoring
  • Nondestructive Testing
  • Seismic- and Wind- Structural Control
  • Structural Dynamics
  • Linear and Nonlinear System Identification

Project Summary

Climate changes have induced extreme weather conditions, storm surge, and sea level rise, resulting in enormously low temperature, strong wind, heavy snow, flash flood, fog, hurricane, tsunamis, etc. in the CSET consortium states (Alaska, Hawaii, Washington, and Idaho) and tremendously impacted traffic safety performance by leading to more frequent and serious traffic crashes in Rural, Isolated, Tribal, or Indigenous (RITI) communities. For example, the average annual precipitation is predicted to increase by 15% to 30% by 2100 in Alaska compared to 1971-1999. More precipitation could lead to more mudslides, debris flows, and avalanches, causing more traffic crashes with severe injuries and fatalities. Traffic crashes may increase as thawing permafrost damages Alaska's roads, railroads, airstrips, and trails. In Hawaii, over the next 30 to 70 years, approximately 6,500 structures and 19,800 people statewide will be exposed to chronic flooding. An estimated $19 billion in economic loss would result from chronic flooding of land and structures located in the sea level rise exposure area and approximately 38 miles of coastal roads would be chronically flooded and become impassible, jeopardizing critical access to many RITI communities. Changing climates will influence traffic safety substantially due to roadway infrastructure deteriorations and increased crash risks and injury outcomes. The combination of adverse climate and poor pavement conditions contributes to 18% of fatal crashes and 22% of injury crashes annually. On the other hand, more 50% of fatalities occur on rural roadways and about 20,000 people are killed annually in rural crashes. The U.S. Department of Transportation (USDOT) indicates that the fatality rate (fatalities per Vehicle Mile Traveled (VMT)) for rural crashes is more than twice the fatality rate in urban crashes. In Hawaii, the rural crash fatality rate is 195% higher than the urban one and native Hawaiians or other pacific islanders are involved in about 26% of motor vehicle traffic fatalities in 2014. Therefore, it is of practical importance to investigate and extract rural crash injury and fatality patterns resulted from adverse weather and climate changes in RITI communities. A crash data analysis and visualization tool will be developed to facilitate online rural crash data interpretation as Phase I in the first year of this two-year project. In the second year, a multinomial Logit model-Bayesian network hybrid approach will be developed as Phase II to discover the underlying injury and fatality patterns of rural crashes impacted by adverse weather and climate changes to identify significant crash contributing attributes in the CSET consortium states. The crash data analysis and visualization tool as well as the research findings are helpful for transportation agencies to develop cost-effective countermeasures to mitigate rural crash injury severities under extreme climate and weather conditions and minimize the rural crash risks and severities in the States of Alaska, Washington, Idaho, and Hawaii.