CSET Project #: 1703
Project Funding: CSET and UHM
Start Date: September 2017
End Date: December 2019
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 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.
Severe traffic crashes result in considerable incapacitating injuries and fatalities, especially in Rural, Isolated, Tribal, or Indigenous (RITI) communities, which have been disadvantaged from a traffic safety perspective across the United States. For example, although rural roads constitute only 40% of Vehicle Mile Traveled (VMT), more than 50% of fatalities occur on rural roadways and about 20,000 people are killed annually in rural crashes. In Hawaii, the rural crash fatality rate was 195% higher than the urban fatality rate in 2014 and native Hawaiians or other pacific islanders are involved in about 26% of motor vehicle traffic fatalities. It is necessary to build up the comprehensive data infrastructure to enhance the ability to develop informed data-driven plans and crash injury mitigation strategies. This project aims to develop an interactive baseline crash data platform to visualize and analyze rural crash characteristics in RITI communities. This research effort will gather and leverage existing traffic accident databases and develop an online system to dynamically retrieve rural traffic crash data and graphically visualize the data for crash attribute analysis. As part of baseline crash data infrastructure establishment, the proposed data platform will enable effective traffic safety program management at all levels in RITI communities to design and implement appropriate countermeasures to mitigate rural crash severities and risks. The proposed interactive baseline crash data platform can set a solid foundation for the development of effective traffic safety policies and successful public safety campaigns to reduce traffic crash injuries and fatalities in RITI communities.