CSET Project #: 1802
Project Funding: CSET, Washington Traffic Safety Commission, and University of Washington
Start Date: July 2018
End Date: September 2019
Dr. Yinhai Wang is a professor in transportation engineering and the founding director of the Smart Transportation Applications and Research Laboratory (STAR Lab) at the University of Washington (UW). He also serves as director for Pacific Northwest Transportation Consortium (PacTrans), USDOT University Transportation Center for Federal Region 10 and visiting chair for the Traffic Information and Control Department at Harbin Institute of Technology. He has a Ph.D. in transportation engineering from the University of Tokyo (1998), a master's degree in computer science from the UW, and another master’s degree in construction management (1991) and a bachelor’s degree in civil engineering (1989) from Tsinghua University in China. Dr. Wang’s active research fields include traffic sensing, e-science of transportation, big-data analytics, traffic operations and simulation, smart urban mobility, transportation safety, etc. He has published over 120 peer reviewed journal articles and delivered more than 130 invited talks and nearly 220 other academic presentations.
Dr. Wang serves as a member of the Transportation Information Systems and Technology Committee and Highway Capacity and Quality of Service Committee of the Transportation Research Board (TRB). He is currently a member of the steering committee for the IEEE Smart Cities and an elected governor for the American Society of Civil Engineers (ASCE) Transportation and Development Institute (T&DI), scheduled to serve as president of ASCE T&DI in 2018. He is a co-chair of the Third IEEE International Smart Cities Conference to be held in Wuxi China in 2017 and the ASCE International Conference on Transportation and Development to be held in Indianapolis in 2018. He was a principal investigator for 75 important research projects with a total amount of funding over 51 million dollars. Additionally, Dr. Wang is associate editor for three journals: Journal of ITS, Journal of Computing in Civil Engineering, and Journal of Transportation Engineering. He was the winner of the ASCE Journal of Transportation Engineering Best Paper Award for 2003.
Rural, Isolated, Tribal, or Indigenous (RITI) communities across the United States are disadvantaged from a transportation safety perspective. Particular concern is focusing on rural road safety. Official data from Federal Highway Administration (FHWA) shows that, in 2012, 54 percent of all fatalities occurred on rural roads while only 19 percent of the US population lived in rural communities. The fatality rate was 2.4 times higher in rural areas than in urban areas (1.81 and 0.74, respectively). Since RITI communities often do not have the capability and resources to sufficiently solve roadway safety problems, several challenges are encountered for addressing transportation safety issues in RITI communities, including: (1) Crashes are often randomly distributed on local and rural roads in RITI areas; (2) Strategies to address safety issues are diverse for different RITI communities and draw from several safety areas. As a result, there is a critical need to realize equitably-augmented safety solutions that address the needs of these underserved and underinvested RITI communities. A survey made by National Association of Counties (NACo) in 2009 revealed that only 42 percent of counties surveyed maintained a database that tracks the number and types of crashes on their rural roads and slightly under half of the respondents have conducted a road safety audit. Till recently, existing databases are still incomplete for most of the RITI communities. It is necessary to develop a complete safety database system for RITI communities. The aim of this research is to conduct a two-year project to build up an effective safety database platform to facilitate data partitioning and visualization for each RITI community in the first year (Phase I) and develop a data-driven safety assessment framework based on the safety database platform to enable effective roadway safety management for RITI communities in Washington State in the second year (Phase II).
In our Year 1 CSET project, a baseline data platform was developed by integrating the collected safety related data for the RITI communities in Washington State. However, the developed baseline data only integrates general rural roadway safety data without classifying the data into groups for each RITI community. Thus, a data partitioning and visualization-based safety database platform is critically needed for realizing effective roadway safety management for RITI communities. The safety assessment framework is the cornerstone of the roadway safety management system. Due to different RITI communities have different safety data sources, a general safety assessment method may not be adapted to all the RITI communities. To provide context sensitive solutions, the roadway safety cultural factors such as local driving habit and training level will be considered. As a result, this project is going to build up a complete safety database with classified data for each RITI community and develop a data-driven safety assessment framework based on the safety database platform to enable an effective roadway safety management system for RITI communities which can mitigate rural crash severities and risks.