CSET Project Reports

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  DUST PALLIATIVE MEAN PARTICLE RESIDENCE TIME CALCULATOR

  Jonathan Metzgar

  Previous research efforts at UAF have established that dust palliative performance may be compared using a calculation called the mean particle residence time (tau, or MPRT). The MPRT value is computed using linear regression techniques to determine the time when the dust palliative loses its effectiveness. A technician tests the palliative using a dustfall column and a nephelometer to measure the concentration of PM10 over time. The technician needs to manually process this raw data with an Excel spreadsheet making dust palliative MPRT reports time-consuming and prone to error. Finally, the certifying technician prints and files the report for future reference which limits future dissemination. We developed a web-based calculator, called UAFDUST, to automate the process of producing the MPRT report. UAFDUST combines a web app front end using Google's Angular library with a PHP and SQL database backend. This database enables a laboratory to record metadata about the dust palliative including the dustfall column testing date and technician, certification date, and certifying technician. The app calculates the MPRT and produces accompanying linear regression plots. The UAFDUST app stores dust palliative MPRT tests in a public database and trained laboratory technicians may contribute new data.

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  Effects of Reading Text While Driving: A Driving Simulator Study

  Panos Prevedouros, M. Mintu Miah, and Eftihia Nathanail

  Although 47 US states make the use of a mobile phone while driving illegal, many people use their phone for texting and other tasks while driving. This research project summarized the large literature on distracted driving and compared major outcomes with those of our study. We focused on distraction due to reading text because this activity is most common. For this research project, we collected simulator observations of 203 professional taxi drivers (175 male, and 28 female) working at the same Honolulu taxi company, using the mid-range driving simulator VS500M by Virage. After a familiarization period, drivers were asked to read realistic text content relating to passenger pick up displayed on a 7-inch tablet affixed to the dashboard. The experimental scenario was simulated on a two-lane rural highway having a speed limit of 60 mph and medium traffic. Drivers needed to follow the lead vehicle under regular and text-reading conditions. The large sample size of this study provided a strong statistical base for driving distraction investigation on a driving simulator. The comparison between regular and text-reading conditions revealed that the drivers significantly increased their headway (20.7%), lane deviations (354%), total time of driving blind (352%), maximum duration of driving blind (87.6% per glance), driving blind incidents (170%), driving blind distance (337%) and significantly decreased lane change frequency (35.1%). There was no significant effect on braking aggressiveness while reading text. The outcomes indicate that driving performance degrades significantly by reading text while driving. Additional analysis revealed that important predictors for maximum driving blind time changes are sociodemographic characteristics, such as age and race, and past behavior attributes.

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  Transportation Equity for RITI Communities in Autonomous and Connected Vehicle Environment: Opportunities and Barriers

  Sameh Sorour, Ahmed Abdel-Rahim, and Skye Swoboda-Colberg

  This report summarizes the results of a study conducted to document the safety and mobility needs of Rural, Isolated, Tribal, or Indigenous (RITI) communities and to identify autonomous and connected vehicle technology that have the potential of addressing these needs. A review of the administrative structure for the five Native American Tribes in Idaho revealed that none of the tribes has a department dedicated to transportation services. Two of the five tribes, however, have a department dedicated to Information Technology (IT) services. Based on the results of focus group discussions and the follow up in-depth interviews, some of the major transportation safety and mobility problems and need areas for RITI communities include: safety of school-age children walking to school, lack of safety pedestrians facilities (sidewalks) in the community, inefficient emergency response services, issues with paratransit scheduling and reliability of service, roadway maintenance issues, aggressive driving in community roadways, struggle of low-income families with no car ownership, snow removal and clean up especially for local roads, and not having enough driver education programs available for the community. In terms of major barriers to Autonomous and Connected Vehicle implementation in RITI communities, the interviewed citizens believe that lack of communication infrastructures, cost of smart phone use, difficulties to use internet and/or smart phones, lack of electrical power coverage in some roadway areas, privacy and safety issues in car sharing operations, cost of expanding communication and power networks, and the lack of human resources in the community to support these technologies are some of the major barriers to the wide-spread implementation of such advanced technology.

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  Reaching Out to Tribal Communities: Lessons Learned and Approaches to Consider

  Rula Awwad-Rafferty, Kevin Chang, and Helen Brown

  When transportation safety decision-making is desired, the involvement and engagement with a community is essential. A streamlined delivery of a project or program is more likely to occur when active dialogue and an exchange of ideas occurs in advance and occurs frequently. This is particularly important in tribal communities, who value sustained relationships and represent the focus population of this study. The research team, on six separate occasions, met with local and regional tribal leaders to explore and discuss transportation safety needs within and outside tribal communities, as well as discern the recommended approaches to foster ongoing dialogue about these needs. In all cases these discussions closely correlated with existing research studies or activities; transportation safety and equity is not seen as separate from other tribal foci and community needs. Specific recommendations to consider, in no particular order, included the following: invest respectfully enough time for people to talk; tribes think long-term and consider the impact of any decision from a long-term viewpoint so an iterative process and re-sharing of ideas is critical; the power of decision is in the hands of the tribe and its members; do not lump tribes together as each tribe is sovereign and unique and every community should be expected to think differently; all tribes are unique as is the environmental and social context; to disseminate information widely and iteratively, do so when there is a large group or event; be sure to understand the Tribal governance, decision making, and organizational structure; know who is the tribal Chairman or Chairwoman; and develop an emic and etic understanding of the community.

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  Enabling Data-Driven Transportation Safety Improvements in Rural Alaska

  F. Lawrence Bennett, Jonathan B. Metzgar, and Robert A. Perkins

  Safety improvements require funding. A clear need must be demonstrated to secure funding. For transportation safety, data, especially data about past crashes, is the usual method of demonstrating need. However, in rural locations, such data is often not available, or is not in a form amenable to use in funding applications. This research aids rural entities, often federally recognized tribes and small villages acquire data needed for funding applications. Two aspects of work product are the development of a traffic counting application for an iPad or similar device, and a review of the data requirements of the major transportation funding agencies. The traffic-counting app, UAF Traffic, demonstrated its ability to count traffic and turning movements for cars and trucks, as well as ATVs, snow machines, pedestrians, bicycles, and dog sleds. The review of the major agencies demonstrated that all the likely funders would accept qualitative data and Road Safety Audits. However, quantitative data, if it was available, was helpful.

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  2007–2016 FATAL TRAFFIC CRASHES IN ALASKA, HAWAII, IDAHO, AND WASHINGTON AND CHARACTERISTICS OF TRAFFIC FATALITIES INVOLVING HAWAIIANS AND CSET MINORITIES

  Panos Prevedouros, Kishor Bhatta, and M. Mintu Miah

  Data for this comparative study were collected from the Fatality Analysis and Reporting System (FARS) for the years 2007 to 2016 for the states of Alaska, Hawaii, Idaho, and Washington. The rates of roadway fatalities, especially those of American Indians (which include Aleuts and Eskimos), Guamanians, Samoans, and Native Hawaiians (which include part-Hawaiians) were the focus of the study; they are referred to as “CSET Minorities” in this report; all other races are referred to as “All Others.” Three main contributing factors for fatal crashes—alcohol use, speeding, and non-usage of restraint—were analyzed for each population group. CSET states are lagging behind many countries in terms of traffic safety. Significant differences in the involvement of alcohol, speeding, and non-usage of restraint were indicated between CSET Minority fatalities and All Others. For all types of crashes examined, CSET Minorities exhibited statistically significant differences, nearly all of them being higher or worse than All Others, except for motorcycle crashes. In Hawaii, the proportion of Hawaiians in the population is steady at approximately 21%, but their proportion in FARS database is at 28% and rising. Aggregate data analysis of traffic fatalities focused on three rural, indigenous, tribal, and isolated (RITI) communities in Hawaii, the entire Big Island of Hawaii, and the rural communities of Waianae and Waimanalo on the island of Oahu. All three locations are known for their relatively large number of Hawaiians and part-Hawaiians. The percentage of Hawaiians in traffic fatalities was 32% on the Big Island, 50% in Waianae, and 78% in Waimanalo.

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  PROMOTING CSET OUTREACH ACTIVITIES THROUGH SAFETY DATA MANAGEMENT AND ANALYSIS IN RITI COMMUNITIES

  Yinhai Wang, Ying Jiang, Christopher Gottsacker, and Ziqiang Zeng

  Traffic crashes are one of the leading causes of death among all people in the United States, but the rates among American Indian and Alaska Native (AIAN) populations are significantly higher than other groups. In fact, rural areas in general are disadvantaged from a traffic safety perspective due to the lack of funding and challenges in safety improvement decisions. This may contribute to the much higher fatality rate on rural roadways than on urban roadways. Additionally, there is a known issue of underreporting of fatal crashes of tribal members. Thus, an increased focus on rural, isolated, tribal, and indigenous (RITI) community traffic safety is necessary in order to progress towards zero fatalities. The need for quality data is recognized, and even included in many tribal transportation plans, but implementation and collection of the data varies. Quality data enables better safety analysis and enables greater support for traffic safety improvements. An easy-to-use and multisource database would enable tribes throughout the state and other rural communities to more readily manage data and apply for improvement funding. In order to reach this point, it is necessary to have agreements with tribes on crash data collection and usage, and understand local customs, needs, and current practices. This research aimed to form trusting and lasting relationships with tribal leaders in Washington State in order to facilitate crash database management and traffic safety analysis in their communities. The outreach activities included meetings with local tribal leaders, interviews, and attendance and presentations at tribal conferences. Ultimately a formal research agreement was signed with one tribe in Washington State granting access to the fatal and serious injury crash data they had collected.

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  Developing a Data-Driven Safety Assessment Framework for RITI Communities in Washington State

  Yinhai Wang, Wei Sun, Hao Yang, Christopher Gottsacker, Sam Ricord, and Shuyi Yin

  In the history of this country, rural, isolated, indigenous, and tribal (RITI) communities were commonly overlooked with regards to social infrastructure and support. This issue is evident in the development of the transportation networks of these areas and the distinct lack of road safety in these types of communities. RITI communities carry a significantly disproportionate amount of traffic collisions and fatalities compared to urban areas. In order to improve the traffic safety conditions of the RITI communities in Washington State, it is necessary to build a traffic safety management system. A baseline data platform was developed by integrating the collected safety related data for the RITI communities in Washington State in the Year 1 Center for Safety Equity in Transportation (CSET) project. Besides the baseline data, the traffic safety management also requires the safety assessment framework, which is the corner stone of the traffic safety management system. Therefore, this project aims to develop a data-driven safety assessment framework to enable an effective roadway safety management system and improve the traffic safety conditions for RITI communities. The framework is based on an effective and efficient database management system for traffic and crash-related data of the RITI communities. In addition, in order to assist transportation agencies in practices such as the identification of high-risk roadway segments, the developed database management system has powerful visualization functions. Besides the database management and visualization platform, this project also develops roadway safety performance indices and traffic safety assessment methods in the safety assessment framework. This project also provides guidance on how to utilize these safety performance indices and results of safety assessment methods for visualization and analysis.

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  Develop a Regional Multi-Source Database System for Safety Data Management and Analysis in RITI Communities in Washington State

  Yinhai Wang, Ziqiang Zeng, Christopher Gottsacker, and Hao (Frank) Yang

  Rural, Isolated, Tribal, and Indigenous (RITI) communities across the United States are disadvantaged from a transportation safety perspective. Particular concern is focusing on rural road safety. 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 distributed along roads in RITI areas without known patterns; (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. To address this gap, this project aims to develop a regional multi-source database system for traffic safety data management and analysis of RITI communities in Washington State. The existing crash data sources in RITI communities in Washington was identified and documented. The crash data on rural routes was extracted from the raw data from Washington State Department of Transportation and integrated into the multi-source database system, including traffic flow characteristics, crash attributes and contribution factors, crash-related trauma data and medical records, weather conditions, etc. The Colville tribe also provided the crash data in their tribal communities under a confidentiality agreement. A multi-source database fusion and integration system architecture was designed. Microsoft SQL Server 2012 was used to implement the database and manage the data. A six-step data quality control method was employed to clean the data by wiping out the outliers from spatial and temporal aspects. The tribal crash data was made accessible to authorized users so they can download the datasets by using password, while the WSDOT crash data was set to be public for all the users. A safety analysis module was developed for visualizing the data in the regional multi-source database system in RITI communities. The data visualization platform is developed based on the Vaadin Framework. The users can interact with the interface for data analysis. A safety performance index and a potential safety improvement index were also developed. By combining the two indexes, one can easily identify crash hotspots and the key influencing factors to consider in an improvement package.

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  Developing an Interactive Baseline Data Platform for Visualizing and Analyzing Rural Crash Characteristics in RITI Communities

  Guohui Zhang, Panos Prevedouros, David T. Ma, Hao Yu, Zhenning Li, and Runze Yuan

  This project focused on developing an interactive baseline crash data platform, termed as Rural Crash Visualization Tool System (RCVTS), to visualize and analyze rural crash characteristics in RITI communities. More than 975 thousand crash records were collected in the state of Alaska, Idaho, and Washington, from 2010 to 2016. Data fusion is applied to unify the collected data. In the proposed RCVTS platform, three main functions are defined: crash data visualization, data analysis, and data retrieval. Crash data visualization includes an on-street map based crash location tool and a graphic query tool. Data analysis involves a number of visualization approaches, including static charts— i.e., the scatter chart—the line chart, the area chart, the bar chart, and interactive graph— i.e., the sunburst chart. Users are allowed to generate customized analytical graphs by specifying the parameters and scale. The three types of authorized users are defined to download crash information in the data retrieval section following corresponding limitations. The proposed RCVTS was illustrated using a sample case with crash records of the State of Alaska. It showed that the proposed RCVTS functions well. Recommendations on future research are provided as well.