Sub-communities within this community

Recent Submissions

  • Mini-RWIS Pilot Project

    Randall, Kevin; Connor, Billy; Weiss, Richard; Cormier, Elycia (2023-05)
    Campbell Scientific in partnership with ADOT&PF successfully demonstrated the use of a low-power, low-cost, small-footprint, mini-RWIS concept in Alaska that could reliably deliver atmospheric and road temperature data as well as camera images year-round. The project originally was conceived to demonstrate eight mini-RWIS stations. ADOT&PF personnel performed site selection. Of the eight mini-RWIS initially conceived for this demonstration project seven mini-RWIS stations were successfully deployed at selected sites in DOT Northern and South-Central regions. The eighth station was incorporated into a University of Alaska project at Atigun Pass that was designed to provide data, forecasting and warning for avalanche risks on the Dalton Highway. The system utilized multiple cameras, blowing snow sensors, as well as other atmospheric sensors on a solar panel/battery system. This station at Atigun Pass should be considered a step above the mini-RWIS concept and is, by far, the northern-most advanced RWIS station deployed in the state of Alaska providing data in an area where the climate conditions are extreme. As such, the station requirements were designed to withstand, high winds, temperatures below -40oF, the potential for rime ice, two months without sunlight, and lack of cellular connectivity. Consequently, the location challenged the equipment. Campbell Scientific initially shipped all equipment to Alaska in the spring of 2019 to be cold chamber tested at the University of Alaska Fairbanks (UAF), then installed in the field prior to the winter season. Cold chamber testing was successfully accomplished, however, due to a variety of delays these stations were not installed prior to the 2019/2020 winter season. In March of 2020, the global COVID-19 pandemic prevented Campbell Scientific personnel from traveling and installing stations during the summer of 2020. Instead, Campbell Scientific reached out to a long-time user of CS equipment, Michael Lilly of Geo-Watersheds Scientific (GWS), in Fairbanks, AK. Michael and his team have decades of experience in the design of low-power data acquisition systems and networks (including power system design, programming, installation, and maintenance) with specialization in remote hydrological and meteorological monitoring stations. The GWS team set out to understand the needs of the project and immediately became fully invested. As a result, the mini-RWIS system design went through a modification process per the recommendations of the GWS team. Campbell Scientific work with GWS to affect the following changes to the mini-RWIS: • Expansion of battery bank considering the long Alaskan winters • Addition of CH200 regulator for the purpose of gathering critical information on the performance of the power system. • Addition of a fiberglass enclosure for the purpose of protecting cables from wildlife during winter months when food sources are depleted. • Reprogramming of dataloggers to meet project goals • Configuration of CCFC camera for optimization of power requirements. GWS was contracted by CSI with approval from ADOT&PF (Contract # 2520H016 Amendment #1) to utilize GWS’ services for installation of two stations during the winter of 2020/2021. ADOT&PF personnel also installed one station during the winter of 2020/2021. Campbell Scientific personnel traveled to Alaska for two weeks during September of 2021 to install the remaining four mini-RWIS stations prior to the 2021/2022 winter season. Maintenance was performed on the three previously installed stations during that trip. Project update meetings were held between CSI, ADOT&PF, UAF, and GWS prior to the 2021/2022 winter season with additional performance review meetings in January 2022 to discuss station performance. CSI personnel additionally traveled to Alaska during July 2022 to visit project stakeholders in Anchorage and Fairbanks and to visit each of the seven mini-RWIS stations to perform general maintenance. In total seven mini-RWIS stations were installed between the northern and central regions in Alaska. The equipment (datalogger, sensors, power system, enclosures, etc.) from the eighth mini-RWIS station, with the support of ADOT&PF, was repurposed for a project being done by UAF personnel with the support of GWS. The CR300 datalogger (embedded in the mini-RWIS stations) was upgraded to the higher capacity CR1000X due to the need for additional sensor inputs, and additional sensors were used including two blowing snow sensors and an additional wind speed and direction sensor, an extreme-cold temperature sensor and snow depth, and snow temperature profile sensors. The seven standard mini-RWIS stations were assessed based on the performance of the atmospheric sensor data (including wind speed and direction, air temperature and relative humidity, and road surface temperature), reliable delivery of camera images, power performance, and cellular communication performance. The performance of the advanced winter-hazards RWIS was performed by the Atigun Pass project. Throughout the study period atmospheric data proved to be within an acceptable and expected range, was reliable and was recorded without failures. Camera images were reliable and delivered in a timely manner over the cellular network. The power performance proved to be very robust and more than sufficient for the power needs of the mini-RWIS stations. Cellular communications proved reliable. Several minor instances of loss of cellular connectivity were encountered but cellular connection was regained quickly and self-corrected.
  • Drone-based Computer Vision-Enabled Vehicle Dynamic Mobility and Safety Performance Monitoring

    Zhang, Guohui; Yuan, Runze; Prevedouros, Panos; Ma, Tianwei (2023-01-30)
    This report documents the research activities to develop a drone-based computer vision-enabled vehicle dynamic safety performance monitoring in Rural, Isolated, Tribal, or Indigenous (RITI) communities. The acquisition of traffic system information, especially the vehicle speed and trajectory information, is of great significance to the study of the characteristics and management of the traffic system in RITI communities. The traditional method of relying on video analysis to obtain vehicle number and trajectory information has its application scenarios, but the common video source is often a camera fixed on a roadside device. In the videos obtained in this way, vehicles are likely to occlude each other, which seriously affects the accuracy of vehicle detection and the estimation of speed. Although there are methods to obtain high-view road video by means of aircraft and satellites, the corresponding cost will be high. Therefore, considering that drones can obtain high-definition video at a higher viewing angle, and the cost is relatively low, we decided to use drones to obtain road videos to complete vehicle detection. In order to overcome the shortcomings of traditional object detection methods when facing a large number of targets and complex scenes of RITI communities, our proposed method uses convolutional neural network (CNN) technology. We modified the YOLO v3 network structure and used a vehicle data set captured by drones for transfer learning, and finally trained a network that can detect and classify vehicles in videos captured by drones. A self-calibrated road boundary extraction method based on image sequences was used to extract road boundaries and filter vehicles to improve the detection accuracy of cars on the road. Using the results of neural network detection as input, we use video-based object tracking to complete the extraction of vehicle trajectory information for traffic safety improvements. Finally, the number of vehicles, speed and trajectory information of vehicles were calculated, and the average speed and density of the traffic flow were estimated on this basis. By analyzing the acquiesced data, we can estimate the traffic condition of the monitored area to predict possible crashes on the highways.

    Ban, Xuegang (Jeff); Abramson, Daniel; Zhang, Yiran; Lukins, Sarah; Goodrich, Kevin; Mirante, Andrea; Lambert, Rachel; Yankey, Mykala (2023-02)
    Transportation and traffic safety is a primary concern within Rural, Isolated, Tribal and Indigenous (RITI) communities in Washington State. Emerging technologies such as connected and autonomous vehicles, sensors and drones have been tested and developed to improve traffic safety, but these advances have largely been limited to urban areas. This project identified opportunities and challenges of adopting drone technologies in RITI communities, and explored context-sensitive applications to traffic safety and related goals. In three phases, the team conducted community workshops, online surveys and other outreach activities with state and county agencies responsible for emergency management and crisis response in coastal Tribal and non-tribal communities; a planning studio and Comprehensive Plan Update for the City of Westport and its surrounding South Beach community straddling two rural counties and including the Shoalwater Bay Indian Tribe; and a pilot educational program with the School District that serves it. To be effective in rural contexts, adoption of drone technology depends on a broadening of local skill development and needs to target diverse community goals. In short, it needs to be broadly embedded in the community. Taking this sociotechnical approach, we focused on long-term workforce development and designed and implemented an after-school program (October 2021 – June 2022) for Ocosta Junior High School students. The course taught students how to assemble and pilot drones and apply them to a variety of practical needs including public works inspection, search and rescue, and environmental monitoring of coastal flooding.
  • Development of an Acoustic Method to Collect Studded Tire Traffic Data

    Chang, Kevin; Alhasyah, Meeloud (2023-02)
    Travel during winter months remains particularly problematic in the Pacific Northwest due to the regular occurrence of inclement weather in the form of snow and ice during freezing and sub-freezing conditions. For travelers and commuters alike, vehicle traction in the form of studded tires serves to provide an added level of driving confidence when weather conditions deteriorate. However, recurring studded tire usage causes damage to the roadway infrastructure in the form of surface wear and rutting over time. Left unattended, this damage contributes to challenging and potentially dangerous driving conditions in the form of standing water and the increased potential for hydroplaning. Currently, an efficient and automated method to collect site-specific studded tire traffic volumes is lacking. While studded tire usage can be locally estimated based on manual roadway traffic counts, parking lot counts, or household surveys, the lack of real-world traffic volumes prevents the fine-tuning of roadway deterioration models that measure performance and estimate infrastructure life. This project tested the use of off-the-shelf sound meters to determine if an acoustic method could be developed to measure studded tire volumes. Based on the results, a prediction model was developed to allow for data-driven solutions that will benefit local transportation officials, planners, and engineers responsible for managing highways and roadways.
  • Assessing the Transportation Adaptation Options to Sea Level Rise for Safety Enhancement in RITI Communities through a Structured Decision-Making Framework

    Shen, Suwan; Shim, Dayea (2023-01-18)
    Through a structured decision-making framework, this study aims to better understand the key factors influencing transportation adaptation planning in practice. Qualitative, semi-structured, in-depth interviews with various stakeholders were conducted to identify the main concerns, challenges, objectives, tradeoffs, and evaluation variables in transportation adaptation planning. Stakeholders were identified through preliminary interviews with transportation planning experts from the metropolitan planning organization using typical case and snowball sampling methods. Key aspects related to the major concerns, objectives, priorities, adaptation plan evaluations, implementation challenges, and potential conflicts and tradeoffs are identified. Major barriers to adaptation plan development and implementation include lack of resources, competing with more urgent needs, conflicts with other planning objectives, lack of holistic view, working in silos, mismatched and outdated information, uncertainty in future scenarios, and action inertia. To overcome these challenges, we propose 1) more efforts to understand community values, develop strategic goals, and identify their priorities in order to balance the tradeoffs 2) collaboration with other sectors to develop a holistic view of resilience and strategic plans that achieve multiple planning goals 3) collaborate with diverse stakeholders to reduce spatial and temporal information mismatches and to create adaptive plans that can accommodate multiple scenarios with uncertainty 4) conduct community outreach and stakeholder engagement from the beginning to build support, consolidate resources, and eliminate social inertia for plan implementation.

    Zhang, Guohui; Yang, Hanyi; Yu, Hao; Li, Zhenning; Zou, Rong; Yuan, Runze; Ma, Tianwei (2022-09)
    This report documents the research activities to investigate the traffic crashes in Rural, Isolated, Tribal, or Indigenous (RITI) communities involving considerable incapacitating injuries and fatalities. The traffic crashes occurring in RITI communities, are different from urban traffic crashes, and are related more to the features like speeding, low application of safety devices (for instance, seatbelt), adverse weather conditions and lacking maintenance and repairs for road conditions, and inferior lighting conditions. Thus, it is necessary to study the properties and attributes of traffic crashes at the RITI area using data analysis methods, such as statistical methods, and data-driven methods. This project is trying to analyze the rural crash injury and fatality patterns caused by changing climates in RITI communities based on enhanced data analysis using latest mathematical method. The mixed logit model to examine the risk factors in determining driver injury severity in four crash configurations in two-vehicle rear-end crashes on state roads based on seven-years of data from the Washington State Department of Transportation. The differences between the MLM and the LCM are investigated for exploring the relationships between driver injury severity in the rain-related rural single-vehicle crash and its corresponding risk factors. Moreover, this project develops a latent class mixed logit model with temporal indicators to investigate highway single-vehicle crashes and the effects of significant contributing factors to driver injury severity. The results of this research will be beneficial to transportation agencies to propose effective methods to improve rural crash severities under special climate and weather conditions and minimize the rural crash risks and severities.
  • Improved Permafrost Protection using Air Convection and Ventilated Shoulder Cooling Systems - Final Project Report

    Goering, Douglas J. (2022-08)
    This report focuses on the effectiveness of air convection embankments (ACE) and ventilated shoulder (VS) cooling systems designed to cool foundation soils and preserve permafrost beneath roadway embankments. The three main sections of the report include a literature review, an analysis of field data from Thompson Drive and the Alaska Highway Dot Lake test site, and a discussion of techniques for modeling ACE and VS structures.

    Vasudevan, Vinod; Kapourchali, Mohammad Heidari (2022-03-30)
    Rural intersections are high-risk locations for road users. Particularly, during the nighttime, lower traffic volumes make it difficult for drivers to discern an intersection despite traffic signs. The lack of alertness may lead to severe crashes. An effective way to reduce the likelihood of crashes at isolated intersections is to warn road users of the intersection in advance. A smart-lighting system can detect approaching vehicles using sensors and transmit this information to a receiver to illuminate the intersection. By deploying a demand-responsive light, it is expected that the system will provide adequate warning to road users, both motorized and non-motorized. This report documents the development and deployment of a smart-lighting system at the University of Alaska Anchorage (UAA).
  • Improving Safety for RITI Communities in Idaho: Documenting Crash Rates and Possible Intervention Measures

    Lowry, Michael; Swoboda-Colberg, Skye; Prescott, Logan; Abdel-Rahim, Ahmed (2022-03-23)
    This report describes a new set of Geographic Information System (GIS) tools that we created to conduct safety analyses. These new GIS tools can be used by state DOTs and transportation agencies to document crash rates and prioritize safety improvement projects. The tools perform Network Segment Screening, the first step in the Roadway Safety Management Process (RSMP) outlined in the Highway Safety Manual (HSM). After developing these new tools, we conducted two case studies to demonstrate how they can be used. The first case study was for screening intersections. Our analysis included all intersections on the Idaho State Highway System. In practice, the analysis would likely be done only for a subset of intersections, such as only for signalized intersections on urban arterials. We chose all intersections for illustration purposes. The result was a ranking of intersections that would most likely benefit from safety improvement efforts. We applied three performance measures to rank the intersections: Crash Frequency, Crash Rate, and Equivalent Cost. The second case study was for screening roadway segments. Again, the entire Idaho State Highway System was included for illustration. The HSM describes two key methods for screening roadway segments: Simple Ranking and Sliding Window. Both methods are available in the new tools. This case study demonstrates the advantage of the Sliding Window, which would be impractical to accomplish on a large scale without the assistance of our new GIS tools. The final part of the work presented in this report is a synthesis to identify and document possible measures to reduce crashes for RITI communities in Idaho and throughout the northwest region.
  • Evaluation of Delivery Service in Rural Areas with CAV

    Prevedouros, Panos; Alghamdi, Abdulrahman (2022-03-15)
    Urban areas have been experiencing automated delivery technology for several servings of food or a few bags of groceries, with automated (robotic) mini vehicles. The benefits of such automated delivery may be much more significant for rural areas with long distances due to the large potential savings in travel time, travel cost, and crash risk. Compared to urban areas, rural areas have older and more disabled residents, longer distances, higher traffic fatality rates, and high ownership of less fuel-efficient vehicles such as pickup trucks. An evaluation of connected autonomous vehicle (CAV) delivery service in rural areas was conducted. A detailed methodology was developed and applied to two case studies: One for deliveries between Hilo and Volcano Village in Hawaii as a case of deliveries over a moderate distance (~50-mile roundtrip) in a high-energy-cost environment, and another for deliveries between Spokane and Sprague in Washington State as a case of deliveries over a longer distance (~80-mile roundtrip) in a low-energy-cost environment. The delivery vehicles were based on the same compact van: A person-driven gasoline-powered van, a person-driven electric-powered van, and a CAV electric-powered van. The case study results suggest that the CAV van can be a viable option for implementing a delivery business for rural areas based on the evaluation results that accounted for a large number of location-specific costs and benefits and the number of orders served per trip.
  • Barriers and Opportunities for Using Rail-Trails for Safe Travel in Rural, Isolated, and Tribal Communities

    Lowry, Michael; Chang, Kevin (2021-11)
    This project explored barriers and opportunities for more effectively using rail-trails for safe travel in rural, isolated, tribal, and indigenous communities. We investigated using crowdsourced data from a fitness app to estimate bicycle volumes on trails. For 10 locations this new method produced suitable results, but for 19 locations the method was not satisfactory. Future research could identify situations in which this new method is feasible. We also created a new mapping tool to get demographic data surrounding locations where new rail-trails could be built. We identified 8,616 miles of potential rail-trail in the Pacific Northwest and explored the surrounding demographics for 12 locations in rural communities in Idaho, Oregon, and Washington. We conducted two separate surveys to solicit community member opinions and usage habits of the Trail of the Coeur d’Alenes.
  • Developing a Data-Driven Safety Assessment Framework for RITI Communities in Washington State

    Wang, Yinhai; Sun, Wei; Ricord, Sam; de Souza, Cesar Maia; Yin, Shuyi; Tsai, Meng-Ju (2021-09-10)
    The roadway safety of the Rural, Isolated, Tribal, or Indigenous (RITI) communities has become an important social issue in the United States. Official data from the 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. Under the serious circumstances, this research aims to help the RITI communities to improve their roadway safety through the development of a roadway safety management system. Generally, a roadway safety management system includes two critical components, the baseline data platform and safety assessment framework. In our Year 1 and Year 2 CSET projects, a baseline data platform was developed by integrating the safety related data collected from the RITI communities in Washington State. This platform is capable of visualizing the accident records on the map. The Year 3 project further developed the safety data platform by developing crash data analysis and visualization functions. In addition, various roadway safety assessment methods had been developed to provide safety performance estimation, including historical accident data averages, predictions based on statistical and machine learning (ML) models, etc. Beside roadway safety assessment methods, this project investigated the safety countermeasures selection and recommendation methods for RITI communities. Specifically, the research team has reached out to RITI communities and established a formal research partnership with the Yakama Nation. The research team has conducted research on safety countermeasures analysis and recommendation for RITI communities.

    Pereira, Luana Carneiro; Prevedouros, Panos (2021-09-30)
    Dashboard cameras and sensors were installed in 233 taxi vans on Oahu, Hawaii which produced several hours of events classified as naturalistic driving data (NDD) in a period of seven months between fall 2019 and spring 2020. The study achieved its objectives to: (1) collect data from NDD events where driving maneuvers caused an acceleration of 0.5g or higher; (2) develop a database suitable for statistical analysis; (3) derive basic statistics for all variables; (4) investigate correlations between variables; and (5) further investigate correlations (which may represent causality effects) for the most frequent types of events, using stepwise linear regression models. The database included a total of 402 harsh events, of which were 398 near-crashes and four were crashes. Several variables such as road, environmental, driver and vehicle characteristics were coded for each event. The installation of Samsara by the CTL company proved to be a successful tool for coaching drivers, and for providing useful insights into traffic safety factors relating to near-miss events.
  • Extracting Rural Crash Injury and Fatality Patterns Due to Changing Climates in RITI Communities Based on Enhanced Data Analysis and Visualization Tools (Phase I)

    Zhang, Guohui; Prevedouros, Panos; Ma, David; Yu, Hao; Li, Zhenning; Yuan, Runze (2021-09)
    Traffic crashes cause considerable incapacitating injuries and losses in Rural, Isolated, Tribal, or Indigenous (RITI) communities. Compared to urban traffic crashes, those rural crashes, especially for those occurred in RITI communities, are heavily associated with factors such as speeding, low safety devices application (for instance, seatbelt), adverse weather conditions and lacking maintenance and repairers for road conditions, inferior lighting conditions, and so on. Therefore, there exists an urgent need to investigate the unique attributes associated with the RITI traffic crashes based on numerous approaches, such as statistical methods, and data-driven approaches. This project focused on extracting rural crash injury and fatality patterns due to changing climates in RITI communities based on enhanced data analysis and visualization tools. Three new interactive graphic tools were added to the Rural Crash Visualization Tool System (RCVTS), to enhance the visualization approach. A Bayesian vector auto-regression based data analysis approach was proposed to enable irregularly-spaced mixture-frequency traffic collision data interpretation with missing values. Moreover, a finite mixture random parameters model was formulated to explore driver injury severity patterns and causes in low visibility related single-vehicle crashes. The research findings are helpful for transportation agencies to develop cost-effective countermeasures to mitigate rural crash severities under extreme climate and weather conditions and minimize the rural crash risks and severities in the States of Alaska, Washington, Idaho, and Hawaii.
  • BUILDING CAPACITY FOR CLIMATE ADAPTATION Assessing the Vulnerability of Transportation Infrastructure to Sea Level Rise for Safety Enhancement in RITI Communities

    Shen, Suwan; Shim, Dayea (2021-09-01)
    Sea level rise (SLR) and more frequent extreme weather events are an emerging concern for transportation infrastructures in coastal areas. In particular, the livelihoods and transportation safety of vulnerable populations such as indigenous rural communities may be at higher risk to sea-level rise and exacerbated coastal flooding due to their heavy dependence on natural resources, settlements in relatively isolated fringe land, limited accessibility to services, and alternative economic activities, as well as lack of resources and tools for adaptation. Despite existing studies on sea-level rise’s impacts, there is a lack of understanding of how the impacts of tidal flooding and sea-level rise may be unevenly distributed both spatially and socially, and how vulnerable (e.g. rural, relatively isolated) communities have experienced such impacts and perceive future risks. Using survey data, this project helps to better understand the current experience and risk perception of different communities when facing sea-level rise and more frequent coastal flooding. It helps to understand different communities’ perceived travel challenges with coastal flooding, the social sensitivity to different types of challenges, and the priorities and concerns to access various types of resources with the projected sea-level rise. The findings could be used to develop adaptation strategies that improve communities’ safe access to highly valued resources and activities.

    Chang, Kevin; Hodgson, Cody (2021-07-05)
    While extensive procedures have been developed for the collection and dissemination of motor vehicle volumes and speeds, these same procedures cannot always be used to collect pedestrian data, given the comparably unpredictable behavior of pedestrians and their smaller physical size. There is significant value to developing lower cost, lower intrusion methods of collecting pedestrian travel data, and these collection efforts are needed at the local or “grass-roots” level. While previous studies have documented many different data collection methods, one newer option considers the use of drones. This study examined its feasibility to collect pedestrian data and used this technology as part of a school travel mode case study. Specific information with regard to the study methodology, permissions required, and final results are described in detail as part of this report. This study concluded that while purchasing and owning a drone requires relatively minimal investment, the initial steps required to operate a drone, along with processing time required to analyze the data collected, represent up-front barriers that may prevent widespread usage at this time. However, the use of drones and the opportunities that it presents in the long-term offer promising outcomes.
  • Investigation of Drone Applications to Improve Traffic Safety in RITI Communities

    Ban, Xuegang (Jeff); Abramson, Daniel; Zhang, Yiran; Cano-Calhoun, Cristina (2021-06-30)
    Transportation and traffic safety is a primary concern among the Rural, Isolated, Tribal, or Indigenous (RITI) communities in the U.S. Although emerging technologies (e.g., connected and autonomous vehicles, drones) have been developed and tested in addressing traffic safety issues, they are often not widely shared in RITI communities for various reasons. This research aims to explore, understand, and synthesize the opportunities and challenges of applying drone technologies to alleviate or resolve traffic safety and emergency related issues within RITI communities. The project team first sent out online surveys to communities on the outer Pacific coast of Washington State and selected the City of Westport as the study area based on the feedback. A pilot study using drones for mapping and sensing in Westport was then conducted, followed by two community meetings to explore potential drone applications. With the three outreach activities, it was found that the current need in the communities was education on drones, including training for remote pilot certification (drone license) and drone operations. Findings of this research will help guide the project team to set up specific drone-related programs in the Westport area in future research.

    Connor, Billy; Goering, Douglas J.; Kanevskiy, Mikhail; Trochim, Erin; Bjella, Kevin L.; McHattie, Robert L. (2020-12)
    This synthesis provides the practicing engineer with the basic knowledge required to build roadway and airports over permafrost terrain. Topic covered include an overview of permafrost, geotechnical investigations, slope stability, impacts of climate, and adaptation strategies during the design, construction and maintenance phases. The purpose of the synthesis is not to provide a comprehensive body of knowledge or to provide a complete how‐to manual. Rather the synthesis provides a working knowledge for those working in permafrost regions such that the practicing engineer will be able to work with subject matter experts to obtain the desired project outcomes.

    Metzgar, Jonathan (2020-12-31)
    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.
  • Transportation Equity for RITI Communities in Autonomous and Connected Vehicle Environment: Opportunities and Barriers

    Sorour, Sameh; Abdel-Rahim, Ahmed; Swoboda-Colberg, Skye (2020-08)
    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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