Institute of Northern Engineering: Recent submissions
Now showing items 1-20 of 604
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Crashes and Injuries on Rural Roads in Alaska - Toward a Better Understanding of Rural Safety Issues through Linked Data and Environmental Factors Task B: Environmental and Geometric Safety Factors of Rural CrashesAlaska experiences extreme weather and driving conditions compared to many other locations in the United States. For example, during summer, most traffic activity occurs in daylight, whereas in winter months, the majority of traffic activity occurs in the dark. Similarly, driving conditions change drastically across seasons. During winter, heavy snow and extremely cold temperatures provide challenges for drivers. These conditions lead to safety concerns such as noticeable changes in daylight hours, peak traffic activities in dark hours, and reduced friction values due to snow and ice. Another challenge is the sun's position above the horizon throughout the year, especially during the spring, summer, and fall seasons. The sun's low elevation angle for an extended period can be a primary concern for drivers since the bright sun glare can make it difficult to see one’s surroundings. During summer, long day hours and high activity levels may cause fatigue for drivers. Also, a higher number of tourists during summer may change the traffic conditions, posing higher safety risks in some regions. This report summarizes the findings of a study analyzing crash data, and combining external data to develop better understanding safety challenges in Alaska.
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Developing a Prototype of a Smart-lighting System for Isolated Rural Intersections: Phase 2Rural 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 to illuminate the intersection. In the first phase of this project, we developed a prototype of a demand-responsive light. This report documents the second phase of development and deployment of a smart-lighting system at the University of Alaska Anchorage (UAA). In this phase, we developed an installation-ready smart-light system that is ready for site deployment and analyzed its ability to generate and store power during winter.
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Crashes and Injuries on Rural Roads in Alaska - Toward a Better Understanding of Rural Safety Issues through Linked DataIn this study, motor-vehicle crash records (MVCD) are linked with hospital-based trauma data from the Alaska Trauma Registry (AKTR) using a probabilistic method using open-source record linkage software (FRIL) with the aim of developing a more comprehensive and accurate depiction of transportation-related injuries across the state. The study achieved a successful match for 66% of AKTR cases using demographic, temporal, and geographic identifiers. Injury classifications from both datasets were harmonized through a reclassification scheme to evaluate the accuracy and completeness of MVCD reporting relative to trauma data. Key findings reveal that while most records were either adequately classified or slightly overclassified, approximately 17% of MVCD records underestimated injury severity. Discrepancies were particularly evident in rural and remote communities. In addition, over 10% of linked records involving alcohol-related trauma were either not suspected of impairment or categorized as “Unknown” in MVCD, despite confirmation of intoxication in AKTR. This research demonstrates the viability and utility of data linkage to identify and address critical gaps in transportation safety records as well as support more effective injury prevention strategies, particularly in underserved and remote communities.
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Predicting Dust Palliative Effectiveness on Unpaved Roads Using a Simple Laboratory ProcedureThe ability of palliatives such as hygroscopic salts and synthetic fluids to reduce dust emissions from unpaved roads and other unpaved surfaces is well known. However, the effectiveness of different products used to control the loss of fine aggregate particles has largely been evaluated by observing the intensity of dust plumes produced behind moving vehicles. Currently, no standardized laboratory test exists for predicting dust palliative performance. Presented here is a laboratory methodology capable of predicting the effectiveness of palliatives applied to unpaved aggregate surfaces. The procedure evaluates the ability of palliatives to retain fine particles by measuring the total mass of PM10 (particulate matter less than 10 μm in size) present in material abraded from the treated aggregate surface. Total mass is determined by measuring PM10 concentrations in settling dust resulting from propelling a sample into a column. The test methodology is simple yet provides repeatable results. Moreover, the resolution in the test results is high enough to distinguish the performance between different palliatives applied at different application rates. Minor limitations are inherent in the methodology owing to the natural heterogeneity that exists in compacted aggregates. These limitations can be reduced with careful sample preparation.
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Investigating the Effect of Subsistence Opportunities on Motor Vehicle Crash Frequency in AlaskaThis study investigates the relationship between personal use subsistence activities (i.e., dipnetting) and motor vehicle crashes using the Chitina Subdistrict fishery as a case study. Using crash data from 2013 to 2021, salmon run counts, permit and harvest data, and traffic volume and speed records, the analysis reveals that crash rates, standard deviation in speeds, and percentage of vehicles traveling over the speed limit increase during peak subsistence periods, particularly on weekends and during late-night or early-morning hours. These trends suggest that the long travel distances and time constraints associated with reaching this subsistence activity may elicit from drivers risk-tolerant driving behaviors such as drowsy or high-speed driving. The findings underscore the need for targeted safety interventions during high-risk periods and recommend further research to more definitively link crash risk with subsistence-related travel.
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EVALUATING DRONE TECHNOLOGY TO IDENTIFY ICE CHANGES THAT CAN CAUSE ICE-ROAD HAZARDSIce roads in Alaska, a form that connects people during the winter months, enable the importing of critical goods and accessibility to medical services. These ice roads span 100 miles or more and are subject to spatial and temporal safety variability during the shoulder seasons and unseasonal warm events of above-freezing temperatures. In this work, we explore using an unmanned aircraft system (UAS) coupled with a ground penetrating radar (GPR) to inspect ice thickness safety and the presence of subsnow liquid overflow, common during winter. We compared our UAS-based GPR with ground-based GPR and nearby ice coring. We found the UAS-based GPR biased compared to the ice cores and the ground-based GPR. Nonetheless, when accounting for this bias, the UAS-based GPR had an RMSE of 5 cm for an ice thickness of 20 to 60 cm. More work is needed to understand the root cause of the UAS-based GPR for measuring ice thickness. The UAS-based GPR also effectively mapped subsnow liquid overflow by measuring the radar return amplitude, which is particularly strong when reflecting between the snow and water layers. Coupling UAS and GPR technology has great promise in conducting ice river safety assessments from a safe location. Still, more work must be done to understand the data’s bias.
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Impact of the COVID-19 Pandemic on Travel Mode Choices and Fatal Crash RatesThe COVID-19 pandemic caused unprecedented disruptions to human mobility and transportation systems worldwide, significantly altering travel behavior and mode choices. This study investigates these changes within the Pacific Northwest region of the United States, encompassing a mix of urban and rural contexts with diverse socio- demographic characteristics. Using survey data from 807 respondents, we analyze transportation patterns before and during the pandemic, focusing on shifts in mode shares and probabilities of switching travel modes. The analysis incorporates McNemar’s test, logistic regression, and latent class analysis (LCA) to evaluate the extent of these shifts and identify key influencing factors. The results reveal a substantial reduction in public transport usage, reflecting heightened concerns over health risks and limited operational capacity during the pandemic. In contrast, there was a notable increase in the use of private vehicles and active transportation modes, such as walking and cycling. Demographic variables, including age, income, employment status, and gender, played significant roles in shaping travel behavior, with younger and lower-income individuals exhibiting higher probabilities of mode change. The latent class analysis highlighted distinct behavioral clusters, indicating that travel behavior responses were not uniform across populations. A logistic regression model further underscored the importance of pre-pandemic travel habits, socio-economic conditions, and pandemic-related concerns in influencing mode choice decisions. Additionally, traffic safety outcomes showed notable variations, with overall crash rates decreasing during the lockdowns but fatality rates rising due to riskier driving behaviors, such as speeding on roads. Crash patterns varied across urban and rural areas, with urban crashes experiencing a slight decline in proportion, while rural crashes increased.
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School Travel Behaviors in Rural Communities: Pandemic-Related ImpactsThe global pandemic, which started around early 2020, significantly disrupted life for many families, and the trip to and from school was not immune to these disruptions. Parents and children alike made travel adjustments depending on their preferences with regard to personal health and safety, social distancing, and aversion to risk. Each school district and individual school also made decisions with regard to in-person or remote learning during this period of uncertainty. In this study, the research team examines how the pandemic affected school transportation for hundreds of families across the Pacific Northwest. An online survey was developed and administered with the help of Qualtrics, an experience management company. Over 600 responses were gathered to assess school transportation-related travel decisions. In addition to collecting demographic data about the respondents, the survey also asked about travel mode choices and characteristics of the trip to and from school. The collective results were then analyzed to determine which factors directly contributed to pandemic-related changes in travel behavior. The study concluded that the demographic factors of parent education level, household income, and age of child were all statistically significant variables that affected behavioral change, though the place of household residence, whether rural or urban, was determined to be an insignificant variable. Additionally, common travel assumptions associated with rural students, when compared with urban students, were confirmed. These factors included a greater reliance on a yellow school bus and lesser availability of critical infrastructure.
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Access, Equity, and Safety in Rural Road Development: Historical Evidence from the Dalton Highway, 1974-2024This study investigates the historical example of the construction of the Dalton Highway—the most significant new road built in Alaska since 1971—to analyze how historical changes in access (both new infrastructures and access policies) and equity (who decides, who benefits, who is seen as a stakeholder) have impacted safety, broadly defined, in rural, isolated, tribal, and indigenous (RITI) communities throughout Northern Alaska.
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Learning from the Permafrost & Infrastructure Symposium: merging science, engineering, and community-based knowledgeThe 2023 Permafrost & Infrastructure Symposium brought over 30 Arctic scientists, engineers, planners, and policymakers to Northern Alaska to see the impacts of permafrost thaw on roads and community infrastructure firsthand and to learn from those who live and work in the Arctic. For the symposium’s first half (July 28–August 1), participants gathered at the Barrow Arctic Research Center in Utqiaġvik for presentations, field trips and discussions focused on critical climate-related issues prioritized by local governments on the North Slope. They were joined in Utqiaġvik by key personnel from the North Slope Borough (NSB), regional housing authority, local utility cooperative, and the Alaska Native villages of Point Lay and Wainwright. Twenty participants flew to Deadhorse, Alaska, for the start of the second half of the symposium (August 1–5), which focused on transportation infrastructure and permafrost landscapes in Prudhoe Bay and south along the 416-mile Dalton Highway towards Fairbanks. A closing half-day session at the University of Alaska Fairbanks (UAF) Usibelli Engineering Learning and Innovation Building explored climate adaptation planning strategies with talks by the Commissioner of Alaska DOT&PF and the U.S. Department of Transportation’s Office of the Secretary. The symposium produced recommendations for the future.
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Safe Reinforcement Learning for Intersection Management in RITI Communities Under Rare Extreme EventsThe rapid advancement of artificial intelligence (AI) is reshaping the transportation sector, with applications spanning autonomous vehicles, driver injury prevention, and traffic management. Efficient traffic management, particularly through adaptive intersection control, holds significant potential for reducing congestion. This study explores the application of reinforcement learning (RL) to adaptive traffic signal control in rural, isolated, tribal, and indigenous (RITI) communities, which face unique challenges such as rare extreme weather events. Standard RL approaches struggle in these contexts due to limited exposure to these rare events. In our study, we first evaluate several mainstream RL algorithms and identified two most promising approaches. Then, we propose to use offline RL algorithms, which can train on existing datasets before interacting with the real environments. This provides a robust solution because (1) it is costly to deploy the algorithm and let the traffic network operate under suboptimal policies before the algorithm learns the optimal policy, and (2) it mimics the scenario where some events are not seen in the training dataset. We compare the performance of offline RL algorithms using different offline datasets, generated by policies of different levels of expertise, in realistic test cases. Results indicate that offline RL approaches perform better when trained on datasets from expert policies, stressing the importance of the quality of the offline datasets. These findings highlight the potential of RL-based adaptive traffic control for improving transportation efficiency, especially when tailored to the specific conditions of RITI communities.
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EFFECTS OF TOURISM ON RURAL ROADS & RURAL DELIVERY WITH CAVWhile some congestion is expected at rural attractions such as national parks, theme parks, special sporting events, scenic points and the like, there are locations along the rural highway network that nearby attractions cause substantial congestion and/or unusually elevated traffic safety risk. This paper presents the case of two very popular tourist attractions on the North Shore of the Island of Oahu in the State of Hawaii: Laniakea Beach and Shark’s Cove. These locations are within five miles of each other and are served solely by the 2-lane rural Kamehameha Highway. These two locations have been congestion black spots for over a decade, and local opposition to more development and tourism has been substantial. A team of students in civil engineering at the University of Hawaii at Manoa has been meeting with the local communities and has collected sample data to substantiate the extent of the problem. Several discussions were completed, where mitigation proposals were presented and discussed. This paper summarizes both the history of this problem, and the various data collected such as vehicular and pedestrian volumes, travel times and queue lengths. It also presents a list of proposed mitigations. There is a multitude of problems with most of the proposals including cost, appeal (they are not context sensitive), difficulty with agency jurisdictional bounds, community acceptance and risk from waves and long-term sea level rise.
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Center for Safety Equity in Transportation (CSET) Baseline Data and OutreachThe research presented herein summarizes the research and education efforts conducted at the University of Alaska Fairbanks as part of the Outreach, Synthesis, and Baseline Data efforts promoted by the Center for Safety Equity in its first year of operation. These key areas were to effectively engage relevant parties needed for larger research efforts, better evaluate what work has been done and how effective existing programs are and establish a baseline using existing and relevant data to inform and evaluate CSET safety efforts and identify commonalities and differences in RITI safety needs across the consortium states. Dozens of outreach events were hosted by CSET and several other events in which CSET participated to develop and foster key connections and collaborations with community members and agencies. CSET help sponsor and coordinate a regional conference focusing on transportation safety, bringing together diverse perspectives on the safety needs of rural, isolated, tribal, and indigenous (RITI) communities. CSET regularly participated in the annual Alaska Federation of Natives convention, using it as an opportunity for outreach and knowledge gathering. Three-dimensional models were designed and printed for the purpose of demonstrating the challenges of building roads in Alaska. Available data sources were compared to determine and highlight deficiencies in current analytical frameworks and support the need to incorporate other data sources in rural and tribal communities for the purposes of transportation planning and safety evaluation.
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Promoting Positive Traffic Safety Culture in RITI Communities through Active Engagement: Implementation Guide and Outreach ActivitiesRural, Indigenous, Tribal, and Isolated (RITI) communities’ crash data analysis clearly highlights three major areas of concern: prevalence of excessive speed, impaired and distracted driving, and underage driving. Safety-focused educational programs and awareness campaigns have all contributed to a reduction in crashes in urban areas. However, in RITI communities, much more work is still needed. It is important that communities are provided with the proper resources and methods to deliver the appropriate training and educational tools that promote and cause a significant positive change in the traffic safety culture. Through reviewed literature and interviews with tribal community stakeholders, this research team came to understand that tribal youth are most impacted and engaged when educational material is made culturally relevant. We then developed an implementation guide to be used by tribes to create, develop, and enact a sustained educational program with the mission to positively impact traffic safety culture among youth in tribal and rural communities.
