UGPTI - Upper Great Plains Transportation Institute
12/23/2024 | News release | Distributed by Public on 12/23/2024 15:17
Presentations at the 104th Annual Meeting of the Transportation Research Board by Researchers From the Center for Transformative Infrastructure Preservation and Sustainability
Posted: Dec 23, 2024
Monday, January 6
Freight Rail Transportation Topics
Monday, January 6, 8 a.m. - 9:45 a.m./Convention Center, Hall A/ Poster Board B574
Analyzing the Determinants of Rail Freight Impact on Port Competition in West Africa
- Emmanuel Anu Thompson, North Dakota State University
- Pan Lu, North Dakota State University
As global trade continues to expand, there is growing demand for freight transportation and economic activities. Due to its critical role in port operations, and driven by economic and geographical factors, rail freight transport reform is currently underway in several African countries. Consequently, rail transportation has emerged as a pivotal factor influencing port competition, connecting seaports with inland ports and landlocked countries. Despite this importance, there is a notable absence of studies assessing these determinants, especially in Africa. Therefore, this study seeks to evaluate the factors influential to rail freight transport on port competition in West Africa.
Lectern Session/The (Un)clear Zone: New Perspectives on Trees and Roadsides
Monday, January 6, 8 a.m. - 9:45 a.m./Convention Center 207A
The (Un)Clear Zone: Trying to Make Sense of Street Trees, Street Design, and Actual Safety Outcomes
- Wesley Marshall, University of Colorado, Denver
Lectern Session 2013: Rehabilitation of Culverts and Buried Structures
Monday, January 6, 8 a.m. - 9:45 a.m./Convention Center 207B
Unreinforced 3D Concrete Pipe Construction and Site Implementation: Opportunities and Challenges
- Alireza Hasani, University of North Dakota
- Boshra Besharatian, University of North Dakota
- Sattar Dorafshan, University of North Dakota (presenter)
- Marc Maguire, University of Nebraska-Lincoln
Extrusion-based additive construction of cementitious materials, or 3D concrete printing (3DCP), has gained significant momentum for large-scale construction in recent years. This technology has mainly been employed for residential buildings, with its many opportunities being rather neglected for transportation infrastructure. Various hurdles that hinder the wider adoption of 3DCP are studied in this paper. Specifically, the authors explored the adaptability of 3DCP for unreinforced pipe culverts by investigating printing discontinuities, seam section effect, on structural behavior of six large-scale 3DCP pipes, durability issues associated with permeable voids, water absorption, chloride ion penetrability, and site implementation of 3DCP structures.
Monday, January 6, 8 a.m. - 9:45 a.m./Convention Center Hall A/Poster Board B423
Optimizing Pavement Maintenance and Rehabilitation Strategies for Large-Scale Pavement Networks: A Case Study of Wyoming
- Waleed Aleadelat, University of Wyoming
- Bernard Boakye, University of Wyoming
- Khaled Ksaibati, University of Wyoming
This study focuses on evaluating the current pavement management strategy adopted by the Wyoming Department of Transportation (WYDOT). In this strategy, different road classes in the state are being independently managed in a silo-like approach. A novel optimization tool was developed, utilizing genetic algorithms, to evaluate the long-term impacts of this pavement management strategy. The new tool simulates the work of WYDOT's Pavement Management System and incorporates variables such as pavement types, traffic volumes, and several distress indices.
Highway Capacity and Quality of Service Committee
Monday, January 6, 10 a.m./Marriott Marquis, Marquis Salon 7 & 8 (M2)
History and Future Level of Service
- Wesley Marshall, University of Colorado Denver
Research in Hazardous Materials Transportation
Monday, January 6, 10:15 a.m. - 12 p.m./Convention Center/Hall A/ Poster Board A280
Environmental Risk Analysis of Hazardous Materials Transportation by Class I Railroad: A Case in the Great Northern Railroad Corridor
- Heshani Wickramage, North Dakota State University
- Pan Lu, North Dakota State University
This study investigated the environmental risk of hazmat transportation along the Great Northern rail corridor, focusing on identifying areas of varying risk levels. It hypothesized that the environmental risk from rail hazmat spills varies by location and is influenced by soil, groundwater characteristics, and temperature. The research aims to enhance emergency preparedness by detailing the spatial variability of risk along these rail routes. A comprehensive environmental risk assessment methodology was developed, incorporating probability analysis of hazmat spills and evaluating impacts on soil and groundwater based on contamination volume and risk per car-mile.
Lectern Session: Uncovering Gender Differences in Travel Behavior and Activity Participation
Monday, January 6, 10:15 a.m. - 12 p.m./Convention Center 146B
Exploring Trip Chaining in Paratransit Services: Gendered & Spatial Patterns in the Denver Region
- Aditi Misra, University of Colorado, Denver
- Wesley Marshall, University of Colorado Denver
- Garrett Fardon, University of Colorado Denver
- Shubhayan Ukil, University of Michigan
- Sneha Tallavajjula, University of Colorado Denver
- Manish Shirgaokar, University of Colorado Denver
Monday, January 6, 10:15 a.m. - 12 p.m./Convention Center Hall A/Poster Board B535
Assessing the Impact of Oil and Gas Extraction Activities on Commercial Truck Traffic Safety on Rural Highways: North Dakota and Wyoming Case Study
- Sherif Gaweesh, University of North Dakota (presenter)
- Mohamed Ahmed, University of Cincinnati
This study investigates the factors influencing the severity of large truck crashes, focusing on the impact of oil and gas activities in North Dakota and Wyoming. Using logistic regression models, the research analyzes crash data to identify significant predictors of crash severity. A forest plot analysis was conducted to pinpoint counties with substantial oil and gas operations, leading to the development of three logistic regression models that distinguish between highways in oil and gas counties and those in non-oil and gas counties.
Pedestrian Perceptions, Health, and Environment
Monday, January 6, 10:15 a.m. - 12 p.m./Convention Center Hall A/B600
Pedestrian Crossing Behaviors at Signalized Intersections in Utah: Factors Affecting Spatial and Temporal Violations
- Amir Rafe, Utah State University
- Patrick Singleton, Utah State University
- Sadie Boyer, Utah State University
- Michelle Mekker, High Street Consulting Group, LLC
This study investigates pedestrian crossing behaviors at signalized intersections, focusing on spatial and temporal violations. Using a comprehensive dataset comprising 5,589 pedestrian crossing events at 47 crosswalks across 39 intersections in Utah, the research employs multilevel regression models to identify the factors influencing these violation behaviors. Key findings indicate that individual characteristics, such as gender and mobility device use, environmental conditions including temperature and time of day, and social dynamics such as the presence of other pedestrians, significantly impact violation behaviors.
Human Factors of Infrastructure Design and Operations
Monday, January 6, 10:15 a.m. - 12 p.m./Convention Center Hall A/Poster Board B546
Examining the Interplay of Pedestrian and Right-Turning Driver Behaviors in Traffic Conflict Severity
- Atul Subedi, Utah State University
- Mahyar Vahedi Saheli, Utah State University
- Patrick Singleton, Utah State University
- Alyssa Gaither, Utah State University
- Michelle Mekker, High Street Consulting Group, LLC
This study explores driver and pedestrian behaviors and their interactions at signalized intersections, focusing specifically on right-turn conflicts. We analyzed the behaviors of drivers making right turns and pedestrians crossing at intersections during conflicts to understand how these behavioral actions affected the severity of conflicts at signalized intersections in Utah.
Traffic Signal Control: Toward Safer and More Efficient Operations for Multimodal Users
Monday, January 6, 10:15 a.m. - 12 p.m./Convention Center Hall A/Poster Board B433
Pedestrian Volumes from Push-Button Traffic Signal Data in Oregon: Estimating Models and Assessing Model Transferability
- Mahyar Vahedi Saheli, Utah State University
- Elizabeth Yates, Portland State University
- Patrick Singleton, Utah State University
- Sirisha Kothuri, Portland State University
- Joseph Broach, Portland State University
This work shows that pedestrian push-button data from traffic signals can be used to estimate pedestrian crossing volumes at signalized intersections, which are critical for pedestrian traffic monitoring, safety assessments, and equity and health analyses. Using data collected in Oregon, models with reasonably low error rates were developed. The study also assessed transferability of models developed in one state and applied to another state. This assessment found that simple models such as the one developed in this study may be applied in locations (even other states) where they were not developed and still yield approximately the same degree of accuracy as a similar locally developed model.
Navigating the Intersection of Health, Equity, and Mobility
Monday, January 6, 10:15 a.m. - 12 p.m./Convention Center Hall A/Poster Board A170
Transportation's Influences on Wellbeing: A Literature Review and Scoping Framework
- William Bouck, Utah State University
- Patrick Singleton, Utah State University
- Louis Alloro, No Organization
- Kim Clark, VIA Consulting
- Julie Estes, Utah State University
This study investigates the relationship between transportation and wellbeing: the conditions humans need to flourish at all levels. Using the results gleaned from our literature review of 44 articles, we found correlations between transportation elements and components of physical, psychological, economic, and social wellbeing. These transportation factors affected overall wellbeing, not merely wellbeing during travel. Our review also revealed the four areas of wellbeing we studied are interrelated and can influence one another; they "stack" in a way that determines total wellbeing.
Transit Capacity and Quality of Service
Monday, January 6, 10:15 a.m. - 12 p.m./Convention Center Hall A/Poster Board A214
Pedestrian Safety and Traffic Operations Around Near-Side Versus Far-Side Transit Stops: Emerging Observational Evidence from Utah
- Fariba Soltani, Utah State University
- Atul Subedi, Utah State University
- Patrick Singleton, Utah State University
- Michelle Mekker, High Street Consulting Group, LLC
This research project's objective was to investigate the impacts of transit stop location (near-side versus far-side) on pedestrian safety and traffic operations. Three different video-based behavioral observation data collections at signalized intersections in Utah were utilized to study: (1) transit vehicle stop events and transit rider crossing behaviors and vehicle conflicts; (2) pedestrian conflicts with right-turning vehicles (driver/pedestrian reactions, conflict severity); and (3) pedestrian crossing behaviors (crossing location, crossing behaviors).
Advancing Electric Vehicle Charging Equity
Monday, January 6, 1:30 p.m. - 3:15 p.m./Convention Center 140
Low Emission Technologies for Rural and Tribal Transit
- Evans Akoto, North Dakota State University
- Bright Quayson, North Dakota State University
This paper investigates the adoption and challenges of low-emission technologies in rural and Tribal transit systems in the United States. While urban transit agencies have increasingly integrated cleaner fuel technologies, such as alternative fuels and electric vehicles, rural and tribal transit operations lag behind due to limited resources and infrastructure. Given that cutaway buses, which emit significant carbon per passenger mile, are commonly used in these areas, there is a critical need to explore alternative fuels and vehicle technologies that could reduce greenhouse gas emissions. The study employs a survey distributed to rural and tribal transit agencies to assess their current fuel options, interest in low-emission technologies, and the barriers they face.
Emerging Technology for Signing and Marking Detection and Assessment
Monday, Jan 6, 2025, 1:30 p.m. - 3:15 p.m./Convention Center 146A
Developing a Methodology to Estimate the Retroreflectivity of Longitudinal Pavement Markings Using LiDAR
- Abbas Mohammadi (presenter), University of Utah
- Juan C. Medina, University of Utah
- Abbas Rashidi, University of Utah
Longitudinal pavement markings significantly affect traffic safety, particularly in adverse weather and nighttime conditions when crashes and fatalities are often overrepresented. Given the wide range of factors affecting the performance of pavement markings, periodic monitoring is needed to ensure their integrity and adequate retroreflectivity levels. Typical monitoring methods include individual readings from manual retroreflectometers and, more recently, mobile setups where much larger segments can be covered in shorter periods. However, mobile setups require specialized equipment, calibration, and significant economic resources. This research uses LiDAR data collected as part of asset management efforts to help assess pavement marking retroreflectivity, reducing reliance on special-purpose equipment, mainly for maintenance-related decisions. Identifying and isolating pavement marking from the LiDAR point cloud, filtering, and modeling are part of a proposed exploratory process to evaluate the associations between field-measured retroreflectivity and a combination of intensity from LiDAR readings, RGB data, and marking material.
Lectern Session: Emerging Technology for Signing and Marking Detection and Assessment
Monday, January 6, 1:30 p.m. - 3:15 p.m., 164A Convention Center
An Automatic Traffic Sign Assessment System Using Deep Learning on Road Log Videos
- Shucheng Zhang, University of Washington Seattle
- Chenxi Liu, University of Utah
- Nutvara Jantarathaneewat, University of Washington
- Yinhai Wang, University of Washington
The safety and efficiency of road transportation are critically dependent on proper traffic infrastructure maintenance, especially traffic signs since they are important to guide all road users and ensure smooth traffic operation. However, timely repairs and updates of damaged traffic signs still pose significant challenges. This study introduces an innovative traffic sign assessment system designed to improve efficiency in the detection and assessment of damaged traffic signs by leveraging deep learning techniques. The system incorporates an edge computing device, a dash camera, and a GPS device to perform four critical subtasks: traffic sign detection and classification, object tracking, condition assessment, and inventory building. The system output is formalized into an inventory that could benefit the management of traffic assets carried out directly by agencies.
Travel Behavior Elements: Activity, Mode, Time Use, Destination, and Activity Patterns
Monday, January 6, 1:30 p.m. - 3:15 p.m./Convention Center Hall A
Exploring the Impacts of Air Quality on Travel Behavior and Activity Participation: Evidence from Travel Diary Surveys in Northern Utah
- Fariba Soltani, Utah State University
- Mahyar Vahedi Saheli, Utah State University
- Patrick Singleton, Utah State University
In this study, we explored whether and how areawide air pollution affected individuals' activity participation and travel behaviors, and how these effects differed by neighborhood context. Using multi-day travel survey data provided by 403 adults from 230 households in a small urban area in northern Utah, we analyzed a series of 20 activity and travel outcomes. We investigated the associations of three different metrics (measured and perceived) of air quality with these outcomes - separately for residents of urban and suburban/rural neighborhoods, and controlled for personal and household characteristics.
Poster Session: Transit from the Rider Perspective: Satisfaction and Equity
Monday, January 6, 3:45 p.m. - 5:30 p.m./Convention Center Hall A/Poster Board B494
What Hampers Transit Agencies from Supplying Appropriate Bus-Stop Amenities?
- Sneha Tallavajjula, University of Colorado Denver
- Manish Shirgaokar, University of Colorado Denver
- Aditi Misra, University of Colorado Denver
- Wesley Marshall, University of Colorado Denver
Public transport is not just a convenience, but a necessity for many who identify as racial/ethnic minorities and often live in marginalized communities. While the proportion of individuals relying on public transit has risen, agencies are constrained due to decreasing ridership, largely from those who have other travel options, which in turn has challenged the capacity of transit providers in keeping up with service improvements to enhance user experience. Bus riders' experiences have been documented extensively in the literature. Specifically, wait times for transit have been shown by researchers to be onerous for riders, indicating that transit stops matter. Transit agencies have competing goals within their ever-diminishing budgets where long-term capital improvements clash with medium-term goals such as improving bus stops. We were interested in learning why transit organizations are unable to supply basic amenities such as shelters and benches at regular bus stops. Utilizing online interviews with transit experts across the United States, we learned the agency-side concerns regarding effective investments at bus stops.
Poster Session: Reimagining Mobility: Shared, Micro, and Transit Solutions for the Future
Monday, January 6, 3:45 p.m. - 5:30 p.m./Convention Center Hall A/Poster Board A137
What Incentives Can Increase Adoption of E-bike Conversion Kits and Pedal-assist E-bikes in India?
- Ashique Hussain, Indian Institute of Technology, Delhi
- Manoj M, Indian Institute of Technology, Delhi
- Manish Shirgaokar, University of Colorado Denver
Pedal-assist e-bikes and electric bicycle conversion kits that enable converting conventional bicycles into e-bikes provide cost-effective and sustainable travel alternatives. This study examined the factors influencing the adoption of pedal-assist e-bikes and e-bike conversion kits in Delhi, India, by collecting socio-demographic information, awareness and attitudes toward e-bikes, and the intentions to buy conversion kits. A stated preference experiment was designed to obtain respondents' choices among regular, solar, and converted bicycles.
Technological Advancements in Low-Volume Roads: Stabilization, Recycled Materials, and Data Analysis
Monday, January 6, 3:45 p.m. - 5:30 p.m./201 Convention Center
Detecting Lateral Offset Distance on Rural Roads in Thailand by Using Point Cloud Data: A Case Study
- Nutvara Jantarathaneewat, University of Washington
- Chenxi Liu, University of Utah
- Shucheng Zhang, University of Washington Seattle
- Yinhai Wang, University of Washington
Lateral offset distance refers to the horizontal clearance that serves as an essential buffer for vehicle operation. Illegal permanent and temporary obstacles along roadsides, such as privately owned signs or building expansions, can obstruct visibility and increase the risk of collisions. Traditionally, road agencies have relied on manual inspections to estimate these distances, a process that is both time-consuming and often inaccurate. To overcome these challenges, this study introduces an automatic process for determining lateral offset distance using point cloud data.
Monday, January 6, 3:45 p.m. - 5:30 p.m./Convention Center Hall A/Poster Board A117
Time Series Clustering Methods for Categorizing Active Travel Trends
- Rachael Panik, Georgia Institute of Technology
- Julie Shorey, HNTB
- Kari Watkins, University of California, Davis
- Patrick Singleton, Utah State University
- B. Aditya Prakash, No Organization
Active travel (AT) data have many uses in transportation planning, engineering, public health, and recreational planning. Often, direct measures of biking and walking are not available to transportation agencies; however, proxy, or indirect measures, of biking and walking are, which leads to interest in using them to inform understanding of AT trends. Our work investigates two topics that can direct the future use of AT proxy data in transport problems: (1) we investigate the feasibility of identifying travel typologies in proxy data sets, and (2) we examine three methods of time series clustering to assess each approach's suitability for clustering AT proxy data. We apply these topics to two examples of AT data - self-reported bicycle data and pedestrian "push-button" data at intersections - comparing the clusterings with qualitative and quantitative measures.
Poster Session 2240: Safety Performance and Analysis for Safe Roads
Monday, January 6, 6 p.m. - 7:30 p.m./Convention Center Hall A/Poster Board B504
Analysis of the Safety Influence Areas for Signalized Intersections: An Integrated Spatial-Statistical Analysis
- Mulugeta Amare, University of North Dakota (presenter)
- Daba Gedafa, University of North Dakota
- Sherif Gaweesh, University of North Dakota
- Demisew Degefu, North Dakota State University
This study investigates intersection influence areas (IIAs) for 118 four-legged signalized intersections using 11 years of crash data in North Dakota. The study employed spatial and statistical analysis techniques and predicted the probability of total, upstream, and downstream crashes being intersection-related to estimate IIAs. The analysis considered crash distance from the intersection center, posted speed limits, and road surface conditions. The study evaluated the models using the "area under the receiver operating characteristic." The findings will assist researchers, transportation engineers, and policymakers by offering methods and models for identifying IIAs to improve crash prediction accuracy and enhance intersection safety.
Tuesday, January 7
Advances in Traffic Monitoring Research and Practice
Tuesday, January 7, 8 a.m. - 9:45 a.m./Convention Center, Hall A/Poster Board A177
A Hybrid Approach to Mitigate the Wander Effect in Weight-in-Motion Systems: Embedded Sensors and Computer Vision
- Xinyi Yang, North Dakota State University
- Pan Lu, North Dakota State University
Road maintenance is significantly affected by factors such as vehicle traffic volume and vehicle weights. Traditional methods for obtaining traffic data, such as static weigh stations and existing weigh-in-motion (WIM) systems, encounter limitations, including inefficiencies and inaccuracies, which are often exacerbated by variables like vehicle speed and road conditions. To address these challenges, this study introduces a novel WIM hybrid system that integrates in-pavement glass fiber reinforced polymer fiber Bragg grating (GFRP-FBG) sensors with image-capturing technology, effectively mitigating the wander effect and ensuring precise weight assessments.
Current Research in Railroad Infrastructure
Tuesday, January 7, 8 a.m. - 9:45 a.m./Convention Center Hall A/Poster Board A245
Under-tie Ballast Condition Assessment via Near-Infrared Spectroscopy: A Feasibility Study
- Boshra Besharatian, University of North Dakota (presenter)
- Sattar Dorafshan, University of North Dakota
Timber ties cover roughly a quarter of a typical railroad section surface area. The under-tie ballast cannot be visually inspected for excessive or trapped moisture, which in the ballast often indicates the presence of fouling. In theory, the trapped water could ingress through contact with ties to their top surface. In this research, an experiment was designed to mimic the water ingress in railroad ties experiencing vapor sorption, indicating dry ballast contact and water exposure from saturated ballast.
Current Research in Transportation Equity
Tuesday, January 7, 8 a.m. - 9:45 a.m./Convention Center Hall A/Poster Board B594
Harnessing Generative Models for Equity in Transportation: A Survey
- Bo Yu, Worchester Polytechnic Institute
- Chenxi Liu, University of Utah
Generative models have shown great potential for addressing data equity challenges in transportation by generating realistic, high-quality data from limited samples. In this paper, we survey the use of generative models to promote transportation equity, categorizing social and data-related challenges across different stages of the transportation data pipeline, from policy-making to data dissemination. We also introduce generative models, including large language models (LLMs), variational auto-encoders (VAEs), generative adversarial networks (GANs), and diffusion models (DMs), highlighting their roles in data augmentation and scenario generation for advancing transportation equity.
Tuesday, January 7, 10:15 a.m. - 12:00 p.m./Convention Center 143AB
University of North Dakota's Switch to Unleaded Fuel: Operational Impacts
- Jeremy Roesler, University of North Dakota
The University of North Dakota (UND) John D. Odegard School of Aerospace Sciences operates one of the largest collegiate flight training environments on the globe, routinely exceeding 120,000 annual flight training hours. As a core-element of this operation, UND primarily uses piston-engine powered aircraft, which use a leaded fuel called 100 low-lead (LL) AVGAS. In the summer of 2023, UND made an operational change from 100LL (leaded) to UL94 (unleaded) fuel. After four months of UL94 use and over 46,000 hours of flight training, UND switched back to 100LL after experiencing multiple cases of unexpected exhaust valve seat recession. This presentation highlights the operational and maintenance aspects of the organization's fuel adoption.
Tuesday, January 7, 10:15 a.m. - 12:00 p.m./Convention Center 143AB
University of North Dakota's Experience with Unleaded Fuel
- Nicholas Wilson, University of North Dakota
Using data from a stakeholder survey, which indicated support for change to unleaded aviation fuel (UL94), UND made an operational adoption of UL94 for a four-month period in 2023 for its piston-engine fleet in Grand Forks, ND. While using UL94, UND's aircraft experienced numerous cases of exhaust valve seat recession (EVSR). After returning to leaded fuel (100LL), a team of faculty and staff analyzed flight and engine data for statistical correlations between EVSR and relevant operational variables. In particular, an engine's total flight hours using UL94 was statistically negatively correlated to tappet clearance measurement, indicative of developing EVSR, r = -.52, p<.01. This presentation focuses on stakeholder perceptions driving change as well as a statistical analysis of the relationships between EVSR and operational data.
New Users of Shared Airspace Committee
Tuesday, January 7, 10:15 a.m. - 12 p.m./Marriott Marquis, Supreme Court (M4)
ACRP Student Paper: Mode Choice Modeling of Electric Air Taxis for Long-Distance Airport Trips
- Atul Subedi, Utah State University
- Patrick Singleton, Utah State University
This study provides valuable insights into what travelers prefer when it comes to using electric air taxis for long-distance trips to and from airports, contributing to the growing field of urban air mobility. By using an integrated choice and latent variable model and data from over 1,000 U.S. travelers, the research identifies key factors that influence transportation choices, such as travel time, cost, and ease of use.
Transportation and Community Impacts
Tuesday, January 7, 10:15 a.m. - 12 p.m./Convention Center Hall A/Poster Board B433
Explaining Heterogeneity in the Self-Reported Importance of Travel Mode Choice Factors
- Mahyar Vahedi Saheli, Utah State University
- Patrick Singleton, Utah State University
- Antje Graul, Utah State University
This study explores the factors affecting travel mode choices and the relative importance of those factors. Based on two nationwide consumer surveys in the U.S., the objective of this study is to measure and explain heterogeneity in the self-reported importance ratings of eight specific types of factors - time, cost, convenience, safety, health, emotions, environment, social - in travel mode choice decisions.
Transportation and Community Impacts Poster Session
Tuesday, January 7, 10:15 a.m. - 12 p.m./Convention Center Hall A/Poster Board B443
"I Lost It All. The Water Destroyed Everything": Transportation Resilience, Housing, and Displacement of Rural Homeless Communities
- Sarah Grajdura, Utah State University
- Julia LanzDuret-Hernandez, University of Vermont
- Nat Robtoy, University of Vermont
- Dana Rowangould, University of Vermont
In this paper, we explore the effects of a major flood event on the mobility and housing security of people experiencing homelessness in rural communities. This research combines quantitative post-disaster survey data with qualitative data from the unhoused community and a community advisory board. This unique dataset sheds light on important linkages between transportation resilience and housing for unhoused populations. We find important connections between mobility, housing, and mental health. Newly unhoused people were more likely to report decreased mobility in the short and long terms. We find vehicle access and housing status to be statistically related to worse mobility outcomes in the short term. These findings provide important insights for policymakers and planners seeking to improve flood resilience and recovery for unhoused people, particularly in rural and small community contexts.
Aviation Climate Change and Sustainability Subcommittee
Tuesday, January 7, 1:30 p.m. - 3:15 p.m./Marriott Marquis, Monument (M4)
How to Achieve an Equitable Outcome? Exploring a Data-Driven Carbon Emission Offset Responsibility Allocation Through Deep Learning
- Manze Guo, Beijing Jiaotong University
- Yongxin Peng, Beijing Jiaotong University
- Bruce Janson, University of Colorado Denver
- Jia Sun, Civil Aviation Management Institute of China
- Xiang Fang, STV, Inc.
This paper encapsulates a global aviation vision for green development, with the offset responsibility under the Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) framework as the core regulation. It establishes a decision-making mechanism for the international aviation industry's carbon emission offset responsibilities from a multi-perspective of equity. A deep learning model has been developed to accurately predict future aviation emissions by leveraging the vast data resources within the aviation sector. Moreover, an analysis of cumulative CO2 emissions and per-capita emissions among the 30 key aviation-emitting countries is conducted, showing significant disparities in carbon emissions between developed and developing nations. A national emission reduction performance index has finally been devised, and a balanced emission offset responsibility model that considers a variety of factors, including historical responsibilities, emission capacities, and post-COVID-19 recovery scenarios, has been implemented.
Electric Bus Fleet Planning, Scheduling, and Charging
Tuesday, January 7, 1:30 p.m. - 3:15 p.m./Convention Center, Hall A/Poster Board B578
Co-Hub Planning for Electric Bus and Paratransit: An Investigation on Shared Charging Scheme with Fuzzy Multi-Objective Optimization
- Bingkun Chen, Monash University
- Zhuo Chen, Monash University
- Xiaoyue Liu, University of Utah
- Ran Wei, University of California, Riverside
- Arman Malekloo, University of Utah
This study investigates a shared charging scheme for integrating the on-route charging of paratransit electric vehicles into the existing electric bus charging infrastructure network with a fuzzy multi-objective optimization framework. The framework encompasses various spatial measuring methods in formulating the objectives and constraints unique to both bus and paratransit services. By further employing the fuzzy programming approach, the compromise optimal solution is determined, which addresses the trade-off among diverse needs and requirements for different local public sectors at the decision-making stage. The proposed framework offers a vital tool for transit-related companies and utility sectors, enabling them to strategically allocate shared charging co-hubs to effectively support electrified paratransit routes.
Poster Session: Research and Innovation in Accessible Transportation and Mobility
Tuesday, January 7, 3:45 p.m. - 5:30 p.m./ Convention Center Hall A/Poster Board A270
Which Older Adults Would Pay More for Ride-hailing Services with Accessible and Age-Friendly Features?
- Aditi Misra, University of Colorado Denver
- Manish Shirgaokar, University of Colorado Denver
- Asha Weinstein Agrawal, Mineta Transportation Institute
Ride-hailing services (Uber/Lyft) can help older adults make trips without having to drive themselves. However, heavy reliance on technology from booking through payment for the service as well as lack of age-appropriate provisions like wheelchair stowing ability has made it hard for older adults to trust and widely use ride hailing. In fact, in its current avatar, ride-hailing services provide little hope for people with disabilities (no stowing option for mobility devices) or for older adults needing help with the car-to-door trip (the driver is not required to help). Little is known about what features of a ride-hailing service are attractive to older adults, what additional features may be important to them, and at what price. In this paper, we rely on a sample of 2,917 Californians 55 and older to investigate: (1) for what trip purposes older adults are willing to use ride hailing and at what cost, and (2) how much are they willing to pay for the additional features they think will make ride hailing more attractive.
Lectern Session: Implementation of Artificial Intelligence Papers
Tuesday, January 7, 3:45 p.m. - 5:30 p.m./Convention Center 152A
Independent Mobility GPT (IDM-GPT): A Self-Supervised LLM Framework for Customized Traffic Mobility Analysis Using Machine Learning Models
- Fengze Yang, University of Utah
- Xiaoyue Liu, University of Utah
- Lingjiu Lu, University of Washington Seattle
- Bingzhang Wang, University of Washington
- Chenxi Liu, University of Utah
This research addresses critical challenges in urban mobility analysis through an innovative multi-agent large language model (LLM) framework, independent mobility GPT (IDM-GPT). It highlights a transformative approach to traffic analysis by combining advanced machine learning models and LLMs for real-time, user-friendly insights, enhancing decision-making while ensuring data privacy. With its potential to streamline traffic management processes and empower agencies to tackle complex mobility issues efficiently, IDM-GPT aligns with TRB's focus on advancing transportation research and applications.
Understanding and Advancing the Seismic Resilience of Highway Bridges
Tuesday, January 7, 3:45 p.m. - 5:30 p.m./Convention Center 209C
Cyclic Performance of Self-Centering Bridge Bent with Stretch Length Anchors: Experiments and Numerical Analysis
- Suman Neupane, University of Utah
- Chris Pantelides, University of Utah
This study investigates the seismic performance and self-centering capability of post-tensioned 3 bridge bents incorporating unbonded post-tensioning (PT) bars and external energy dissipators, namely four stretch length anchors (SLAs). Two bridge bent configurations were experimentally evaluated under five quasi-static cyclic loadings: the first included a bridge bent specimen with PT bars in the columns and six SLAs at the cap beam and footing, while the second included PT bars in the columns only.
Advances in Construction Management
Tuesday, January 7, 3:45 p.m. - 5:30 p.m./Convention Center Hall A/Poster Board B537
Mapping the Risk Patterns of Construction Cost and Time Overruns Across Regions in U.S. Highway Infrastructure
- Mamdouh Mohammed, Lawrence Technological University
- Ahmed Abdelaty, University of Wyoming
Despite the importance of regional factors, little research has mapped the relationship between project location and the potential for cost overruns and delays across different U.S. regions. This study aims to address this gap by mapping these relationships, which can help construction organizations such as state departments of transportation and local agencies make informed decisions regarding funding resource allocation and project scheduling. By identifying potential risks early, these organizations can implement proactive measures, ultimately improving the chances of delivering projects within budget and on schedule.
Research and Innovation in Accessible Transportation and Mobility
Tuesday, January 7, 3:45 p.m. - 5:30 p.m./Convention Center Hall A/Poster Board A255
Location Choice Modeling for Households with a Disability Based on Parcel Characteristics
- Aleks Paskett, Utah State University
- Ziqi Song, University at Buffalo, SUNY
- Keunhyun Park, University of British Columbia
This study offers an analysis of parcel-level factors influencing location choices for households with a person with disabilities, emphasizing the role of the built environment. Using data regarding the characteristics of residential units, such as size, price, age, and proximity to points of interest, researchers completed a multinomial logit model estimating the factors influencing location choice for the subject households. The subject area for the study is Salt Lake, Utah, Davis, and Weber counties in the state of Utah.
Tuesday, January 7, 6 p.m. - 7:30 p.m./Convention Center Hall A/Poster Board B504
Assessing the Efficacy of Pretrained Large Language Models in Analyzing Autonomous Vehicle Field Test Disengagements
- Melika Ansarinejad, University of Cincinnati (presenter)
- Sherif Gaweesh, University of North Dakota
- Mohamed Ahmed, University of Cincinnati
This study examines the use of pre-trained large language models (LLMs) to analyze disengagement reports from Levels 2-3 autonomous vehicle (AV) field tests, utilizing data from the California Department of Motor Vehicles. Disengagements, which occur when human intervention is required due to operational deficiencies or incidents, are critical for evaluating AV performance and guiding necessary infrastructure adjustments. Traditional methods for analyzing disengagement data are labor-intensive and prone to error, prompting an investigation into LLMs for automating the process. GPT-4 was employed to identify patterns, categorize causes, and extract insights from large datasets. While challenges such as inconsistent reporting by manufacturers and limited detail in reports posed constraints, the findings suggest that LLMs offer significant potential for improving the speed, accuracy, and cost-effectiveness of AV disengagement analysis. These capabilities can support advancements in AV technology and safety practices.
New Insights from Bicycle Transportation Research
Tuesday, January 7, 6 p.m. - 7:30 p.m./Hall A Convention Center/Poster Board B423
Zero-shot Learning Based Cyclists Detection Through Surveillance Systems
- Yinhai Wang, University of Washington
- Sruangsaeng Chaikasetsin, University of Washington Seattle
- Mehrdad Nasri, University of Washington
- Hanyi Yang, University of Hawaii Manoa
- Chenxi Liu, University of Utah
Active transportation, including pedestrians and cyclists, is crucial to the modern transportation system. According to the 2023 NHTSA report, active transportation users account for significant traffic fatalities, with pedestrian and cyclist fatalities comprising 17% and 2% of all deaths, respectively. These statistics highlight the urgent need for improved safety measures for vulnerable road users. Despite technological advancements, existing sensing systems lack detailed classifications for active transportation users, unlike those for motorized vehicles. Our study addresses this gap by introducing a zero-shot learning approach for cyclist detection, leveraging pre-trained models to identify humans and bicycles without additional training data. We propose five critical metrics for cyclist identification and extend this to video detection and tracking using YOLO models and the ByteTrack algorithm.
Safety Performance and Analysis for Safe Road Users and Safe Speeds
Tuesday, January 7, 6:00 p.m. - 7:30 p.m./Convention Center Hall A/Poster Board B518
Right-Turn Safety for Pedestrians: Insights from Multilevel Models of Conflicts in Utah
- Atul Subedi, Utah State University
- Patrick Singleton, Utah State University
- Alyssa Gaither, Utah State University
- Michelle Mekker, High Street Consulting Group, LLC
Pedestrians and vehicles frequently interact at signalized intersections, and a significant portion of recent pedestrian crashes at intersections involve right-turning vehicles. There is a need to proactively understand right-turn safety for pedestrians without waiting for crashes to occur. Using the severity of conflicts between pedestrians and right-turning vehicles as a surrogate safety measure, this study investigated associations of various 6 conflict- and location-specific factors with pedestrian conflict severity, and ascertain variations 7 across locations.
Wednesday, January 8
Wednesday, January 8, 8 a.m. - 9:45 a.m./Convention Center Salon C
Prospecting the Use of Existing Traffic Signal Video Detection Technology for Collecting Reliable Count Data
- Kshitij Sharma, North Dakota State University
This study is aimed at trying to determine the prospects of existing traffic signal video detection technology for collecting reliable count data. A unique intersection outfitted with video detection technology, which had already been set up for counting vehicles, was selected and, more importantly, was next to an automated traffic recorder (ATR). A binding condition for selection was that there should not be any other intersection or driveway between the study intersection and the nearby ATR.
Advancements in Winter Maintenance Technologies
Wednesday, January 8, 8 a.m. - 9:45 a.m./Convention Center Hall A/Poster Board A294
Analyzing Public Satisfaction with Winter Road Maintenance and Snow Clearance Across Demographic Groups and Geographies in Utah
- Shailendra Khanal, Utah State University
- Patrick Singleton, Utah State University
Winter road maintenance (WRM) is essential for safe travel during adverse weather conditions in the United States. This research ultimately aims to improve WRM practices by studying the factors affecting the public's satisfaction with snow/ice clearance and maintenance activities during winter storms. Surveys conducted in early 2024 across diverse regions of Utah provided comprehensive data on satisfaction with snow removal efforts on various transportation facilities and by different groups or organizations. Ordered logit models revealed some significant demographic and regional variations in snow clearance satisfaction.
Wednesday, January 8, 10:15 a.m. - 12:00 p.m./Convention Center, Hall A/Poster Board A102
Incorporating Equity into Transportation Asset Management: Status and Recommendations from Professionals
- Fawzi G. Khalife (presenter), Colorado State University
- Mehmet E. Ozbek, Colorado State University
- Rebecca A. Atadero, Colorado State University
- Erin E. Arneson, Colorado State University
The researchers present the findings from a nationwide survey with professionals working in transportation asset management (TAM). The results highlighted that equity remains neglected in TAM and that its integration is intricate. The respondents provided their perspectives on current practices aimed at advancing equity, as well as the obstacles they encounter in these efforts.
Information Systems and Technology
Wednesday, January 8, 10:15 a.m. - 12 p.m., Hall A Convention Center/Poster Board 144
Attention Empowered GAN for Lens Satin Removal and Image
- Yan Shi, University of Washington
- Chenxi Liu, University of Utah
- Yinhai Wang, University of Washington
In the development of intelligent transportation systems, surveillance cameras have been widely deployed to ensure traffic safety and manage flow. However, these systems often face significant challenges if the lenses are stained, especially at night. The interaction between light and lens stains can degrade image quality, thereby affecting visibility and the accuracy of vehicle detection and traffic monitoring. This paper presents an attention-based generative adversarial network (GAN) model to restore nighttime traffic surveillance images degraded by lens stains from seven adverse weather conditions such as rain and dust. By utilizing an innovative attention mechanism, our model effectively identifies and prioritizes regions severely affected by stains, optimizing the restoration process.
Driving Equity Forward: Addressing Disparities in Electric Vehicle Adoption and Infrastructure
Wednesday, January 8, 10:15 a.m. - 12 p.m./Convention Center 140
Advancing Equitable Electric Vehicle Adoption: Addressing Home Charging Barriers and Costs
- Parsa Pezeshknejad, University of Vermont
- Lilac Damon, University of Vermont
- Sarah Grajdura, Utah State University
- Dana Rowangould, University of Vermont
Policymakers are pursuing vehicle electrification to reduce greenhouse gas. To equitably and effectively decarbonize transportation, we must address context-specific barriers to EV adoption, especially among disadvantaged populations. A critical obstacle faced by many with fewer economic resources is a lack of access to home charging, which brings benefits in terms of convenience and cost. People living in multifamily, attached, and older homes and renters face unique barriers to installing home chargers, although little is known about the effects of these home charging barriers on EV adoption. In this study we evaluate the relationships between EV adoption and housing characteristics as well as the costs of installing home charging for homes of different types in Burlington, Vermont.
Asphalt Binders: Advances in Alternative Binders and Recycling Technology
Wednesday, January 8, 3:45 p.m. - 5:30 p.m./Convention Center Hall A/Poster Board A156
Optimizing Modified Asphalt Binder Performance: Role of Recycled Polyethylene and Waste Cooking Oil
- Raja Abubakar Khalid, University of North Dakota (presenter)
- Duncan Oteki, University of North Dakota
- Daba Gedafa, University of North Dakota
- Nabil Suleiman, University of North Dakota
This study focuses on utilizing recycled polyethylene (PE) as an asphalt binder modifier. The effect of PE and waste cooking oil (WCO) on the rheological properties of asphalt binders used in North Dakota was examined. A shredded blend of high-density PE and low-density PE obtained from grocery bag recycling was used to modify the PG 58S-34 asphalt binder using the wet method. The results indicate significant improvement in the PE-modified binder's rutting resistance. Adding WCO improved the fatigue cracking resistance while maintaining the modified binder's rutting resistance. Asphalt binder with 4.5% PE and 5% WCO replacement resulted in optimum performance at high and average temperatures under different aging conditions.
Pavement Material Behavior and Testing Methodologies
Wednesday, January 8, 3:45 p.m. - 5:30 p.m./Convention Center Hall A/Poster Board A166
Evaluating the Performance of Rutting Tests for North Dakota's Mixtures Containing Reclaimed Asphalt Pavement
- Duncan Oteki, University of North Dakota (presenter)
- Andebut Yeneneh, University of North Dakota
- Raja Abubakar Khalid, University of North Dakota
- Daba Gedafa, University of North Dakota
- Nabil Suleiman, University of North Dakota
This study investigated the |dynamic modulus (|E*|), flow number (FN), and incremental repeated load permanent deformation (iRLPD) tests as substitutes for evaluating the rutting performance of mixtures. The strong correlation between the Hamburg wheel track testing (HWTT) rut depths and FN and iRLPD parameters suggested that these tests can be substitutes. Ranking mixtures based on the |E*|, FN, iRLPD, and HWTT parameters revealed that factors affecting rutting performance, such as the binder grade, gradation, and reclaimed asphalt pavement (RAP) content, were detected.
Texture Evaluation and Friction Response: The Rub on Safety
Wednesday, January 8, 3:45 p.m. - 5:30 p.m./Convention Center 202B1
Safety Performance Functions and Crash Modification Factors for Skid Resistance on Interstate and Non-Interstate Highways
- Atul Subedi, Utah State University
- Sailesh Acharya, National Renewable Energy Laboratory (NREL)
- Patrick Singleton, Utah State University
- Michelle Mekker, High Street Consulting Group, LLC
Pavement friction is crucial for road safety, especially in adverse weather. This study investigates the relationship between pavement friction - measured as skid number (SN) - and crash frequency on Utah highways. Using data from 2016-2019 for I-15 (interstate) and US-89 (non-interstate), negative binomial models were estimated to establish safety performance functions and crash modification factors. The models accounted for traffic volume, segment length, and roadway geometric characteristics, examining various crash types, including dry and wet weather, property damage only, and injury-related crashes.