Upper Great Plains Transportation Institute (UGPTI)
Browse by
The Upper Great Plains Transportation Institute (UGPTI) is a research, education, and outreach center at North Dakota State University which is guided, in part, by an advisory council composed of representatives of various organizations, industries, and agencies affecting or affected by transportation. The UGPTI website may be found at https://www.ugpti.org/
Recent Submissions
-
Unlocking Drone Potential in the Pharma Supply Chain: A Hybrid Machine Learning and GIS Approach
(2023)In major metropolitan areas, the growing levels of congestion pose a significant risk of supply chain disruptions by hindering surface transportation of commodities. To address this challenge, cargo drones are emerging as ... -
Data-Driven Deployment of Cargo Drones: A U.S. Case Study Identifying Key Markets and Routes
(2023)Electric and autonomous aircraft (EAA) are set to disrupt current cargo-shipping models. To maximize the benefits of this technology, investors and logistics managers need information on target commodities, service ... -
Identifying Factors Associated with Terrorist Attack Locations by Data Mining and Machine Learning
(2023)While studies typically investigate the socio-economic factors of perpetrators to comprehend terrorism motivations, there was less emphasis placed on factors related to terrorist attack locations. Addressing this knowledge ... -
A Systematic Literature Review of Drone Utility in Railway Condition Monitoring
(2023)Drones have recently become a new tool in railway inspection and monitoring (RIM) worldwide, but there is still a lack of information about the specific benefits and costs. This study conducts a systematic literature review ... -
Introducing an Efficiency Index to Evaluate eVTOL Designs
(2023)The evolution of electric vertical takeoff and landing (eVTOL) aircraft as part of the Advanced Air Mobility initiative will affect our society and the environment in fundamental ways. Technological forecasting suggests ... -
Predicting Advanced Air Mobility Adoption by Machine Learning
(2023)Advanced air mobility (AAM) is a sustainable aviation initiative to deliver cargo and passengers in urban and regional locations by electrified drones. The widespread expectation is that AAM adoption worldwide will help ... -
Ranking Risk Factors in Financial Losses From Railroad Incidents: A Machine Learning Approach
(2023)The reported financial losses from railroad accidents since 2009 have been more than US$4.11 billion dollars. This considerable loss is a major concern for the industry, society, and the government. Therefore, identifying ... -
Reducing Risks by Transporting Dangerous Cargo in Drones
(2022)The transportation of dangerous goods by truck or railway multiplies the risk of harm to people and the environment when accidents occur. Many manufacturers are developing autonomous drones that can fly heavy cargo and ... -
Perspectives on Using Connected Vehicles for Transportation Infrastructure Condition Monitoring
(2022)The condition of surface transportation infrastructure directly affects the economic health of a nation. However, it is difficult to justify the large sums of money needed to extend current methods to monitor all the ... -
Perspectives on Securing the Multimodal Transportation System
(2022)The vast, open, and interconnected characteristics of the transportation system make it a prime target for terrorists and hackers. However, there are no standard measures of transport system vulnerability to physical or ... -
Relating Subjective Ride Quality Ratings to Objective Measures
(2022)Agencies have long used subjective roughness ratings from panels of users to inform policy development on road maintenance strategies. The commoditization of electronics motivated the development of more objective, automated, ... -
Remediation Ranking of High Crash Fatality Locations Involving Older Drivers in Florida's Rural Counties
(2022)In 2019, Florida's aging road users (65 years or older) accounted for 20% of the population but 37% of all crashes. Florida Department of Transportation has identified aging road users as one of the areas that requires ... -
Vehicle Axle Detection from Under-Sampled Signal through Compressed-Sensing-Based Signal Recovery
(2022)In traffic data collection, sampling design should satisfy the requirements of identifying prominent pulses corresponding to vehicle axle passage. Insufficient measurement leads to signal distortion and attenuation, reducing ... -
Detecting Sources of Ride Roughness by Ensemble Connected Vehicle Signals
(2022)It is expensive and impractical to scale existing methods of road condition monitoring for more frequent and network-wide coverage. Consequently, defects that increase ride roughness or can cause accidents will go undetected. ... -
Using Artificial Intelligence to Derive a Public Transit Risk Index
(2022)A terrorist attack on the public transportation system of a city can cripple its economy. Uninformed investments in countermeasures may result in a waste of resources if the risk is negligible. However, risks are difficult ... -
Applying Unsupervised Machine Learning to Counterterrorism
(2022)To advance the agenda in counterterrorism, this work demonstrates how analysts can combine unsupervised machine learning, exploratory data analysis, and statistical tests to discover features associated with different ... -
Technology Developments and Impacts of Connected and Autonomous Vehicles: An Overview
(2022)The scientific advancements in the vehicle and infrastructure automation industry are progressively improving nowadays to provide benefits for the end-users in terms of traffic congestion reduction, safety enhancements, ... -
Characterizing Ride Quality With a Composite Roughness Index
(2022)There are many important applications that require ride quality characterization. However, the only international standard that specifies a roughness index is not suitable for applications beyond assessing the ride quality ... -
Exploratory Spatial Data Analysis of Traffic Forecasting: A Case Study
(2022)Transportation planning has historically relied on statistical models to analyze travel patterns across space and time. Recently, an urgency has developed in the United States to address outdated policies and approaches ... -
An Application of Natural Language Processing to Classify What Terrorists Say They Want
(2022)Knowing what perpetrators want can inform strategies to achieve safe, secure, and sustainable societies. To help advance the body of knowledge in counterterrorism, this research applied natural language processing and ...
RSS 1.0