Denver Tolliver

Advanced Air Mobility (AAM) is increasingly recognized as a promising approach for improving healthcare logistics, yet evidence remains fragmented across aviation, transportation, healthcare, and digital infrastructure. This study examined the operational, clinical, and institutional evidence to characterize the evolution of healthcare-focused AAM, identify dominant research themes, and determine critical knowledge gaps. The review followed PRISMA-ScR guidelines and combined bibliometric analysis, thematic synthesis, and semantic network analysis of 168 peer-reviewed studies published between 2015 and 2025 and retrieved from IEEE Xplore, ScienceDirect, Scopus, and Web of Science. The analysis identified six thematic clusters encompassing system design, healthcare logistics, biological specimen transport, emergency response, health equity, and digital infrastructure. Publication activity increased rapidly after 2020. Emergency response represented the most mature research domain, and pharmaceutical logistics, longitudinal operational validation, and health equity remained comparatively underdeveloped. These findings demonstrate that healthcare-focused AAM functions as a sociotechnical system requiring coordinated advances in technology, governance, institutional integration, and equitable access to support clinically reliable and operationally sustainable healthcare delivery.

Advanced Air Mobility (AAM) is increasingly recognized as a promising approach for improving healthcare logistics, yet evidence remains fragmented across aviation, transportation, healthcare, and digital infrastructure. This study examined the operational, clinical, and institutional evidence to characterize the evolution of healthcare-focused AAM, identify dominant research themes, and determine critical knowledge gaps. The review followed PRISMA-ScR guidelines and combined bibliometric analysis, thematic synthesis, and semantic network analysis of 168 peer-reviewed studies published between 2015 and 2025 and retrieved from IEEE Xplore, ScienceDirect, Scopus, and Web of Science. The analysis identified six thematic clusters encompassing system design, healthcare logistics, biological specimen transport, emergency response, health equity, and digital infrastructure. Publication activity increased rapidly after 2020, emergency response represented the most mature research domain, and pharmaceutical logistics, longitudinal operational validation, and health equity remained comparatively underdeveloped. These findings demonstrate that healthcare-focused AAM functions as a sociotechnical system requiring coordinated advances in technology, governance, institutional integration, and equitable access to support clinically reliable and operationally sustainable healthcare delivery.

Advanced Air Mobility (AAM) has emerged as a transformative solution for time-critical healthcare logistics. It promises to overcome ground transport limitations in emergency response, organ transport, and medical supply distribution. Despite rapid technological progress in electric vertical takeoff and landing (eVTOL) systems, automation, and airspace management, scholarly work on AAM in healthcare remains fragmented across disciplines. Therefore, a systematic synthesis is needed to consolidate knowledge, evaluate methodological maturity, and guide future research and policy directions. This review examines how AAM has been conceptualized, modeled, and applied within healthcare contexts. It addresses three questions: (1) What bibliometric patterns characterize research on healthcare-focused AAM? (2) What technical, regulatory, and societal barriers constrain its integration? (3) How do current approaches optimize time-critical missions? The study conducts a systematic review of 121 peer-reviewed publications (2015–2025) using five major databases. The analysis combines bibliometric mapping, thematic synthesis, and semantic network visualization to identify conceptual patterns, research clusters, and interdisciplinary linkages. Six dominant themes emerge: design, logistics, airspace, acceptance, regulation, and economics. These themes reflect the multidimensional evolution of AAM research. Findings show rapid growth since 2020, driven by advances in automation and electrification. However, the study also reveals persistent fragmentation between engineering-driven feasibility studies and policy or healthcare-oriented research. The field is transitioning from technical prototyping toward integrated frameworks that address safety, governance, and healthcare system alignment. This review contributes a unified socio-technical perspective on AAM for healthcare. It offers conceptual clarity and identifies priority directions for empirical validation, equity-focused deployment, and regulatory harmonization. The study provides actionable insights for researchers, practitioners, and policymakers seeking to translate aerial mobility innovations into resilient, equitable healthcare delivery systems.

The swift advancements in autonomous vehicle systems have facilitated their implementation across various industries, including agriculture. However, studies primarily focus on passenger vehicles, with fewer examining autonomous trucks. Therefore, this study reviews autonomous truck systems implementation in North Dakota’s agricultural industry to develop comprehensive technology readiness frameworks and strategic deployment approaches. The review integrates systematic literature review and event history analysis of 52 studies, categorized using Social–Ecological–Technological Systems framework across six dimensions: technological, economic, social change, legal, environmental, and implementation challenges. The Technology Readiness Level (TRL) analysis reveals 39.5% of technologies achieving commercial readiness (TRL 8–9), including GPS/RTK positioning and V2V communication demonstrated through Minn-Dak Farmers Cooperative deployments, while gaps exist in TRL 4–6 technologies, particularly cold-weather operations. Nonetheless, challenges remain, including legislative fragmentation, inadequate rural infrastructure, and barriers to public acceptance. The study provides evidence-based recommendations that support a strategic three-phase deployment approach for the adoption of autonomous trucks in agriculture.

The growing demand for equitable and efficient transportation solutions has positioned autonomous vehicles (AVs) as a transformative technology with significant potential for rural areas. This literature review examines the challenges and opportunities associated with AV deployment in rural environments, characterized by sparse infrastructure, diverse road conditions, and aging populations. Using a systematic analysis of field tests, simulation-based studies, and survey research, key obstacles are identified, including limited lane markings, unpaved roads, digital connectivity gaps, and user acceptance issues. The results highlight the critical role of advancements in sensor technology, localization methods, and edge computing in addressing these barriers. Additionally, strategic infrastructure modifications, such as enhanced road signage and reliable communication systems, are essential for AV integration. This paper emphasizes the need for tailored AV solutions to meet the specific requirements of rural settings, including adaptability to adverse weather conditions and mixed traffic environments. Insights into public perception reveal the importance of trust-building initiatives and community engagement to foster widespread acceptance. The findings provide actionable recommendations for policymakers, industry leaders, and infrastructure operators, focusing on scalable deployment strategies, policy adaptations, and sustainable solutions. By addressing these challenges, AVs enhance mobility, safety, and accessibility, transforming rural transportation networks into more equitable and efficient systems. This review serves as a foundational reference for future research, charting pathways for the integration of AVs in rural contexts.

Cybersecurity challenges are increasing in the rail industry because of constant technological evolution that includes the Internet of Things, blockchains, automation, and artificial intelligence. Consequently, many railroads and supply chain stakeholders have implemented strategies and practices to address these challenges. However, the pace of cybersecurity implementation in the railroad industry is slow even as cyberthreats escalate. This study uniquely integrates bibliometric analysis with a systematic literature review to provide a holistic view of cybersecurity trends in rail freight. The study analyzes 70 articles focusing on cybersecurity practices in the rail freight industry, structured around four research questions relating to: (1) challenges, (2) measures, (3) emerging trends, and (4) innovations. Key findings are that implementing cybersecurity practices in the rail freight industry comes with numerous challenges and risks. The study concludes that new threats will constantly emerge with technological advancements. Therefore, there is a need for continuous human training, collaboration, and coordination with stakeholders. This study also highlights research gaps and recommends how stakeholders can most appropriately execute cybersecurity strategies and best coordinate them with the various technological functions in the rail freight industry.

Cybersecurity challenges are increasing in the rail industry because of constant technological evolution that includes the Internet-of-Things, blockchains, automation, and artificial intelligence. Consequently, many railroads and supply chain stakeholders have implemented strategies and practices to address these challenges. However, the pace of cybersecurity implementation in the railroad industry is slow even as cyberthreats escalate. This systematic review incorporates bibliometric analysis to analyze 70 articles focusing on cybersecurity practices in the rail freight industry, structured around four research questions relating to: (1) challenges, (2) measures, (3) emerging trends, and (4) innovations. Key findings are that implementing cybersecurity practices in the rail freight industry comes with numerous challenges and risks. The study concludes that new threats will constantly emerge with technological advancements. Therefore, there is a need for continuous human training, collaboration, and coordination with stakeholders. This study also highlights research gaps and recommends how stakeholders can most appropriately execute cybersecurity strategies and best coordinate them with the various technological functions in the rail freight industry.

The efficient and timely delivery of pharmaceuticals is critical, particularly in regions with dispersed populations and challenging logistics. Inclement weather often disrupts ground transport, complicating the consistent supply of essential medications. Advanced air mobility (AAM), particularly through the use of drones, presents a promising solution to these logistical challenges by enabling smaller, more frequent deliveries to low density populated places and bypassing traditional transport constraints. This study evaluates the potential benefits of AAM for pharmaceutical transport in North Dakota (ND). The authors developed a comprehensive GIS and optimization framework to identify optimal locations for logistical centers and routes for drone and truck transport. The study introduces a person-years-saved (PYS) metric to rank the potential for AAM deployments to foster healthcare improvements in underserved communities. Moreover, the study found that drone trips were significantly more cost-effective and efficient than truck trips, with trucks being 2.3 times more expensive and having a 2.8 times higher underutilization rate. The study concludes with recommendations for regulatory support and future research to validate and expand the application of AAM in pharmaceutical logistics, contributing to improved healthcare delivery and operational efficiency in often overlooked rural populations. These insights provide a foundation for the practical implementation of AAM technologies, emphasizing their potential to revolutionize pharmaceutical logistics in challenging environments.

Using Uncrewed Aerial Vehicles (UAVs) to monitor the condition of nodal transportation assets—airports, seaports, heliports, vertiports, and cargo terminals—presents a transformative approach to traditional inspection methods. The focus on nodal assets rather than linear assets like roads, railways, bridges, and waterways fills a gap in addressing the dynamic challenges specific to transportation hubs. This study reviews scholarly literature on applying UAV-based remote sensing (URS) techniques to assess the condition of various transportation hubs, which are critical junctures in global logistics networks. Utilizing a systematic literature review framework, this study reviewed 486 publications from 2015 to 2023 to extract insights from the evolving discourse on URS applications. The findings suggest that these emerging methods resulted in substantial enhancements in time saving, cost efficiency, safety, and reliability. Specifically, this study presents evidence on how URS approaches can overcome the constraints of conventional inspection methods by enabling rapid, high-precision mapping and surveillance in complex and constrained environments. The findings highlight the role of UAVs in enhancing operational workflows and decision making in transportation planning and maintenance. By bridging the gap between traditional practices and innovative technology, this research offers significant implications for stakeholders in the field, advocating for a shift towards more dynamic, cost-effective, and precise asset management strategies.

The proliferation of autonomous trucking demands a sophisticated understanding of the risks associated with the diverse U.S. interstate system. Traditional risk assessment models, while beneficial, do not adequately address the state and regional variations in factors that significantly impact the safety and efficiency of autonomous freight transport. This study addresses the problem by developing a composite risk index that evaluates the safety of U.S. interstate routes for autonomous trucking, considering both state and regional differences in traffic volumes, road conditions, safety records, and weather patterns. The potential for autonomous trucking to transform the freight industry necessitates a risk assessment model that is as dynamic and multifaceted as the system it aims to navigate. This work contributes a regionally sensitive risk index using GIS methodologies, integrating data from national databases, and applying statistical analysis to normalize risk factors. The findings reveal significant state and regional disparities in risk factors, such as the predominance of precipitation-related risks in the Southeast and traffic in the Far West. This work provides a targeted approach to risk assessment for policymakers and infrastructure planners and offers a strategic tool for logistics companies in optimizing autonomous trucking routes. The long-term benefit is a scalable model that can adapt to evolving data inputs and contribute to the broader application of risk assessment strategies in various domains.