Raj BridgelallNorth Dakota State University | NDSU · College of Business
Raj Bridgelall
Doctor of Philosophy
About
134
Publications
30,276
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Introduction
Academe research scientist and industry technology leader with more than 30 years of experience as principal investigator, technical manager, and product developer. Deployed products and services include intelligent transportation systems, big data analytics, wireless sensor networks, cloud computing, mobile computing, and optomechanical systems. Published more than 70 peer-reviewed articles and has 140 US patents issued or pending.
Additional affiliations
Education
September 2011 - June 2015
September 1990 - December 1991
September 1987 - December 1990
Publications
Publications (134)
Solid-state batteries (SSBs) offer significant improvements in safety, energy density, and cycle life over conventional lithium-ion batteries, with promising applications in electric vehicles and grid storage due to their non-flammable electrolytes and high-capacity lithium metal anodes. However, challenges such as interfacial resistance, low ionic...
Integrating advanced air mobility (AAM) into the logistics of high-value electronic commodities can enhance efficiency and promote sustainability. The objective of this study is to optimize the logistics network for high-value electronics by integrating AAM solutions, specifically using heavy-lift cargo drones for middle-mile transport and using th...
Solid-state batteries (SSBs) hold the potential to revolutionize energy storage systems by offering enhanced safety, higher energy density, and longer life cycles compared with conventional lithium-ion batteries. However, the widespread adoption of SSBs faces significant challenges, including low charge mobility, high internal resistance, mechanica...
Rechargeable solid-state batteries (SSBs) offer enhanced safety, higher energy density, and longer cycle life compared with conventional lithium-ion batteries, making them a promising solution for electric vehicles, grid storage, and other high-demand applications. However, challenges such as interface stability, low ionic conductivity, and manufac...
Integrating advanced air mobility (AAM) into the logistics of high-value electronic commodities can enhance efficiency and promote sustainability. The objective of this study is to optimize the logistics network for high-value electronics by integrating AAM solutions, specifically using heavy-lift cargo drones for middle-mile transport and using th...
Electrifying aircraft, a crucial advancement in the aviation industry, aims to cut pollutive emissions and boost energy efficiency. Traditional aircraft depend on fossil fuels, which contribute significantly to greenhouse gas emissions and environmental pollution. Despite progress in electric propulsion and energy storage technologies, challenges s...
Electrifying aircraft, a crucial advancement in the aviation industry, aims to cut pollutive emissions and boost energy efficiency. Traditional aircraft depend on fossil fuels, which contribute significantly to greenhouse gas emissions and environmental pollution. Despite progress in electric propulsion and energy storage technologies, challenges s...
This study examines the balance between urban transportation security and supply chain efficiency amid global disruptions like the COVID-19 pandemic, attacks on maritime lanes, and geopolitical conflicts. The authors combine bibliometric network analysis and natural language processing (NLP) to review scholarly literature from 2017 to 2023. This ap...
This study presents a comprehensive exploration of vertical take-off and landing (VTOL) aircraft within advanced air mobility (AAM), examining the crucial challenges of integrating these innovative technologies into transportation systems. AAM promises transformational social change by enhancing transportation energy efficiency, safety, and operati...
The emerging field of Advanced Air Mobility (AAM) presents myriad opportunities for disrupting traditional modes of transport, including passenger travel to cargo logistics. Moving cargo by air instead of by truck in significant volumes can preserve road condition and reduce highway crash exposure. However, its path to full-scale adoption is fraugh...
The transportation of patients in emergency medical situations, particularly in rural areas, often faces significant challenges due to long travel distances and limited access to healthcare facilities. These challenges can result in critical delays in medical care, adversely affecting patient outcomes. Addressing this issue is essential for improvi...
This study examines the balancing between urban transportation security and supply chain efficiency amid global disruptions like the COVID-19 pandemic, attacks on maritime lanes, and geopolitical conflicts. The authors combine bibliometric network analysis and natural language processing (NLP) to review scholarly literature from 2017 to 2023. This...
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 solu...
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...
Ships connect the global economy through maritime transport. However, their susceptibility to increasing geopolitical conflicts has heightened concerns about the risks to crew safety and navigation security. This systematic literature review (SLR), utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework,...
Regular railway inspections are crucial for maintaining their safety and efficiency. However, traditional inspection methods are complex and expensive. Consequently, there has been a significant shift toward combining remote sensing (RS) and machine learning (ML) techniques to enhance the efficiency and accuracy of railway defect monitoring while r...
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 transpo...
The relentless expansion of urban populations and the surge in e-commerce have increased the demand for rapid delivery services, leading to an increase in truck traffic that contributes to urban congestion, environmental pollution, and economic inefficiencies. The critical challenge this poses is not only in managing urban spaces efficiently but al...
This primer provides an overview of the rapidly evolving field of generative artificial intelligence, specifically focusing on large language models like ChatGPT (OpenAI) and Bard (Google). Large language models have demonstrated unprecedented capabilities in responding to natural language prompts. The aim of this primer is to demystify the underly...
The emergence of autonomous vehicles (AVs) presents a transformative shift in transportation, promising enhanced safety and economic efficiency. However, a fragmented legislative landscape across the United States hampers AV deployment. This fragmentation creates significant challenges for AV manufacturers and stakeholders. This research contribute...
As official public records of inventions, patents provide an understanding of technological trends across the competitive landscape of various industries. However, traditional manual analysis methods have become increasingly inadequate due to the rapid expansion of patent information and its unstructured nature. This paper contributes an original a...
Governments and manufacturers anticipate that connected vehicle deployments will reduce accidents, optimize traffic flow, and enhance the driving experience. Although extensive studies focus on the technical aspects of connected vehicles, a gap exists in systematically analyzing the invention trends shaping the field. Insights into these trends is...
This study tackles the urgent need for efficient condition monitoring of road and rail infrastructure, which is integral to a nation’s economic vitality. Traditional methods proved both costly and inadequate, resulting in network gaps and accelerated infrastructure decay. Employing connected vehicles with integrated sensors and cloud computing capa...
The inefficiency of transporting goods contributes to reduced economic growth and environmental sustainability in a country. Autonomous trucks (ATs) are emerging as a solution, but the imbalance in the weight moved and ton-miles produced by long-haul and short-haul trucking creates a challenge in targeting initial deployments. This study offers a u...
Stakeholders expect emerging urban air mobility (UAM) services that use electric vertical takeoff and landing (eVTOL) aircraft to revolutionize transportation systems. However, to be effective, eVTOL facilities, known as vertiports, must seamlessly integrate with the existing multimodal transportation infrastructure. This research analyzes how to b...
The gradual adoption of electric vehicles (EVs) globally serves as a crucial move toward addressing global decarbonization goals for sustainable development. However, the lack of cost-effective, power-efficient, and safe chargers for EV batteries hampers adoption. Understanding the research needs and identifying the gaps in EV charger innovation in...
Analysts predict that future air taxis will fundamentally change the travel behavior of society. However, current market forecasts for air taxi demand varies widely because of inconsistencies in assumptions about travel purpose, technology acceptance, time savings, affordability, and safety. To successfully deploy Advanced Air Mobility (AAM), stake...
Workforce shortages during the COVID-19 pandemic and the recent threat of railroad strike in the United States have generated greater public awareness of how freight flow disruptions can harm society. Unlike highways, trains often do not have the ability to take alternative routes that directly connect major metropolitan areas; hence railroad netwo...
Traditional hot spot and cluster analysis techniques based on the Euclidean distance may not be adequate for assessing high-risk locations related to crashes. This is because crashes occur on transportation networks where the spatial distance is network-based. Therefore, this research aims to conduct spatial analysis to identify clusters of high- a...
The successful deployment of Advanced Air Mobility (AAM) requires the safe integration of electric vertical takeoff and landing (eVTOL) aircraft in non-segregated airspace. However, a lack of practical deployment demonstrations can slow the regulatory progress. This study presents a practical deployment framework for the integration of eVTOL aircra...
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 a potential mode of transport that could improve the reliability of the pharmaceutical supply chain and enhance healthcare. This...
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 location establishment, and the distribution of origin–destination pairs within EAA’s range limitations. This research introduces a thr...
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 that commercial services are fast emerging to transform urban and regional air mobility for people and cargo. However, the complex...
This primer provides an overview of the rapidly evolving field of generative artificial intelligence, specifically focusing on large language models like ChatGPT (OpenAI) and Bard (Google). Large language models have demonstrated unprecedented capabilities in responding to natural language prompts. The aim of this primer is to demystify the underly...
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 gap, this study conducts a multivariate analysis to determine attributes that are more associated with terrorist attacked locat...
Drones have recently become a new tool in railway inspection and monitoring (RIM) worldwide, but there is still a lack ofinformation about the specific benefits and costs. This study conducts a systematic literature review (SLR) of the applications, opportunities,and challenges of using drones for RIM. The SLR technique yielded 47 articles filtered...
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 to reduce pollution, reduce transport costs, increase accessibility, and enable a more reliable and resilient supply chain. Howeve...
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 cyberattacks. The separation of governance over different modes of transport increases the difficulty of coordination in developin...
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 and ranking the factors that contribute to financial losses from railroad accidents would inform strategies to minimize them. To...
This educational guide will help students and practitioners seeking to understand the fundamentals and practice of linear programming. The exercises contained within demonstrate how to solve classical optimization problems with an emphasis on spatial analysis in supply chain management and transport logistics. All exercises describe the Python prog...
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 safely integrate into the national air space. Those developments present an opportunity to not only diminish risk but also to decre...
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 multimodal infrastructure. The convergence of connected vehicle and cloud computing technologies presents an opportunity to automate...
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 attention in achieving Vision Zero—a strategy to eliminate all traffic fatalities and severe injuries, while increasing safe, healt...
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, and cost-effective measurement technologies. Consequently, there has been an explosion of ensemble measurements using smartp...
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 the quality of signal pulses. {This study exploits the value of under-sampled data by applying compressed sensing (CS) method...
It is expensive 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. This paper presents a method to enable network-wide, continuous monitoring by using low-cost GPS receivers and accelerometers onboard regula...
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 terrorist motives. A new empirical text mining method created a “motive” field in the Global Terrorism Database to enable associativ...
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, stress-free travels, fuel cost savings, and smart parking, etc. The advances in connected, autonomous, and connected autonomous ve...
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 to infrastructure planning, design, and construction. Policymakers at the federal, state, and local levels are expressing greater...
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 of paved roads. Other potential applications include automated ride quality characterization of gravel roads, bike or wheelchai...
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 machine learning techniques to a comprehensive database of terrorism events. A specially designed empirical topic modeling technique...
The aim of this tutorial is to help students grasp the theory and applicability of support vector machines (SVMs). The contribution is an intuitive style tutorial that helped students gain insights into SVM from a unique perspective. An internet search will reveal many videos and articles on SVM, but many of them give simplified explanations that l...
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 that commercial services are fast emerging to transform urban and regional air mobility for people and cargo. However, the complex...
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 to quantify in an objective manner because of uncertainties, speculations, and subjective assumptions. This study contributes a...
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 attention in achieving Vision Zero—a strategy to eliminate all traffic fatalities and severe injuries, while increasing safe, healt...
The aim of this tutorial is to help students grasp the theory and applicability of support vector machines (SVMs). The contribution is an intuitive style tutorial that helped students gain insights into SVM from a unique perspective. An internet search will reveal many videos and articles on SVM, but free peer-reviewed tutorials are generally not a...
The aim of this tutorial is to help students grasp the theory and applicability of support vector machines (SVMs). The contribution is an intuitive style tutorial that helped students gain insights into SVM from a unique perspective. An internet search will reveal many videos and articles on SVM, but many of them give simplified explanations that l...
Railroads can save significant sums of money by deploying multi-sensor track scanners on connected trains to detect track and roadbed problems that could cause accidents. However, uncertainties about performance and return-on-investment have impeded the development and deployment of such sensor systems. This research develops a budget model that bo...
Current research at the Upper Great Plains Transportation Institute of North Dakota State University (NDSU) focused on the adoption challenges and opportunities of drones in Advanced Air Mobility.
Rapid acquisition, processing, and visualization of data can enhance the effectiveness of transportation planning, traffic operations, and incident response by using data sensed remotely from transportation assets like roads, bridges, railroads, pipelines, freight yards, rights-of-way, and other essential assets. Unmanned aircraft systems (UAS) can...
The rise of autonomous vehicles has created a new landscape of autonomous logistics. Technological advancements in energy storage, capacity, computing, communications, and lightweight structural materials have reduced the cost, size, noise, and risks of vehicle operations. As a result, there has been a manufacturing push of many variants into the m...
Countries considering high-speed rail (HSR) developments face enormous challenges because of their high deployment cost, environmental obstacles, political opposition, and their potentially adverse effects on society. Nevertheless, HSR services are importantly sustainable that can have positive and transformative effects on the economic growth of a...
Micromobility is an evolving form of transportation modality that uses small human- or electric-powered vehicles to move people short distances. Planners expected that bike sharing, the first form of micromobility, would reduce traffic congestion, cut travel cost, reduce pollution, enable connectivity with other modes of transport, and promote publ...
Accelerometers embedded in smartphones have become an alternative means of measuring the roughness of roads. However, the differences in their sensitivity and sampling rates between smartphones could produce measurement inconsistencies that challenge the wide spread of the smartphone approach for road roughness measurements. In this study, the roug...
Railroads are critical to the economic health of a nation. Unfortunately, railroads lose hundreds of millions of dollars from accidents each year. Trends reveal that derailments consistently account for more than 70 % of the U.S. railroad industry’s average annual accident cost. Hence, knowledge of explanatory factors that distinguish derailments f...
Tracks are critical and expensive railroad asset, requiring frequent maintenance. The stress from heavy car axle loads increases the risk of deviations from uniform track geometry. Irregularities in track geometry, such as track warping, can cause an excessive harmonic rocking condition that can lead to derailments, traffic delays, and associated f...
The widespread availability of connected and autonomous vehicles (CAVs) will likely affect social change in terms of how people travel. Traditional methods of travel demand and land use modeling require vast amounts of data that could be expensive to obtain. Such models use complex software that requires trained professionals to configure and hours...
California is the largest economy among states in the US. More than 40% of the nation's containerized cargo flows through the marine ports of California. Cruise ships also call on four of California's largest ports, with the Port of San Diego growing the fastest. This study assessed the attack risk for the Port of San Diego by applying a model from...
The railroad industry plays a crucial role in stimulating the economic growth of a nation. Therefore, monitoring the conditions of railroad is vitally essential for ensuring railroad safety. Railroad maintenance systems have integrated advanced technologies to help inspectors detect and localize anomalies that can cause casualties and financial los...
Transportation agencies report that millions of crashes are caused by poor road conditions every year, which makes the localisation of roadway anomalies extremely important. Common methods of road condition evaluation require special types of equipment that are usually expensive and time-consuming. Therefore, the use of smartphones has become a pot...
GPS loggers and cameras aboard connected vehicles can produce vast amounts of data. Analysts can mine such data to decipher patterns in vehicle trajectories and driver–vehicle interactions. Ability to process such large-scale data in real time can inform strategies to reduce crashes, improve traffic flow, enhance system operational efficiencies, an...
The adoption of connected and autonomous vehicles (CAVs) is in its infancy. Therefore, very little is known about their potential impacts on traffic. Meanwhile, researchers and market analysts predict a wide range of possibilities about their potential benefits and the timing of their deployments. Planners traditionally use various types of travel...
Class I railroads in North America collectively invested USUS$11.2 billion to comply with a U.S. federal mandate to deploy positive train control as a form of train protection system. This amount dwarfs the potential savings from accidents the technology could prevent. Therefore, railroads must seek additional benefits. This research contributes si...
This study applied a decision-based model with uncertainty to identify factors in mode choice and to rank their influence in attracting riders to available public transit modes in the city of Tehran. The model integrates a fuzzy Delphi method and a fuzzy analytic hierarchy process with fuzzy set theory to process opinion uncertainties. The surveys...
Trucks in North America account for more than 23% of the transportation sector's greenhouse gas emissions. Truck platooning and truck electrification are potential technologies for reducing emissions and operating cost. However, adoption uncertainties result in speculations about their potential impact. Traditional modeling techniques to inform pol...
The installation of high-speed rail in the world during the last two decades resulted in significant socioeconomic and environmental changes. The U.S. has the longest rail network in the world, but the focus is on carrying a wide variety of loads including coal, farm crops, industrial products, commercial goods, and miscellaneous mixed shipments. F...
Automated, connected, electrified, and shared mobility will be cornerstones of the transportation future. Research to quantify the potential benefits and drawbacks of practice, and to identify barriers to adoption, is the first step in any strategic plan for their adoption. However, uncertainties, complexity, interdependence, and the multidisciplin...
Transportation agencies cannot afford to scale existing methods of roadway and railway condition monitoring to more frequently detect, localize, and fix anomalies throughout networks. Consequently, anomalies such as potholes and cracks develop between maintenance cycles and cause severe vehicle damage and safety issues. The need for a lower-cost an...
Frequent network-wide monitoring of the condition of roadways and railways prevent fatalities, injuries, and financial losses. Even so, agencies cannot afford to inspect vast transportation networks using present methods. Therefore, the idea of using low-cost sensors aboard connected vehicles became appealing. However, low-cost sensors introduce ne...
Weight data of vehicles play an important role in traffic planning, weight enforcement, and pavement condition assessment. In this paper, a weigh-in-motion (WIM) system that functions at both low-speeds and high-speeds in flexible pavements is developed based on in-pavement, three-dimensional glass-fiber-reinforced, polymer-packaged fiber Bragg gra...
A continuous condition monitoring system to detect and localize railroad track irregularities is achievable with inertial sensors onboard revenue service trains. However, the inaccurate geospatial position estimates of GPS receivers and the non-uniform sampling of inertial sensors adds noise and reduces signal strength. Consequently, the signal-to-...
Regular maintenance of railroad tracks is not only essential for the proper functioning of the railway, but also significantly improves ride quality, reduces track damage, and increases track life. Deviations from the designed track geometry can result in poor ride quality and possible derailments. This research investigates the potential use of lo...
Railroad companies spend a significant portion of their revenue on track inspections to maintain safety and maximize operational efficiency. Deviations from the designed track geometry
over time could lead to poor ride quality and possible derailments. The existing approaches to track inspections are expensive and laborious. The use of low-cost sen...
Federal track safety regulations require railroads to inspect all tracks in operation as often as twice weekly. Railroad companies deploy expensive and relatively slow methods using human inspectors and expensive automated inspection vehicles to inspect and monitor their rail tracks. The current practices are not only expensive and decrease rail pr...