Browsing by Author "Jones, Steven"
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Item Accessibility of movement challenged persons to evacuation routes and their earthquake risk perception(University of Alabama Libraries, 2021) Bhuiya, Md Musfiqur Rahman; Shao, Wanyun; University of Alabama TuscaloosaThis study aims to evaluate the accessibility during earthquake evacuation for movement challenged persons (MCPs), a disable group highly vulnerable to earthquake, and explores their risk perception in the context of megacity Dhaka, Bangladesh. As there is no accessibility measure to determine accessibility of a network of MCPs integrating physical impedance faced by them in their movement, this study has modified Link to Node Ratio calculate the accessibility of MCPs with consideration of physical impedance and applied it determine the accessibility of MCPs to evacuation routes of 13 wards of Dhaka. Study of accessibility of MCPs during evacuation reveals that 6 wards have poor overall accessibilities while 3 wards have relatively satisfactory conditions of overall accessibility and 4 wards have relatively good accessibilities but fall short of satisfactory conditions. The study reveals that MCPs who are more aged and have more severe level of disability perceive accessibilities of evacuation network, indoor floor surface and entrance gate to be lower. Moreover, male and better educated MCPs is found to perceive accessibilities of indoor floor surface and entrance gate to be higher. Age, income, structure, having experienced an earthquake earlier, mass media as a source of information on earthquake training is found to contribute to perceiving higher level of earthquake risk (as a whole). MCPs who have participated in the training program is found to know what they should do in the advent of an earthquake irrespective of being outside or inside of the home. The study reveals lack of accessibility in training centers and lack of distribution of information of training programs as key reasons behind MCPs not participating in the training.Item An Analysis of the Effects of Crash Factors and Precrash Actions on Side Impact Crashes at Unsignalized Intersections(Wiley, 2021) Adanu, Emmanuel Kofi; Li, Xiaobing; Liu, Jun; Jones, StevenAnnually, side impact crashes contribute to a significant proportion of road fatalities. These crashes typically occur as a result of traffic violations at intersections. This study contributes to efforts in addressing side impact crashes at unsignalized intersections by performing a path analysis to unravel some behavioral trajectories through which these crashes occur. The study further investigated how these behavioral pathways influence the severity of the crashes. Crashes that occurred at unsignalized four-way intersections and T-junctions in Alabama were used for model estimations. Three precrash actions, failed to yield right-of-way at the stop sign, failed to yield right-of-way at a turn, and running stop sign, were considered. +e model estimation results reveal that some of the crash factors were more associated with certain precrash factors but not others at either four-way intersections or T-junctions or both. It was observed that side impact crashes that occurred under daylight conditions at four-way intersections, for instance, were less likely to involve running a stop sign but more likely to involve failure to yield at the stop sign and failure to yield right-of-way at a turn, but under dark and unlit roadway conditions, the at-fault drivers were more likely to run a stop sign or fail to yield at a stop sign but less likely to be involved in failure to yield right-of-way at a turn. +is approach to injury severity analysis uncovers complex underlying relationships between precrash actions, other contributing factors, and crash outcomes.Item Cyber-Resilient Positioning and Navigation for Autonomous Ground Vehicles(University of Alabama Libraries, 2024) Dasgupta, Sagar; Rahman, MizanurIn the realm of autonomous ground vehicle navigation, the reliability and integrity of Global Navigation Satellite Systems (GNSS) are paramount. This dissertation investigates the vulnerabilities of GNSS, specifically focusing on spoofing attacks that threaten the operational safety of Autonomous Vehicles (AVs) in urban environments. Through an in-depth exploration of sensor fusion technologies and alternative navigation methodologies, this research aims to investigate the cyber-resilience of GNSS-based AV navigation systems against such sophisticated threats. This research is divided into three key areas of investigation. Firstly, it explores the characteristics of slow drift Global Positioning System (GPS) spoofing attacks, establishing the foundational understanding necessary for developing effective countermeasures. Following this, secondly, the dissertation details the development of a multi-sensor fusion based detection framework that leverages data from an array of onboard vehicular sensors to detect discrepancies indicative of GNSS spoofing attempts. The effectiveness of this detection framework is rigorously evaluated through experimental validation in real-world urban settings, demonstrating its capacity to accurately identify GNSS spoofing with minimal false positives. Thirdly, the research explores the potential of Geographic Information Systems (GIS) and landmark-based navigation systems as alternative solutions for ensuring navigational accuracy in GNSS-contested urban areas. By utilizing a combination of GIS data and identifiable urban landmarks, this approach offers a viable alternative to GNSS-dependent navigation, enhancing the resilience of AVs to GNSS spoofing attacks. The dissertation concludes by summarizing the significant contributions of the research to the field of autonomous vehicular navigation, highlighting the practical implications of the findings for improving the cyber-resilience of GNSS systems. Through its innovative approach to GNSS spoofing detection and alternative navigation strategies, this dissertation lays the groundwork for future advancements in cyber-secure AV operation in urban environments.Item Envisioning Urban Air Mobility in Small and Medium-Sized Urban Areas in the United States(University of Alabama Libraries, 2023) Yang, Chenxuan; Liu, JunUrban Air Mobility (UAM) represents a revolutionary innovation that utilizes low-altitude urban space to provide air transportation. While UAM offers numerous advantages and holds promise as a solution to traffic congestion, it faces various constraints, including public acceptance, economic considerations, and management challenges. While extensive research has explored the integration of UAM into mobility systems for large metropolitan areas, the potential benefits it could bring to smaller urban areas with populations under 350,000 have been under-discussed. This dissertation research aims to assess the feasibility and viability of implementing UAM in small and medium-sized urban areas. The first major study in this dissertation involves a national survey to investigate Americans' willingness to pay for URAM services and their preferences when faced with commutes that exceed a certain duration. The second study evaluates the impact of UAM on over 300 small and medium-sized urban areas by comparing the travel accessibility of existing road-based regional transportation systems with hypothetical UAM-integrated systems. These hypothetical UAM networks interconnect vertiports within regions, enabling travelers to reach their destinations via Vertical Take-Off and Landing (VTOL) aircrafts after reaching the nearest vertiport by ground transportation. The third study explores an innovative intermodal mobility system that integrates Shared Autonomous Vehicles (SAVs) and VTOLs within the UAM framework. Agent-based simulations are employed to assess the feasibility and viability of this system in small and medium-sized urban areas. This dissertation sheds light on the benefits and trade-offs associated with UAM in small and medium-sized urban areas. It serves as a valuable resource for evaluating the practicality of intermodal UAM services and informs policies related to the planning and implementation of UAM services in the United States.Item An Exploratory Approach to Digitizing the Operational Environments for Connected and Automated Vehicles(University of Alabama Libraries, 2022) Fu, Xing; Liu, Jun; University of Alabama TuscaloosaThe transportation industry is going beyond the traditional areas. The digital innovations operated by the technology companies are reinventing transportation with new business and technologies, such as shared mobility and autonomous driving. Among these, connected and autonomous vehicles (CAV) emerge to be a strike in both the industry and research areas. However, in comparison to the thriving in public discussion, the practice and the market of autonomous driving are not clear yet. To ensure operation safety, the CAVs are equipped with various sensors to perceive the surrounding environments during the operation. The road tests of the CAVs collect comprehensive driving contextual information which is not available in the past. The data conveys the information about the vehicle operation, interaction, and the static road environments. The booming in the CAV data provides extensive sources to investigate the traffic from a microscopic aspect, which brings an evolution to the traditional transportation industry and academics to transform from the planning, design, and operation to the age of data, modeling, and machine learning. Under this trend, this dissertation takes the advantage of the multi-source data to examine the driving environments that the CAVs will encounter. The overarching research goal of this dissertation is to explore a framework or methodology to understand the driving environments from the view of CAVs. This research utilizes the (1) Connected vehicle basic safety message data; (2) Google street image data; (3) Lyft Level 5 perception data and (4) Waymo motion data to explore the driving environments from both the static and dynamic aspects. The methodology of this research incorporates spatiotemporal analysis, statistical modeling, and machine learning. The dissertation research will be unfolded into 4 sections which are targeted at four datasets: (1) Historical driving performance study; (2) Static driving environment classification; (3) Dynamic driving environment characterization; (4) Contextual vehicle lane changing prediction.The research in this dissertation is expected to contribute by providing practical metrics for digitizing the driving environments. The extracted information can be compiled to the High Definition (HD) map for autonomous driving or can be employed as indicators for the Operational Design Domains (ODD) evaluation.Item How did the COVID-19 pandemic affect road crashes and crash outcomes in Alabama?(Pergamon, 2021) Adanu, Emmanuel Kofi; Brown, David; Jones, Steven; Parrish, Allen; University of Alabama TuscaloosaWith the rising number of cases and deaths from the COVID-19 pandemic, nations and local governments, including many across the U.S., imposed travel restrictions on their citizens. This travel restriction order led to a significant reduction in traffic volumes and a generally lower exposure to crashes. However, recent preliminary statistics in the US suggest an increase in fatal crashes over the period of lockdown in comparison to the same period in previous years. This study sought to investigate how the pandemic affected road crashes and crash outcomes in Alabama. Daily vehicle miles traveled and crashes were obtained and explored. To understand the factors associated with crash outcomes, four crash-severity models were developed: (1) Single-vehicle (SV) crashes prior to lockdown order (Normal times SV); (2) multi-vehicle (MV) crashes prior to lockdown order (Normal times MV); (3) Single-vehicle crashes after lockdown order (COVID times SV); and (4) Multi-vehicle crashes after lockdown order (COVID times MV). The models were developed using the first 28 weeks of crashes recorded in 2020. The findings of the study reveal that although traffic volumes and vehicle miles traveled had significantly dropped during the lockdown, there was an increase in the total number of crashes and major injury crashes compared to the period prior to the lockdown order, with speeding, DUI, and weekends accounting for a significant proportion of these crashes. These observations provide useful lessons for road safety improvements during extreme events that may require statewide lockdown, as has been done with the COVID-19 pandemic. Traffic management around shopping areas and other areas that may experience increased traffic volumes provide opportunities for road safety stakeholders to reduce the occurrence of crashes in the weeks leading to an announcement of any future statewide or local lockdowns. Additionally, increased law enforcement efforts can help to reduce risky driving activities as traffic volumes decrease.Item Identification of factors associated with road crashes among functionally classified transport modes in Namibia(Elsevier, 2020-03) Adanu, Emmanuel Kofi; Jones, Steven; Odero, KennethNamibia, like other low- and middle-income countries, is facing a public health crisis from deaths and injuries attributable to road crashes. The crash fatality rate in Namibia was recently estimated to be 23.9 per 100,000 population. Such a high rate of road deaths exacts serious social and economic stress on many countries, hence the need to critically examine and understand factors driving this trend. This paper seeks to enhance the understanding of some underlying factors that influence road safety in Namibia and, by extension, serve as an illustrative example for an analysis of similar data within the context of other developing countries. A latent class multinomial logit model was estimated to examine factors that are associated with crashes involving different categories of vehicles commonly used in Namibia. The findings from this study provide evidence of crash contributing factors such as driver age, visibility constraints, rainfall effects, and characteristics of crash locations associated with different transport modes. In highlighting additional contributing factors related to roadway features and vehicle categories, this work forms the foundation of a Safe Systems approach towards addressing road crashes in Namibia and, other countries with similar road safety challenges.Item An in-depth analysis of head-on crash severity and fatalities in Ghana(Cell Press, 2023) Adanu, Emmanuel Kofi; Agyemang, William; Lidbe, Abhay; Adarkwa, Offei; Jones, Steven; University of Alabama TuscaloosaHead-on collisions are often linked to more serious injuries compared to other types of crashes, due to the intense impact they cause. In low-and middle-income countries, these collisions frequently involve high occupancy public transportation vehicles, leading to higher fatality rates per crash. Given the high risk of injury and potential for multiple casualties, this study delves into the factors influencing the outcomes of head-on crashes and the number of fatalities in Ghana. The study analyzed six years of historical head-on collision data from Ghana and developed two models to address the issue. The injury-severity analysis was performed using a random param-eter multinomial logit with heterogeneity in means and variances approach and aimed to identify the factors that have a significant impact on the severity of injuries sustained in head-on colli-sions, while the random parameters negative binomial fatality count model was designed to examine the factors that contribute to the number of fatalities in these crashes in the country. Results showed that head-on collisions with drivers over 65, buses, motorcycles, and those be-tween 25 and 65 years of age were more likely to result in fatalities. Speeding and vehicle malfunctions were also found to be significant contributing factors to fatal head-on collisions. Head-on crashes involving minibuses and incidents where the driver was attempting to overtake another vehicle were found to be more likely to result in a higher number of fatalities. The results of this study uncover an intriguing interaction between human-related elements and socioeco-nomic factors, which pose obstacles to the Government's endeavor to upgrade the major high-ways in the country. Additionally, the increasing need for transportation has led to the presence of vehicles on the roads that may not meet safety standards. Consequently, it is no surprise that several of the study's findings align with expectations. Nevertheless, within the specific context of Ghana, these findings furnish compelling data-driven evidence supporting the adoption and implementation of the safe systems approach as a means to tackle fatal head-on collisions in the country.Item Multi-Scale Risk and Impact Assessment of Potential Dam Failure in the United States(University of Alabama Libraries, 2021) Song, Junho; Jones, Steven; Kam, Jonghun; University of Alabama TuscaloosaAging water infrastructure in the United States (U.S.) is a growing concern. According to the 2018 National Inventory of Dams (NID) database, there are more than 90,000 dams registered in the U.S, and their average age is 57 years. The compounding impact of climate change with aging dams has increased the potential for and exposure risk of dam failure-driven floods. At the national level, dam failure with an absence of a state dam safety program and Emergency Action Plans (EAPs) trigger local-economic collapse causing malfunction of flood control, economic paralysis, and fatalities with property losses. Since the 1950s, which is known as the Dam nation period, dams have been providing sustainable water resources for the entire continental United States (CONUS). Dams are considered a vital infrastructure providing water and water ways to communities and industries, therefore, a dam safety program is required along with increasing economics. At the state level, dams play a significant role as well (e.g., agriculture, navigation, and recreation) to increase the quality of life. Therefore, a scheduled inspection of dams inevitably leans on dam management agencies and private owners for protecting benefits from the existing dams. However, due to the various regional characteristics and legislations by the states, such as topography, privacy, and security issues, systematic administrating of dams is poorly conducted. Dams in the Black Belt areas of Alabama, home to some of the most socioeconomic vulnerable communities in Alabama, indicate an extremely low level of regular dam inspection based on the NID. At the site level, hyper-resolution inundation floodplain mapping for dam breach is crucial to improve EAPs and to minimize adverse impacts of the dam failure. However, hyper-resolution 2D modeling for hydrodynamics and costly bathymetric surveys limit understanding of the impact of antecedent flow conditions on flood mapping at the site level.This dissertation proposes a multiple-scale risk and impact assessment of potential dam failure in the United States with a focus on the state of Alabama, the only state in the CONUS with no formal dam safety legislation, in order to better understand 1) how the risk and preparedness of potential dam failure in the United States vary at a range of spatial scales (site-level to national-level), 2) how the economic benefits of the existing dams vary across the U.S. states in terms of the marginal cost of water use, and 3) what are the values of cutting-edge technologies are beneficial in better describing the flood inundated areas due to potential dam failure. This dissertation consists of five main chapters. In Chapter 1, the objectives and goals of this dissertation are addressed. In Chapter 2, the spatiotemporal patterns of the growth of dams and their potential hazard and economic benefit are assessed, using more than 70,000 NID-registered dams in the CONUS. In Chapter 3, the state-level risk of dam failure is assessed using more than 2,000 dams in the state of Alabama. The vulnerability of communities to dam failure is high in populated counties with high incomes while less populated counties with lower incomes show a low vulnerability to dam failure due to the relatively small storage capacities of the existing dams. In Chapter 4, the sensitivity test of inundation flood mapping to initial river depth with antecedent flow condition is also conducted using the experimental simulations of the two-dimensional hydrodynamic model with a Remotely Operated Vehicle (ROV). Applying the NID database which is updated with EAP data for the entire dams in the U.S, the results of the dissertation provide quantified data on potential economic values and hazards of dams. Therefore, the results of the dissertation are useful to not only estimate the total cost of recovery but also assess potential losses of the water cost due to dam failures. In addition, providing calculated cost of flood damage restoration would be a valuable index for flood insurances and increasing public awareness as a beginning step of dam safety. Furthermore, using an underwater drone has been successfully applied to acquire precise Digital Elevation Model (DEM) data and flood maps. If fully autonomous underwater drones are available later, the drones would play a key role in floodplain research areas as well as not only river streams, but also river basins are accessible to measure the bathymetric survey. The findings of this study can be useful data for reconsideration of the dam safety programs and EAPs, and it further emphasizes the need for careful design of EAPs accounting for antecedent flow conditions and accurate river channel depths for places that are required to establish safety programs.Item New Perspectives on the Role of Transportation Systems in Disaster Resilience(University of Alabama Libraries, 2023) Islam, Riffat; Jones, StevenNatural disasters such as hurricanes and tornadoes can cause significant disruption to transportation systems, making emergency response efforts challenging. To enhance disaster resilience, transportation systems must be able to effectively respond and assist in emergency situations. This dissertation examined the impact of transportation systems on disaster resilience by exploring various research studies, analyzing public attitudes toward adopting emerging technologies, and assessing the practical implications of these technologies in disaster scenarios. The dissertation is therefore divided into three separate but related studies.In the first part of this dissertation, a systematic literature review was conducted to investigate the critical roles of transportation systems in emergency response during a hurricane. A total of 86 scholarly publications were examined to assess the broader functions of transportation systems concerning hurricanes, with a particular focus on the transportation modes utilized and the research methodologies employed. The second part of this dissertation investigates the willingness to use shared autonomous vehicles (SAVs) during tornadic events. The study used a survey to measure the willingness of Alabama residents to use SAVs to reach a community shelter during tornado events. The third part of this dissertation simulates a dynamic ridesharing operation to explore the potential of SAVs in evacuating vulnerable populations during tornado early warning in Tuscaloosa County, Alabama. Finally, the dissertation delves into how transportation systems can bolster disaster resilience while ensuring equitable access to emerging technologies. The outcomes of this dissertation will offer helpful directions for future research and serve as a valuable resource for emergency management agencies seeking to create effective transportation plans in response to disasters.Item Post-pandemic shared mobility and active travel in Alabama: A machine learning analysis of COVID-19 survey data(Elsevier, 2023) Xu, Ningzhe; Nie, Qifan; Liu, Jun; Jones, Steven; University of Alabama TuscaloosaThe COVID-19 pandemic has had unprecedented impacts on the way we get around, which has increased the need for physical and social distancing while traveling. Shared mobility, as an emerging travel mode that allows travelers to share vehicles or rides has been confronted with social distancing measures during the pandemic. On the contrary, the interest in active travel (e.g., walking and cycling) has been renewed in the context of pandemic-driven social distancing. Although extensive efforts have been made to show the changes in travel behavior during the pandemic, people's post-pandemic attitudes toward shared mobility and active travel are under-explored. This study examined Alabamians' post-pandemic travel preferences regarding shared mobility and active travel. An online survey was conducted among residents in the State of Alabama to collect Alaba-mians' perspectives on post-pandemic travel behavior changes, e.g., whether they will avoid ride-hailing services and walk or cycle more after the pandemic. Machine learning algorithms were used to model the survey data (N = 481) to identify the contributing factors of post-pandemic travel preferences. To reduce the bias of any single model, this study explored multiple machine learning methods, including Random Forest, Adaptive Boosting, Support Vector Machine, K-Nearest Neighbors, and Artificial Neural Network. Marginal effects of variables from multiple models were combined to show the quantified relationships between contributing factors and future travel intentions due to the pandemic. Modeling results showed that the interest in shared mobility would decrease among people whose one-way commuting time by driving is 30-45 min. The interest in shared mobility would increase for households with an annual income of $100,000 or more and people who reduced their commuting trips by over 50% during the pandemic. In terms of active travel, people who want to work from home more seemed to be interested in increasing active travel. This study provides an understanding of future travel preferences among Alabamians due to COVID-19. The information can be incorporated into local trans-portation plans that consider the impacts of the pandemic on future travel intentions.Item Reducing traffic violations in the online food delivery industry-A case study in Xi'an City, China(Frontiers, 2022) Lu, Xin-wei; Guo, Xiao-lu; Zhang, Jing-xiao; Li, Xiao-bing; Li, Li; Jones, Steven; Chang'an University; University of South Florida; University of Alabama TuscaloosaOnline food delivery (OFD) is one of the top industries in the Online-to-offline (O2O) commerce sector. Deliverymen need to complete a large number of delivery orders in limited default time every day, which cause high working stress to them. Therefore, a high level of traffic violations and crashes by deliverymen and corresponding negative impact on public safety are observed. To reduce traffic violations by deliverymen and resulting crashes, a hierarchical online food delivery framework is proposed, which is based on data from questionnaire surveys conducted in Xi'an City, China. The study includes the analysis of the root cause correlated with traffic violations during online food delivery as part of an empirical study on the priority delivery fee by applying a conditional price sensitivity measurement (PSM) model. The feasibility and rationality of the framework are further investigated by using cross analysis of urban dwellers' occupation, income, and commuting cost. The results identify that, through rationally shunting the demand of online food delivery, prolonging the default delivery duration, and providing diversified delivery services, the proposed hierarchical online food delivery mechanism is able to relieve the stress of deliverymen during peak hours of food requests. This reduces the willingness of deliverymen to engage in traffic violations, and other risky behaviors during food delivery trips. All of which facilitate high-quality and timely online food delivery service while enabling improved safety of deliverymen and others as part of enhanced public safety and health.Item Robotics and Automation in Construction: Developing Foundational Insight and Tools to Support Safe Implementation(University of Alabama Libraries, 2022) Okpala, Ifeanyi Udodilim; Nnaji, Chukwuma A; University of Alabama TuscaloosaThe construction industry is bedeviled by a high rate of worker attrition, work-related musculoskeletal disorders (WMSDs), injuries, fatalities, and flat or declining productivity rates. This is a major concern of practitioners and researchers in the construction industry prompting the need for the adoption, implementation, and acceptance of emerging technologies such as robotics and automation (RA) tools that have the potential to improve construction workers’ safety, health, and productivity. Among current developments in RA, wearable robots or exoskeletons have gained traction as a viable tool and ergonomic solution which could reduce the impact of the daily repetitive, high-risk tasks and work conditions requiring overexertion. While researchers have reported the utility of exoskeletons in other industries, limited studies have provided foundational insight on the effective and safe use of exoskeletons in the construction domain. The overarching research goal of this dissertation is to advance the body of knowledge and practice at the nexus of robotics and construction operations. This research utilizes a range of research methodologies and data analysis techniques to develop and evaluate novel tools and methods for enhancing the safe and effective integration of wearable robots into construction operations. Specifically, this dissertation develops (1) a conceptual model to investigate the acceptance of wearable robots in the construction industry, (2) a method to assess the impact of environmental factors on the performance of wearable robots when used for specific construction activities, and (3) systematic processes and tools to identify and evaluate the safety risks associated with the use of wearable robots in the construction industry. This study contributes to the body of knowledge by providing researchers with means to assess the acceptance of wearable robots, a method to evaluate the effectiveness of wearable robots within construction context, and the quantification of wearable robot safety risk. The dissertation also contributes to construction practice by developing critical insight, tools, and strategies that support the application of wearable robots in the construction industry.Item The Role of Immersive Visualization Technologies in Natural Hazard Risk Communication(University of Alabama Libraries, 2024) Sanni, Tolulope Opeyemi; Liu, Jun; Shi, YangmingRecent research links climate change to the increased frequency and severity of disaster events, resulting in the loss of life, property losses, displacement, and psychological harm to the global population. This heightens the need to improve natural hazard resilience. Existing research studies have called for mitigating actions for disaster risk reduction and highlighted effective risk communication is critical in shaping natural hazard risk perception and protective action decisions. However, the existing methods of risk communication can only provide households with generalized and abstract natural hazard information, leading to misunderstanding and misinterpretation. This dissertation research explores the use of Virtual Reality (VR) to supplement Natural Hazard Risk Communication (NHRC). Through a comprehensive survey of United States sub-urban residents, a VR-based tornado simulation, and human subjects' experiments, this study evaluated the readiness of communities to embrace VR for NHRC. Additionally, the study assessed the efficacy of VR in enhancing NHRC compared to traditional 2D video methods. Furthermore, this dissertation also investigated individuals' risk perceptions and habituation behavior of different NHRC modalities in VR. The study results showed that demographics of age and gender could play a role in the willingness to adopt VR for NHRC, and VR supplementation to NHRC led to a substantial decline in risk perception for 2D video conditions compared to the baseline, which suggests that immersive visualization has the potential to deliver more effective sensitization for future designs of fully immersive VR-based NHRC systems. Finally, we found that the haptics modality had the highest effect on risk perception, shelter time, protective action intent, and trust in the tornado risk communication than the text and audio modalities while also recording higher risk perception and the slightest tendency to habituate across both groups of risk-takers and non-risk-takers.Overall, this dissertation provides insights into the adoption strategies for VR in NHRC and the effectiveness of immersive natural hazard risk communication strategies. The findings of this study contribute to the design of appropriate and effective natural hazard risk communication systems in the future, aiding informed decision-making and sensitizing proactive measures to safeguard individuals and communities for disaster resilience.Item A Safe Systems Approach to Vulnerable Road User Safety Issues in Ghana(University of Alabama Libraries, 2021) Agyemang, William; Jones, Steven; University of Alabama TuscaloosaApproximately, 90% of global road traffic deaths occur in low-and middle-income countries (LMICs), and vulnerable road users (VRUs) constitute 54%, even though these countries have about 60% of the world’s vehicle population. VRUs are particularly prone to injuries and fatalities because they are not protected by any external vehicular body and their vulnerability is higher in mixed traffic conditions. There have been efforts by many countries across the globe to reduce road traffic deaths and injuries, but progress varies significantly between different regions and countries. In Ghana, VRUs account for a high proportion of crashes, with pedestrians and motorcyclists making up about 60% of total crashes every year. Motorcycle-related road safety has become topical due to the recent rapid rise in commercial motorcycle activities attributed to the problem of urban traffic congestion and the general lack of reliable and affordable public transport in rural areas. Additionally, uncontrolled interaction between human and high-speed vehicular activities in and around settlement areas throughout Ghana has resulted in numerous pedestrian deaths and injuries. The phenomenon has been attributed to the land-use and right-of-way planning practices as well as lack of safe crossing facilities for VRUs, comprising pedestrians, bicyclists, and motorcyclists (both two- and three-wheelers). This dissertation is the result of three distinct, but interrelated research efforts addressing VRU safety issues in Ghana. Ghana, like many other countries in sub-Sahara Africa (SSA), is a rapidly developing nation with a rising middle-income population that is driving the urbanization and motorization processes. Nonetheless, a vast majority of the population rely on walking and motorcycles for their daily travel needs. Pedestrians and motorcyclists, both drivers and pillions, make up a significant proportion of VRU fatalities in the country. This dissertation seeks to throw more light on the VRU safety concerns in the country by a) understanding how local transport professionals perceive pedestrian and motorcycle safety issues and the adoption of the Safe Systems approach as a countermeasure tool to address them, and b) conducting data-driven analyses to identify factors contributing to these crashes so that potential countermeasures can be developed based on local conditions and input from local road safety professionals. The dissertation consists of three major areas related to VRU safety in the country. The first part of the study assessed opinions of local transport professionals on the complex safety issues relating to VRUs using the Safe Systems approach to explore how local context could guide the implementation of countermeasures. The Safe Systems approach takes a holistic view of road safety, and this framework is based on the basic premise that humans are prone to errors, mistakes, and mishaps and that as a result are vulnerable to crashes and must therefore be protected systemically. The Safe Systems approach addresses: behavioral issues that may result in crashes (speeding, driving under the influence, aggressive or distracted driving, etc.) under its safer people pillar; issues related to vehicle design and condition under safer vehicles; emphasis on infrastructure designed and constructed to prevent or reduce the severity of crashes through the safer roads pillar; and finally the promulgation of policies that promote safer speeds, especially where vehicular traffic is mixed with VRUs. The study used a Multi-Criteria Decision-Making tool, the Analytic Hierarchy Process (AHP), to develop a framework based on knowledge and opinions gleaned from a survey of local road safety professionals to prioritize countermeasures for VRUs (i.e., pedestrians and motorcyclists) using a Safe Systems approach. This initial work provided a reference frame for two subsequent data-driven analyses of motorcycle and pedestrian crashes throughout the country. The motorcycle crash study emphasized the differences among crashes that occur in rural versus urban areas. The pedestrian study focused explicitly on crashes that occurred on inter-urban highways in Ghana. It is anticipated that the findings of the dissertation research will provide a basis for the development of targeted and appropriate countermeasures to reduce the number of VRU deaths and injuries in Ghana. The recommendation for a localized Safe Systems approach and a data-driven strategy to address VRU safety issues is expected to result in improved overall road safety in the country, and other countries with similar characteristics in the region. The proposed Safe Systems framework developed, and its results can be used by transport professionals to prioritize localized efforts to improve the safety of VRUs.Item Severity analysis of crashes involving in-state and out-of-state large truck drivers in Alabama: A random parameter multinomial logit model with heterogeneity in means and variances(Elsevier, 2022) Okafor, Sunday; Adanu, Emmanuel Kofi; Jones, Steven; University of Alabama TuscaloosaThe trucking sector contributes significantly to the economic vitality of the United States. Large trucks are primarily used for transporting goods within and across states. Despite its economic importance, large truck crashes constitute public safety concerns. To minimize the consequences, there is a need to understand the factors that contribute to the severity outcomes of truck-involved crashes. Since many large truck drivers transport goods across several states, the driver-centered crash factors are expected to differ between in-state and out-of-state drivers. For this reason, this study developed two random parameters multinomial logit models with heterogeneity in means and variances to examine the factors contributing to the severity of crashes involving in-state and out-of-state large truck drivers in Alabama. The study was based on the 2016-2020 large truck crashes in Alabama. After data cleaning and preparation, it was observed that approximately 20% of in-state and 23% of out-ofstate large truck crashes were fatigue-related. There were more speeding related crashes (12.4%) among in-state large truck drivers, but the contribution of speeding to crash severity outcomes was only significant in the out-ofstate model. More crashes related to red light running violation (14.2%) were observed among out-of-state drivers, pointing to the fundamental issues of fatigue and unfamiliarity with the operations of signalized intersections in Alabama. The study contributes to the literature on large truck crashes by uncovering the nuances in crashes involving in-state and out-of-state large truck drivers. Despite the seeming similarity in factors that influence crash outcomes, this study provides the basis for truck drivers' training and communication campaigns on the differences that may exist in roadway characteristics from state to state. Also, policy formulations and strategies that prioritizes the well-being of the large truck drivers and creates a better working condition for them should be explored.Item A Shared Low-Speed Light-Weight Autonomous Mobility (SLLAM) System for Campus Environments(University of Alabama Libraries, 2023) Zhang, Zihe; Liu, JunVehicle automation, electric vehicle technology, and shared mobility have the capacity to revolutionize the safety, convenience, and environmental impact of future transportation systems. While significant research has focused on the possibility of deploying shared autonomous electric vehicles (SAEVs) on roads to replace human-driven cars, there has been little exploration of the potential for SAEVs to be used in low-speed urban environment to provide on-demand transportation. This dissertation proposes the deployment of a fleet of low-speed, single-occupancy SAEVs to meet the demand for short-distance trips in a low-speed urban environment. This system is referred to as the Shared Low-speed Lightweight Autonomous Mobility (SLLAM) system. This dissertation examined the potential impact of introducing SLLAM to a university campus by revealing students' attitudes towards the novel system, accessing the required fleet system, and analyzing the system's performance under different demand levels. Additionally, the competitiveness of the system regarding mode share was analyzed. The dissertation is therefore divided into three separate but related studies.The dissertation consists of three related studies. The first study describes a survey that was conducted to collect information on students' attitudes towards the Shared Low-speed Lightweight Autonomous Mobility (SLLAM) service. This study investigated the intention-to-use and willingness-to-use of the SLLAM system, and machine-learning supported path analysis was used to analyze students' attitudes towards the service. In the second study, based on the reconstructed travel demand in the campus area, the operation of the SLLAM system was simulated using agent-based simulation. The system performance was evaluated under different demand levels. The third study simulated mode choice decisions at the agent level among the SLLAM system and other transportation modes, and analyzed the system's impact on the local environment.The outcomes of this dissertation provide insights for the city planner, stakeholders and agencies considering implementing SLLAM services or similar low-speed autonomous vehicle service in their areasItem Small-Key Based Post-Quantum Cryptographic Scheme for Blockchain-Based Vehicular Ad-Hoc Network (Vanet)(University of Alabama Libraries, 2023) Shakib, Kazi Hassan; Rahman, MizanurThe increasing threat posed by quantum computing to contemporary cryptographic systems has prompted the urgent need for advanced quantum-resistant solutions in secure communication architectures. This thesis aims to address this concern within the context of a blockchain-based Vehicular Ad-hoc Network (VANET). Specifically, I investigate and develop a proof-of-concept of a new Post Quantum Cryptographic (PQC) solution, Diophantine Isogeny Key Exchange (DIKE), designed to ensure the security of VANET against potential quantum-based attacks. In the dynamic VANET scenario, there is a need for a resilient small key-based PQC solution, which requires less computational operations and storage. DIKE, unlike existing PQC methods, integrates algebraic and geometric properties, presenting a mathematically challenging problem for both classical and quantum computers. The study initially focuses on the development and implementation of a quantum-based attack model, utilizing quantum Shor's algorithm, to illustrate the vulnerability of the existing VANET infrastructure and the necessity for a quantum-secured blockchain. Furthermore, the research aims to devise the DIKE PQC solution, leveraging Diophantine equations and isogenies to establish a robust key exchange mechanism resilient to quantum threats in dynamic VANET scenarios to acquire minimum latency.To evaluate the efficacy of the proposed quantum attack model, comprehensive simulations of a blockchain-based VANET, vehicle-to-everything (V2X) communication, and vehicular mobility are conducted using advanced simulation tools, including Objective Modular Network Testbed in C++(OMNET++), the extended INET library, Vehicles in Network Simulation (VEINS), and Simulation of Urban Mobility(SUMO). Additionally, quantum modules are integrated into IBM Qiskit, an open-source quantum software development kit, to demonstrate the potential vulnerabilities of the current cryptographic mechanisms in VANET architecture. The results of this investigation reveal the potential susceptibility of the trust-based blockchain scheme in a blockchain-based VANET to a quantum-based impersonation attack. On the other hand, the results and evaluations provide a detailed performance assessment of the DIKE scheme, affirming its efficiency, computational resilience, and suitability for post-quantum cryptography applications, thus underscoring its potential significance in the field. So, as a low-key size, PQC DIKE can be a viable option for secure communication in blockchain-based VANET. Consequently, this study emphasizes the critical importance of implementing quantum-secured protocols to safeguard VANET against quantum threats, thereby ensuring the integrity and security of communication within the connected transportation system.Item A study of infrastructural connectivity on a college campus: the case of the University of Alabama(University of Alabama Libraries, 2021) Schnarre, Emily L.; Appiah-Opoku, Seth; University of Alabama TuscaloosaAs the University of Alabama and the City of Tuscaloosa continue to undergo unprecedented growth, more students than ever need to commute to campus. While most students choose to drive to campus, this places stress on the University’s parking lots and development plans. In an attempt to combat that stress, the multimodal network infrastructure, was evaluated to identify the overall connectivity for student commuting. This evaluation was completed by using graph theory applications to gauge to overall connectivity of the sidewalk, bike lane, and bus route networks available to students at the University of Alabama. Through GIS mapping, relationships between these networks were identified, as well as gaps in these networks. Along with these graph theory metrics, a survey of student’s commuting patterns was performed to identify how students travel to campus and their overall familiarity with the alternative transportation networks. Together, this data was compiled to identify areas in which connectivity is limiting a student’s ability to commute to campus, either due to gaps in the network or lack of awareness of the network. These results were used to create policy recommendations which sought to improve connectivity metrics and overall mobility for students at the University of Alabama in an effort to combat the recent unprecedented growth.Item Transportation Digital Twin Framework and its Vulnerabilities Against Cyber-Attacks(University of Alabama Libraries, 2023) Irfan, Muhammad Sami; Rahman, MizanurDigital twin (DT) systems aim to create virtual replicas of physical objects that are updated in real-time with their physical counterparts and evolve alongside the physical assets throughout their lifecycle. Transportation systems are poised to significantly benefit from this new paradigm. In particular, DT technology can augment the capabilities of intelligent transportation systems. However, the development and deployment of networkwide transportation DT systems need to take into consideration the scale and dynamic nature of future connected and automated transportation systems. Therefore, there is a need to understand the requirements and challenges involved in developing and implementing such systems.This thesis investigates the development of a Transportation DT (TDT) system framework and all related components alongside an assessment of the vulnerabilities of such a system against cyber-attacks. Accordingly, the concept of DT and its relationship with the transportation system is investigated. Current studies on the safety and mobility enhancement applications using DT are surveyed. A hierarchical concept for a TDT system starting from individual transportation assets and building up to the entire networkwide TDT is presented. A reference architecture is also presented for TDT systems that could be used as a guide in developing TDT systems at any scale within the presented hierarchical concept. The study also investigates the vulnerabilities of the system against cyber-attacks with respect to each part of the architecture. Based on the vulnerability assessment of the system, an intelligent attack model is developed that uses a Reinforcement Learning (RL) based attack agent to execute a sybil attack on the system. This attack model is implemented in a simulation scenario using a microscopic traffic simulation software with the goal of creating congestion within a TDT system. The analyses revealed that the RL agent can learn an optimal policy for creating an intelligent attack.