Transportation Safety Research Articles

Investigation of Deep Learning Model for Vehicle Classification

The usage of automobiles in cities and metropolitan areas has increased drastically throughout the years and there is a need to monitor the flow of road traffic to improve the traffic congestion and safety. One of the best ways to monitor the traffic is using an artificial intelligence and machine learning. An automatic vehicle tracking system based on artificial intelligence and machine learning can offers capability to analyse the real-time traffic video data for the purpose of traffic surveillance. The computer vision is one of the subsets in machine learning that can train the computer to understand the visual data and perform specific tasks such as object detection and classification. A Vision-based system can be proposed to detect road accidents, predict traffic congestion and further road traffic analytics. This can improve the safety in transportation where it can recognize types of vehicles on the road, detecting road accidents, predicting the traffic congestion and further road traffic analytics. In the context of road traffic monitoring, the parameters of the traffic such as the type and number of vehicles that passes through must be recorded in order to gain valuable insights and make prediction such as the occurrence of traffic congestion. However, this requires reliable informative and accurate data as input for analytics. Therefore, in this research the deep learning model for vehicle classification is investigated to detect, classify types of vehicles and further predictive analytics. The vehicle classification is proposed based on Single Shot Detector (SSD) architecture model. The proposed model is tested on five different classes of vehicles with a total of 1263 images. Experimental results show that SSD model able to achieve 0.721 of precision, 0.741 of recall and 0.731 of F1 Score. Finally, the result show that the SSD model is more accurate among all the models for all the performance measure with the difference of more than 0.052 of precision, 0.706 of recall and 0.05 of F1 Score.

Research progress of hydrogen blocking coatings

In the context of carbon peak and carbon neutrality, the use of clean energy has become the focus of attention. Hydrogen energy as the most potential secondary energy has a very important position in various fields, so the storage and transport of hydrogen energy is one of our most important concerns. Long distance pipeline is regarded as an effective means to transport hydrogen, but the high pressure hydrogen environment is easy to cause hydrogen embrittleness and other problems in the pipeline, which seriously threatens the safety of pipeline transportation. Hydrogen blocking coatings are one of the most effective ways to solve such problems. In this paper, the research results in recent years are reviewed and summarized. The article points out the hydrogen barrier mechanism, advantages and disadvantages of various types of hydrogen barrier coatings, the current status of research, as well as future research focus and development trend.

Research on Collision Warning Method for Ship-Bridge Based on Safety Potential Field

In order to ensure the safety of navigation in a bridge area, and based on the theory of the safety potential field, a method of ship safety assessment and early warning in an inland river bridge area is proposed. Firstly, the risk elements associated with ship collisions in a bridge area are classified. Secondly, these risks are quantified using the potential energy field, the boundary potential field and the behavioural field, and then the ship state under the influence of wind flow, predicted by the Kalman filter, is quantified using the kinetic energy field. Then, the above four potential energy fields are merged to obtain a superposition field, and the magnitude of the instantaneous risk in the bridge area is obtained based on its magnitude. Finally, the change of field strength values under different moments is used for early warning. The results of the simulation of a ship passing through the piers of the Baijusi Bridge show that the model can effectively quantify the risk of a ship–bridge collision in the inland bridge area and provide real-time warning of the risk of a ship–bridge collision in the bridge area, which is of great significance for improving the safety of the inland bridge area.

Occupational health and safety among farmers: a comprehensive study in Central Anatolia, Turkey

BackgroundThe agricultural sector is vital for food production, economic stability, and environmental sustainability. However, it also poses significant occupational health and safety challenges due to factors such as heavy machinery usage, exposure to chemicals, and challenging environmental conditions.MethodThis cross-sectional study involved 366 farmers affiliated with the Yozgat Chamber of Agriculture in Turkey. Data on demographic characteristics, occupational factors, and work accidents were collected with interview technique between May and August 2023. While descriptive data were expressed as categories with numbers and percentages, chi-square analysis was used to compare the obtained answers with the status of having or not having a work accident. Binary logistic regression analysis was used to estimate the effect of independent variables on the probability of having a work accident.ResultsThe study revealed that 33.0% of farmers experienced work accidents in the last year. Most accidents occurred during work shifts (28.8%) and in the fall season (34.8%). Factors contributing to accidents included lack of personal protective equipment (51.5%) and transportation-related issues (36.4%). Logistic regression analysis indicated that working more than 8 h daily, working 5 days or more per week, and using bus/minibus transportation significantly increased the likelihood of experiencing work accidents.ConclusionFindings underscore the importance of implementing effective occupational health and safety measures, including proper training, provision of personal protective equipment, and improving transportation safety. Addressing these issues can enhance the well-being of agricultural workers and contribute to a safer working environment in the sector.

Research on Pipeline Stress Detection Method Based on Double Magnetic Coupling Technology.

Oil and gas pipelines are subject to soil corrosion and medium pressure factors, resulting in stress concentration and pipe rupture and explosion. Non-destructive testing technology can identify the stress concentration and defect corrosion area of the pipeline to ensure the safety of pipeline transportation. In view of the problem that the traditional pipeline inspection cannot identify the stress signal at the defect, this paper proposes a detection method using strong and weak magnetic coupling technology. Based on the traditional J-A (Jiles-Atherton) model, the pinning coefficient is optimized and the stress demagnetization factor is added to establish the defect of the ferromagnetic material. The force-magnetic relationship optimization model is used to calculate the best detection magnetic field strength. The force-magnetic coupling simulation of Q235 steel material is carried out by ANSYS 2019 R1 software based on the improved J-A force-magnetic model. The results show that the effect of the stress on the pipe on the magnetic induction increases first and then decreases with the increase in the excitation magnetic field strength, and the magnetic signal has the maximum proportion of the stress signal during the excitation process; the magnetic induction at the pipe defect increases linearly with the increase in the stress trend. Through the strong and weak magnetic scanning detection of cracked pipeline materials, the correctness of the theoretical analysis and the validity of the engineering application of the strong and weak magnetic detection method are verified.

Identifying Veterans with a Higher Risk of Social Needs Using Cluster Analysis.

Many social need screening to advance population health and reduce health disparities, but barriers to screening remain. Improved knowledge of patient populations at risk for social needs based on administrative data could facilitate more targeted practices, and by extension, feasible social need screening and referral efforts. To illustrate the use of cluster analysis to identify patient population segments at risk for social needs. We used clustering analysis to identify population segments among Veterans (N=2010) who participated in a survey assessing nine social needs (food, housing, utility, financial, employment, social disconnection, legal, transportation, and neighborhood safety). Clusters were based on eight variables (age, race, gender, comorbidity, region, no-show rate, rurality, and VA priority group). We used weighted logistic regression to assess association of clusters with the risk of experiencing social needs. National random sample of Veterans with and at risk for cardiovascular disease who responded to a mail survey (N=2010). Self-reported social needs defined as the risk of endorsing (1) each individual social need, (2) one or more needs, and (3) a higher total count of needs. From the clustering analysis process with sensitivity analysis, we identified a consistent population segment of Veterans. From regression modeling, we found that this cluster, with lower average age and higher proportions of women and racial minorities, was at higher risk of experiencing ≥ 1 unmet need (OR 1.74, CI 1.17-2.56). This cluster was also at a higher risk for several individual needs, especially utility needs (OR 3.78, CI 2.11-6.78). The identification of characteristics associated with increased unmet social needs may provide opportunities for targeted screenings. As this cluster was also younger and had fewer comorbidities, they may be less likely to be identified as experiencing need through interactions with healthcare providers.

Analisis Media Statement Kasus Lion Air Penerbangan Jt-610 Boeing 737 Max 8 Dengan Pendekatan Storytelling Michael L. Kent

The focus of this study is on how Lion Air managed crisis communication following the Boeing 737 MAX 8 crash of Flight JT-610. The research delves into the use of storytelling in media statements as a strategy for crisis communication during the aftermath of the crash. It outlines Lion Air's goals in sharing information and engaging with the public and media in the midst of this crisis. The study utilizes a qualitative text analysis to scrutinize three specific media statements released during the crisis. By applying Michael L. Kent's storytelling elements, the analysis of the media statements concentrates on factors like emplotment, narrative theory, identification, form, and masterplots. The selected statements cover the immediate aftermath of the crash on October 29, 2018; a subsequent statement on March 13, 2019, addressing broader safety concerns surrounding the Boeing 737 MAX 8; and a final statement on October 26, 2019, summarizing findings from the National Transportation Safety Committee's investigation. The research findings suggest that employing storytelling through straightforward text in media statements, incorporating credible character depiction, structured narrative, empathy, and compelling storytelling, can notably influence an organization's reputation recovery and improvement. Well-crafted and timely media releases are essential as primary information sources for the media, especially in crisis scenarios where prompt and precise information dissemination is critical. This method ensures that information, though disseminated quickly, maintains relevant and impactful storytelling aspects. The study concludes that storytelling, characterized by humanistic, empathetic, and coherent narratives across media statements, can be effectively utilized by Lion Air to uphold consistent and narrative-focused communication with the public through the media.

Improving port state control through a transfer learning-enhanced XGBoost model

With the advancements in modern information technology, Port State Control (PSC) inspections, as a crucial measure to protect ship safety and the marine environment, are undergoing an intelligent transformation. This paper aims to streamline the selection process for inspecting high-risk ships by employing a data-driven model to predict the number of deficiencies in ships arriving at ports. A transfer learning-enhanced eXtreme Gradient Boosting (XGBoost) model is proposed by innovatively incorporating sample similarity calculations to adapt the model to the unique characteristics of the target port. This novel model enables the integration of relevant data from other ports, enhancing the predictive performance of the model to specific port conditions. Utilizing PSC inspection records from ports within the Tokyo Memorandum of Understanding (MoU) and choosing the port of Singapore as the target, numerical experiments demonstrate that the proposed model achieves improvements of 1.81 %, 6.08 %, and 3.60 % in the mean absolute error, mean squared error and root mean squared error, respectively, compared to the standard XGBoost model. Furthermore, across various sizes of training samples, the proposed model outperforms other machine learning models. This work may service as a significant step towards exploring the potential of developing data-driven models based on comprehensive data to assess the risk level of foreign ships arriving at ports, ameliorating the PSC inspection process by aiding PSC officers in identifying substandard ships more effectively.

Multi-objective model predictive control for ship roll motion with gyrostabilizers

Ships are prone to significant roll motion while sailing in adverse conditions, posing a serious threat to ship safety and maneuverability. Therefore, effective ship motion control is crucial. Integrating the MPC control algorithm with a gyrostabilizer can effectively achieve this goal. To evaluate and compare control strategies, a multi-objective model predictive control is proposed that integrates considerations of ship motion, safety, and energy consumption to conduct the operation concurrently. By assigning different weights to these factors, the study aims to discern the varying impacts on control effectiveness. The response of ship roll motion in beam waves is evaluated through roll hydrodynamic modelling, accounting for wave memory effects. A state-space model of ship and gyrostabilizers is proposed to represent their dynamic interaction and response to external moment. Subsequently, the influence of different weightings in the multi-objective model predictive control is compared, and the control performances of a frigate under different wave conditions are analyzed respectively. The multi-objective model predictive control, with varied weight assignments, leads to distinct reductions in roll motions. This investigation offers valuable insights into controlling roll motion in beam wave conditions, effectively reducing motion under varying sea conditions, and providing alternative guidance tailored to user preferences.

A hybrid failure analysis model design for marine engineering systems: A case study on alternative propulsion system

Marine engineering systems have a fundamental role in ensuring the efficiency, safety, and sustainability of maritime transportation. The performance and reliability of these systems, particularly propulsion systems, are of paramount importance. This paper introduces a pioneering hybrid failure analysis model that integrate the Variable Weighted Synthesis Analytic Hierarchy Process (VWS-AHP) with the conventional Failure Mode and Effect Analysis (FMEA) methodology. The primary objective is to enhance the comprehension of failure modes within marine engineering systems, particularly focusing on alternative propulsion systems. While conventional FMEA is a widely employed methodology for analysis of failure modes, its capacity and effectiveness can be further augmented by integrating complementary techniques. The proposed hybrid model combines the robustness of FMEA in identifying failure modes with the VWS-AHP method’s ability to handle complex decision-making scenarios involving multiple criteria and varying levels of importance. This integration affords a comprehensive framework to assess failure risks, prioritize critical failure pathways, and evaluate the potential impacts of failures in marine engineering systems. To demonstrate the applicability of the proposed model, we conduct a case study on an alternative propulsion system. The outcomes of the case study showcase the efficacy of the hybrid model in enhancing FMEA.

Maritime Cyber Security: Adopting a Checklist Based on IACS UR E26 Standard

The efficient operation of ship systems that control navigation, communications, sensors, and power and machinery is dependent on the increasing digitization of the maritime sector and the intense use of information and operational technologies. The goal of issuing and enforcing global regulations and standards is to lessen the impact of potential dangers that could jeopardize on-board systems, network and data integrity, and operation, functionality and safety. At this point, "Cyber Resilience of Ships" (UR E26) is recently released by the International Association of Classification Societies (IACS) to address the need to improve ships' cyber resilience. This regulation will be applicable to new ships built on and after 1 July 2024. This study aims to create a check list for ship cyber security based on IACS UR E26 standard. A ship cyber security checklist was developed by first analyzing ship operational technologies, identifying potential cyber risks and vulnerabilities, and then creating a checklist in accordance with the IACS UR E26 standard to ensure cyber security on board. With a focus on clean seas and safe ships, the IACS provides technical assistance, verifies compliance, and conducts research and development to enhance maritime safety, security and regulation. This study provides practical tool to ships for ship cyber security management under the safety management system besides IACS standard benefits. Creating a checklist in accordance with the IACS UR E26 standard also allows ship owners and operators to comply with the standards and facilitate inspection processes. This reduces the effort spent to comply with international regulations. It helps to proactively manage cyber risks by providing a systematic approach to ship cyber security management.

Safety Assurance of Maritime Autonomous Surface Ships

Abstract Safety of Maritime Autonomous Surface Ships (MASS) is inherently complex owing to the dynamic and unpredictable nature of the maritime environment. This is exacerbated by the pace of change in enabling technologies and their disruptive impact. Integral to the safety assurance of MASS is assessment and mitigation of risk. The International Maritime Organisation (IMO) defines Risk as “the combination of frequency and severity of the consequence”. The advent of software-controlled systems has introduced difficulties in quantifying frequencies; an issue which is more prevalent in the context of autonomy due to the complex interaction between control algorithms and the variabilities of the environment in which they are deployed. Within complex autonomous systems, therefore it is challenging to perform quantitative risk assessments using failure rates, which gives rise to a need for different techniques to assess risk. Novel risk assessment methodologies such as those presented in the European Maritime Safety Agency (EMSA) Risk Based Assessment Tool (RBAT) combined with conventional risk assessment techniques can offer a solution to this challenge. Compliance with legislation and standards is another cornerstone of safety assurance, which is also inherently difficult for MASS vessels owing to their having been developed for conventional vessels. A goal-based approach to legislation compliance could present an interim solution until the IMO goal-based Maritime Autonomous Systems (MAS) provides harmonisation across the industry. Whilst MASS Safety assurance is non-trivial, there are solutions to many of the challenges faced; this paper examines the predominant challenges and presents potential solutions.

Drifting vessel statistics and emergency towing cases

Abstract Recent climate studies forecast violent weather events with impact on the safety of maritime transportation. For example, harsh weather may result in system failures such as blackouts or loss of steering capability. Problems met when performing planned maintenance at sea may lead to adverse events if the weather cause delays or makes it impossible to complete the planned work. A drifting vessel in general is a liability for collisions with offshore structures, groundings, and total loss due to capsizing. The increasing use of ocean structures for energy production at sea (coastal and deepwater windfarms) and the transfer of fish farming structures to more exposed locations increase the probability of collisions between drifting ships and ocean structures. To mitigate risks, several incidents and their consequences have been analysed by national administrations. In some cases, these analyses have recommended the use of dedicated emergency towing resources. The willingness of the national governments to fund such resources is directly related to the time since the last major incident in their territorial waters. This paper reviews some recent cases of emergency towing operations in Norwegian waters and highlights challenges interlinked to setting up an emergency towing connection between a drifting ship and an emergency towing vessel in harsh weather.

A combined method for the evaluation of contributing factors to maritime dangerous goods transport accidents

This paper evaluates the contributing factors to maritime dangerous goods (DG) transport accidents by integrating the Entropy Weight (EW) and Grey Relational Analysis (GRA) methods. For this purpose, investigation reports of maritime DG transport accidents that occurred worldwide between 2000 and 2023 are derived from the International Maritime Organization’s Integrated Shipping Information System (IMO GISIS) database’s Marine Casualties and Incidents (MCI) module. Eleven main ship operations and thirteen primary causes were selected by analysing accident investigation reports. The weights of main ship operations are calculated utilizing the EW method. The correlational degrees of the primary causes are then calculated using the GRA method. Most maritime DG transport accidents occur during unberthing, bunkering, and pilotage operations. The most common contributing factors of maritime DG transport accidents are collisions and occupational accidents. Specifically, maritime DG transport accidents are most likely to be caused by collisions during sailing, passage, maneuvering, and bunkering operations, as well as occupational accidents during cargo loading, anchoring, berthing, and mooring operations. The results of this paper can support stakeholders in developing the needed policies to guarantee the safety of maritime DG transport.

High-frequency Resonance Suppression of Railway Traction Power Supply System Based on the Combination of Single-tuned and C-type Filters

Background: Railroad transportation in the actual operation process, there are also many dangerous accidents caused by resonance, which greatly affect the safety of railroad transportation. A comprehensive examination of the operational dynamics within the power branch of a traction substation is imperative for sustaining system equilibrium. Discrepancies between these facets pose a potential threat to the safety of railway transport. Thus, a meticulous analysis of highfrequency resonance characteristics and the formulation of effective suppression techniques become paramount. Objective: Harmonics from grid-side locomotive traction braking are scrutinized under different operational scenarios and different train runs. The aim is to develop an effective harmonic management strategy to normalize the THD and thus maintain the traction power supply system to become more stable. Methods: This study investigates the high-frequency harmonic resonance characteristics using a control variable approach. Harmonics and negative sequences generated during locomotive traction braking under different operating conditions are investigated by means of extensive analysis. These challenges require the implementation of a harmonic management method. This method uses a combination of two monotonic filters and a C filter in parallel. This method applies to different operating conditions and can dynamically adapt harmonics to changes in the number of trains, which is related to the actual dynamics of the traction power system closely. Results: A comparative evaluation of seven operating conditions shows that the filter in this patent exceeds the efficiency of existing methods. The filter reduces the fluctuations during spectral changes, and the voltage distortion rate decreases from the previous 2.33% to 0.55%, making it more adaptable and promising effective harmonic management in high voltage and high current situations. Conclusion: Through multiple simulation tests, a synergistic configuration involving the C-type filter and two single-tuned parallel connections under regenerative braking conditions emerges. This refined, patented filter design not only mitigates the impact of negative sequence during the filtration process but also substantially diminishes high harmonics and THD.

BEYOND – Building an Experience to Yield Optimal Nautical Displays – Measuring Nautical Situation Awareness

Abstract The growing digitisation and integration of ship operations, navigation, communication, safety equipment and systems have expanded the functional scope of modern navigation systems. However, this has also increased the workload for the crew, making it more challenging to cultivate situation awareness and make appropriate decisions, particularly in critical situations. The research project, BEYOND – Building an Experience to Yield Optimal Nautical Displays, aims to develop and validate a test methodology for evaluating maritime Human-Machine Interfaces (HMI). Besides system usability and user experience, maritime HMIs are generally evaluated in terms of the situation awareness acquired during navigation. For this purpose, the established Situation Awareness Global Assessment Technique (SAGAT) was adapted such that participants experienced a series of simulated navigation scenarios and were interrupted at unexpected intervals to answer situation awareness questions. This paper addresses the challenge of formulating the appropriate situation awareness questions and their associated frameworks. An assembly of questions reflecting the knowledge of a navigator was created, taking into account different categories of information, including the own ship, the route taken, and the surrounding area. The number of questions needed to capture the necessary knowledge comprehensively was also defined. Additionally, it was crucial to determine the appropriate answer options for each question. Besides graphically presented multiple-choice questions, where the answer had to be selected based on a screenshot of the environment, there are also alphanumeric questions where the participant had to retrieve knowledge from the situation and enter numerical values. For instance, this included information about the course, navigation hazards, etc. A major challenge in assessing these numerical values was determining the acceptable range, i.e., the thresholds that define an answer as correct or incorrect. This paper outlines the BEYOND methodology developed for the comprehensive testing of maritime HMIs, focusing primarily on situation awareness assessment. It describes the steps taken to compile a list of situation awareness questions and their corresponding accuracy thresholds based on the findings from expert interviews. The paper also discusses the experimental results of a user study conducted to test the overall methodology.

Research on the evolution and venting characteristics of gasoline–air mixture explosions in confined pipeline trench spaces

In recent years, international energy cooperation has become more extensive, and the safe and reliable transportation of oil and gas resources has become increasingly important. However, storage and transportation sites can have confined spaces in engineering practice, which can lead to safety problems. There is a risk of gasoline–air mixture explosions in confined spaces such as pump rooms, valve operation rooms, and inspection wells, particularly in Class B and Class C pipeline trench areas that utilize non-sand-filled trenches or where the local depth exceeds 2.0 m. These locations are equipped with doors, manholes, or ventilation openings for personnel access within oil storage zones. To investigate the combustion characteristics of gasoline–air mixture explosions in such confined spaces, experimental research was conducted on a simulation platform (L/D = 15, V = 0.015 m3). The findings reveal the following: (1) the most hazardous initial gasoline–air mixture volume fraction for ignition at the upper ignition point is 1.7%; (2) the morphology of the internal flame evolves through four distinct stages, with the post-explosion flame shapes resembling “brush-like” and “mushroom cloud” formations; (3) low YCH = 1.1%, medium YCH = 1.7%, and high YCH = 2.3% volume fractions of hydrocarbons were selected to analyze the progression of the explosion development process; (4) the external overpressure distribution during venting explosions, with varying initial gasoline–air mixture volume fractions, conforms to the function y = ae−bx as the distance L varies, with venting pressure waves exhibiting a trend of exponential decay.

Comparison of surface layers responses under heavy truck loadings on new and rehabilitated pavement with different interface bond conditions

The integrity and functionality of road pavements are vital for ensuring safe and efficient transportation networks. However, surface layers are prone to various forms of deterioration. This study investigates the responses of two pavement structures-one newly constructed and one rehabilitated-under traffic loading, through experimental tests conducted on an accelerated pavement testing facility (APT) and numerical simulations using the Viscoroute©2.0 software. Focus is placed on surface layer behavior, with an emphasis on understanding the behavior of interfaces between the asphalt layers. The findings show that the new pavement structure exhibits good bonding and continuous strain distribution, while the reinforced pavement structure exhibits partial sliding at the interface and strain discontinuity. For the new pavement structure, the strains are well predicted using a bonded interface, while for the rehabilitated pavement structure, the strains are predicted using a thin elastic interface layer with a low elastic modulus.

Mobility challenges for women: A case study of bus rapid transit Peshawar

In Pakistan, women face significant barriers to urban mobility. This is due to limited access to safe, affordable, and sustainable public transportation, exacerbated by socio-cultural norms and experiences of harassment. Addressing these challenges is crucial for promoting gender equality and unlocking women's potential for growth. This research inspects women's mobility experiences and challenges and proposes potential improvements for bus rapid transit (BRT) Peshawar. Interviews were conducted for data collection, and statistical tools and methods were employed to analyze the results. The most common modes of travel to and from the BRT stations were walk (39%&45%) followed by Taxi/Rickshaw (32%each) and car/bike(15%&9%), respectively. Most users accessed the BRT system within a 3km radius (55%) and typically traveled during the daytime (56% from 6-10 am and 51%from 2-6 pm). The main challenges identified, mainly for the younger users, were harassment faced at stations (66%for 18-30 years and 52%for 31-45 years of age groups, respectively) while on the buses with 54%for <18 years and 56%for 18-30 years of age groups, respectively, with a visual type of harassment in major. The study highlights women's unique mobility challenges with Peshawar BRT. Addressing these issues can boost their education and economic prospects, as a major study sample was comprised of lower-income employees (80% having an income less than 40,000PKR*) and middle-aged students (48%). The findings provide valuable insights for BRT Peshawar and future BRT projects in developing countries. Despite separate seats, challenges persist during peak hours due to the absence of partitions between male and female sections within buses and other BRT amenities.

A Qualitative Study of Transportation-Related Barriers to HIV Care in South Carolina.

Addressing structural barriers to care for people living with human immunodeficiency virus (HIV) in the southern United States is critical to increase rates of viral suppression and to reduce existing HIV disparities. This qualitative study aimed to describe transportation-related barriers experienced by people living with HIV in South Carolina, understand perceived effects of transportation vulnerability on HIV care, and explore strategies used by individuals to overcome transportation-related challenges. We conducted semistructured interviews with 20 people living with HIV from South Carolina who were either reengaging in HIV care after a prolonged absence (>9 months) or in care but with a detectable viral load (ie, >200 copies/mL). All people living with HIV reported transportation vulnerability. A deductive/inductive approach was used to identify transportation-related barriers perceived to negatively affect HIV care. We also identified strategies and resources described by people living with HIV as helpful in addressing transportation challenges. Participants described a range of transportation-related barriers to HIV care, including lack of access to reliable, safe, and affordable transportation, as well as stigma due to HIV and socioeconomic statuses. These barriers were reported to negatively affect engagement in care and worsen both physical and mental health. Participants indicated flexible clinic policies and instrumental support from family and friends were useful in overcoming barriers. This study offers insight for the development of transportation interventions to improve equitable access to HIV care for people living with HIV in South Carolina. It also calls attention to the ways in which transportation vulnerability, HIV-related stigma, and disability status intersect to create unique challenges for some people living with HIV.