Transportation Safety Research Articles

Differentiating three distinct kinds of flaws in oil and gas pipelines derived from the spacing effect of capacitive imaging sensors

Purpose This paper aims to apply the spacing effect of capacitive imaging (CI) sensors to inspect and differentiate external flaws of the protective module, internal flaws of the protective module and external flaws of the metallic module in oil and gas pipelines simultaneously. Through experimental verification, a method for differentiating three distinct kinds of flaws derived from the spacing effect of CI sensors has been demonstrated. Design/methodology/approach A 3Dimensions (3D) model for simulating the inspection of these flaws was established by using COMSOL. A novel CI sensor with adjustable working electrode spacing was designed, and a modular CI system was developed to substantiate the theoretical findings with experimental evidence. A method for differentiating three distinct kinds of flaws derived from the spacing effect of CI sensors was established. Findings The results indicate that the method can successfully discriminate external flaws of the protective module, internal flaws of the protective module and external flaws of the metallic module using CI sensors. Originality/value The method for differentiating three distinct kinds of flaws derived from the spacing effect of CI sensors is vital for keeping the transportation safety of oil and gas pipelines.

Machine learning embedded hybrid MCDM model to mitigate decision uncertainty in transport safety planning for OAS countries

Providing defensible decisions is a prerequisite for methodologies of multi-criteria decision-making (MCDM) activities, and this is especially true for socio-economic analysis in public sector. This study proposes an all-in-one MCDM model with machine learning algorithms. The model integrates the method based on the removal effects of criteria (MEREC), combined compromise solution (CoCoSo), and density-based spatial clustering of applications with noise (DBSCAN), i.e., MEREC–CoCoSo–DBSCAN. In particular, the uniform manifold approximation and projection (UMAP) is implanted in DBSCAN to reduce the data dimensionality, and the k-nearest neighbors (KNN) algorithm is embedded to determine the inflection points (ɛ) and minPts in the data. This counters the inherent model failure of DBSCAN in dealing with high-dimensional data and eliminates the requirement for manual intervention in the model procedure, thereby fully avoiding potential human error and automating the computing process. A case study on benchmarking transport safety systems for member countries of the Organization of American States (OAS) demonstrates the reliability, adaptability, and efficiency of the proposed model. It moreover reflects its feasibility in resolving real-life socio-economic issues by offering valuable insights and potential solutions in economic investment and funding allocation in regard to transport safety strategy. Overall, this study provides government officials, managers, and policymakers with a valuable tool for handling MCDM activities in socio-economic development with considerable practicality and credibility.

ERGONOMIC AND LOGISTIC ENSURING THE REQUIREMENTS FOR THE COMFORT DURING THE ORGANIZATION OF PASSENGER TRANSPORTATION IN A SMALL-CAPACITY BUS

Purpose. The most important advantage of passenger transport by road is the high quality of transport service, which depends on the organization of the transport process, structural features and technical condition of the rolling stock used and the route, the development of the route network and other factors. Comfort reflects the properties of bus passenger transportation, which lead to the creation of the necessary service conditions and convenience for passengers in the bus, at the start-end and transit points on the basis of regulatory documents approved in the prescribed manner. Features of the design of small-capacity buses in terms of comfort and safety of passenger transportation and provision of proper travel conditions mostly determine the scope of use of buses of this class by types of connections and length of routes. The purpose of the paper is the development of a structural model, based on the analysis of the main factors affecting the determination of the comfort of a small-capacity bus for urban transportation during the transportation of passengers. Methods. The analysis of literary sources showed that indicators of comfort (as well as indicators of information service, speed, timeliness, safety of cargo, safety), which refer to indicators of the quality of passenger transportation, are decisive in this group of indicators. From the point of view of Ukrainian legislation and regulatory framework, the concepts of passenger bus capacity and comfort are analyzed. The main factors that determine the comfort of small-capacity buses for urban transportation during the transportation of passengers are determined. Ensuring the comfort of passenger transportation in a small-capacity city bus is determined by compliance with ergonomic requirements, which, in turn, depends on the design features of the arrangement of the area intended for passengers. Scientific novelty. It is proposed to evaluate the comfort category in the urban public road transport system using a structural model that combines two sets of factors – logistic and ergonomic. The logistic set of factors includes characteristics in time and space, that is, characteristics of comfort outside the means of urban public road transport. The ergonomic set of factors includes characteristics that describe comfort in vehicles. Practical significance. On the basis of this model, possible ways of ensuring ergonomic requirements for the layout of the interior and interior of small-capacity buses for urban passenger transportation are proposed. It was established that the main factors of the redistribution of transport mobility between urban passenger transport and transport for individual use are the insufficient comfort of passenger transport or the insufficient density of the route network.

Perceptions of Service Enhancements in Shared Autonomous Vehicles: A Demographic Perspective

As the pressure on urban mobility rises, shared autonomous vehicles (SAVs) offer enhanced transportation efficiency and safety. This study investigates the valuations of additional services in SAVs, examining demographics’ impact on preferences for different service features. We use data from 1723 Norwegian respondents to an online survey. We find that women put increased value on a safety host. Younger respondents value fast travel time. More tech-savvy individuals showing a higher valuation for services enhancing personal utility and comfort. Intention to use strongly predicts valuation of utilities, but not social factors.

Remote control of the technical condition of metro trains using seismological tools

As urban road congestion increases and people shift to using the subway, the safety of under-ground transportation becomes a priority. Therefore, it is necessary to establish a monitoring sys-tem for subway trains to detect malfunctions that occur during operation. The article proposes an engineering seismology method for remote monitoring of the technical condition of metro trains based on the analysis of micro seismic vibrations. This method allows remote control of the dynamic parameters of each train and their deviations from the norm. The authors demonstrate how a seismic recorder placed in a building adjacent to a metro station can be used to monitor changes in the amplitude-frequency spectrum of vibro seismic recordings. It is used to determine the arrival and departure times of trains, and it is shown that observations are best made for departures due to their more pronounced signal amplitude. The recorded signal of a metro train should fall within a certain frequency range, which is determined based on its average values, and any deviation of the observed signal spectrum from this norm indicates changes in the train's condition. The proposed approach not only helps improve passenger safety, but also reduces the risk of emergencies associated with technical malfunctions of rolling stock. In the future, it is possible to develop software equipped with a database of statistical data, which will allow even more efficient control of metro operations and prompt response to any deviations, thus ensuring a high level of safety and comfort for passengers.

Evaluation of the strength of the truck tractor’s frame under emergency braking conditions

Authors carried out a theoretical study of the force impact during emergency braking on the strength of the frame of a truck tractor as a part of a road train with a semi-trailer in order to build a model of the dependence of the safety factor index of the frame on the geometric and weight parameters of the car, semi-trailer, transported cargo and the type of the pavement. Using D'Alembert's principle, a generalized calculation scheme of the frame of the semi-trailer and the truck unit after reaching a steady deceleration during emergency braking while maintaining straight-line movement and adhesion of all wheels to pavement was made. Through a static calculation, the dependences for the unknown reactions of the car frame constraints were obtained, its dangerous cross-section was established, and the condition for the static strength of the longeron was determined. Using this condition and the obtained ratios for active and reactive loads, a model of the dependence of the safety margin coefficient of the car frame on the road train parameters was built. By the example of a road train consisting of a KrAZ-6446 truck tractor and a VARZ-6006 semi-trailer the application of the constructed model for evaluating the strength of the car frame and determining the permissible safe zone location of the center of gravity of different weights cargo in the plane of the road train is demonstrated. The method proposed in this work and the built model can be used to study the strength of the frames of truck tractors and semi-trailers of other manufacturers and types and to establish safe schemes for the placement and fastening of loads to ensure the operational reliability of the vehicle and the safety and security of cargo transportation.

Impact of AIS Manipulation on Shipping Safety and Strategic Countermeasures

Impact of AIS Manipulation on Shipping Safety and Strategic Countermeasures

Enhancing security through continuous biometric authentication using wearable sensors

The paper presents a novel approach for biometric continuous driver authentication (CDA) for secure and safe transportation using wearable photoplethysmography (PPG) sensors and deep learning. Conventional one-time authentication (OTA) methods, while effective for initial identity verification, fail to continuously verify the driver’s identity during vehicle operation, potentially leading to safety, security, and accountability issues. To address this, we propose a system that employs Long Short-Term Memory (LSTM) models to predict subsequent PPG values from wrist-worn devices and continuously compare them with real-time sensor data for authentication. Our system calculates a confidence level representing the probability that the current user is the authorized driver, ensuring robust availability to genuine users while detecting impersonation attacks. The raw PPG data is directly fed into the LSTM model without pre-processing, ensuring lightweight processing. We validated our system with PPG data from 15 volunteers driving for 15 min in varied conditions. The system achieves an Equal Error Rate (EER) of 4.8%. Our results demonstrate that the system is a viable solution for CDA in dynamic environments, ensuring transparency, efficiency, accuracy, robust availability, and lightweight processing. Thus, our approach addresses the main challenges of classical driver authentication systems and effectively safeguards passengers and goods with robust driver authentication.

Design of a Path-Following Controller for Autonomous Vehicles Using an Optimized Deep Deterministic Policy Gradient Method

The need for a safe and reliable transportation system has made the advancement of autonomous vehicles (Avs) increasingly significant. To achieve Level 5 autonomy, as defined by the Society of Automotive Engineers, AVs must be capable of navigating complex and unconventional traffic environments. Path-following is a crucial task in autonomous driving, requiring precise and safe navigation along a defined path. Traditional path-tracking methods often rely on parameter tuning or rule-based approaches, which may not be suitable for dynamic and complex environments. Reinforcement learning has emerged as a powerful technique for developing effective control strategies through agent-environment interactions. This study investigates the efficiency of an optimized Deep Deterministic Policy Gradient (DDPG) method for controlling acceleration and steering in the path-following of autonomous vehicles. The algorithm demonstrates rapid convergence, enabling stable and efficient path tracking. Additionally, the trained agent achieves smooth control without extreme actions. The performance of the optimized DDPG is compared with the standard DDPG algorithm, with results confirming the improved efficiency of the optimized approach. This advancement could significantly contribute to the development of autonomous driving technology.

Molecular insights into the synergistic inhibition mechanisms of antifreeze protein and methanol on carbon dioxide hydrate growth

The formation of CO2 hydrates during CO2 transportation and deep-sea injection poses a significant risk of pipeline blockage. Combining kinetic (KHIs) and thermodynamic hydrate inhibitors (THIs) serves as a promising efficient and economical strategy to mitigate this issue, whose performance and microscopic mechanisms yet are still poorly understood. This study employs molecular dynamics simulations to explore the effects of the combination of winter flounder antifreeze protein (wf-AFP) as a KHI and methanol as a THI on CO2 hydrate growth. We find that methanol and wf-AFP exhibit an intriguing synergistic inhibition performance on hydrate growth. In the AFP-only system, AFP serves as a spatial hindrance near the hydrate growth interface. However, in the AFP + methanol system, AFP changes its position due to the attractive force of methanol. Part of the AFP fragment remains on the hydrate interface, while the rest surrounds the CO2 droplet. Methanol, in addition to disrupting the water structure, combines with AFP to act as a double barrier to CO2 dissolution into the aqueous solution, thereby significantly reducing the gas source for hydrate growth. These findings provide molecular-level insights into hydrate inhibition mechanisms and guide the design of efficient inhibitors for safe CO2 transportation and injection.

Blind assistance system for appliance control and public transport safety using CNN, MobileNet V2 and Yolo V8

The purpose of this research is to address the challenges faced by visually impaired individuals, particularly in handling household appliances independently. With approximately 285 million visually impaired individuals worldwide, technological solutions are crucial to enhancing their accessibility and independence. This paper introduces a Smart Assistance System designed to empower visually impaired individuals to interact with household appliances in real-time without assistance. In this study, three Convolutional Neural Network (CNN) algorithms are compared to develop the system. The evaluation metrics include accuracy, precision, recall, F1 score, and hamming loss on validation images. The performance comparison reveals that the custom architecture CNN, MobileNetv2, and YOLO models achieve F1 scores of 0.43, 0.63, and 0.24, respectively. To enhance object detection and classification, the paper suggests implementing bounding box buttons categorization using YOLOv8, which demonstrates superior performance with a 95% classification accuracy on testing images of home appliance buttons. They face similar difficult while in public and accessing public property. Expanding upon the proposed system’s capabilities, the paper introduces the concept of panic button detection and activation in a bus environment tailored for blind individuals. This system relies on various factors such as the number of people onboard, heart rate monitoring, and the detection of distress signals or SOS sounds emitted by the user. By integrating advanced sensing technologies and intelligent algorithms, this panic button detection system aims to provide prompt assistance and ensure the safety of visually impaired passengers in public transportation settings.

Sulfide stress corrosion cracking in L360QS pipelines: A comprehensive failure analysis and implications for natural gas transportation safety

This research investigates the severe weld failures in L360QS pipelines, which are integral to the infrastructure of high-pressure natural gas transportation systems. Even with strict compliance to engineering standards, two pivotal welds experienced sulfide stress corrosion cracking (SSCC) due to continuous exposure to hydrogen sulfide and stresses from construction activities. A comprehensive material analysis and stress simulation has been utilized, revealing a maximum stress concentration of 544.9 MPa that surpasses the yield strength of the pipeline material. This discovery prompts a reevaluation of current safety margins and underscores the urgent need for enhanced pipeline integrity management. Our findings, corroborated by stress distribution simulations, not only illuminate the complex interplay of material properties and environmental factors in SSCC but also provide a new perspective for the safe service of pipeline.

Exploring the factors hindering the intention to adopt sustainable transportation options in Addis Ababa, Ethiopia: using structural equation modeling

With poor transportation infrastructure and increased reliance on motorization, fast-growing cities in the Global South that are experiencing rapid urbanization have received less attention in terms of sustainable transportation research. In this regard, it is imperative to support active mobility and public transit that help to reduce vehicle emissions, traffic congestion, road fatalities, and energy depletion while supporting public health, robust economies, and social equity. However, in the emerging cities context, the adoption of sustainable transportation options are constrained by various factors. This study aims to explore the key factors hindering the adoption of sustainable transportation options in Addis Ababa, Ethiopia. To do so, travel survey data were gathered from 720 households using stratified sampling and analyzed using factor analysis. The results from factor analysis indicated five groups of factors hindering residents’ intention to adopt sustainable transportation options, including (1) infrastructure condition, (2) modal characteristics, (3) land use pattern, (4) policy framework, and (5) technology-related factors. The confirmatory factor analysis also depicts the five latent factors and the contributions of observed variables that are statistically significant (p < 0.01). More specifically, observed variables such as (i) inadequate pedestrian facilities, (ii) lack of bike facilities, (iii) poor public transit facilities, (iv) limited availability of reliable public transport, (v) long wait times, (vi) high public transport fare, (vii) discomfort, (viii) safety and security issues are the most significant factors. Another set of factors includes (ix) walking distance, (x) dispersed land use pattern, (xi) poor land use mix, (xii) inadequate policy support, and (xiii) lack of real-time information. Furthermore, the intention to adopt sustainable modes of transportation is influenced by socio-demographic characteristics such as gender, age, educational status, income, family size, and car ownership. The result contributes to the existing literature by providing insight into adopting sustainable transportation modes in emerging cities like Addis Ababa, which are characterized by several urban transportation challenges.

Design Features of a Removable Module for Securing Containers in Gondola Cars

Purpose. The main purpose of the study is to highlight the design features of the design of a removable module for fastening containers in gondola cars. Methodology. For the safe transportation of containers in gondola cars, it is proposed to use a removable module. This module operates on the principle of an intermediate adapter between the container and the open wagon body. The choice of the profiles of the beams of the frame of the removable module was made according to the moments of resistance of their components. To do this, the core system of the removable module frame was constructed and calculated using the Lira CAD software package. According to the maximum bending moment acting in the module frame due to the moment of resistance and the known permissible stresses, the profile of the frame beams was selected. Taking into account the selected profile of the frame, its spatial model was built and strength calculations were performed. The finite element method implemented in SolidWorks Simulation was used for strength calculations. The calculation was carried out for two loading schemes of the removable module: the effect of a vertical load and the effect of vertical and longitudinal loads. Findings. Based on the calculation, the profile of the removable module was selected according to the determined value of the resistance moment - a square pipe with a height and width of 300 mm and a wall thickness of 5 mm. The results of the strength calculations of the removable module showed that for the case of its perception of a vertical load, the maximum stresses are 112.5 MPa. The maximum displacements occur in the upper parts of the superstructures and are about 1 mm. For the case of the vertical and longitudinal loads perceived by the removable module, the maximum stresses in its structure amounted to 287.6 MPa. The maximum displacements occurred in the end superstructure located on the side of the load applied to the removable module. These displacements amounted to 2.16 mm. Thus, the strength of the removable module for the considered loading schemes is ensured. Originality. A scientific approach to the design of a removable module for securing containers in gondola carsis proposed. Practical value. The research will contribute to the creation of recommendations for the design of modular-type vehicle structures, as well as to improving the efficiency of railway transport operation.

Incident reporting and data monitoring of sexual violence and harassment on public transport

IntroductionSexual violence and harassment occur in different settings, including public transport, and cause significant harm to victim-survivors' mental and physical health. While sexual violence and harassment on public transport is a documented problem, the public transport sector uptake has been slow and the true prevalence of sexual violence and harassment on public transport is yet to be determined. We aimed to investigate existing public transport and key stakeholder data systems, and explore the views of service providers, to ultimately improve sexual violence and harassment incident reporting and data monitoring. MethodsUsing a mixed methods design, researchers worked with public transport providers and other interested stakeholders in one Australian state. Twelve organizations were involved in the project and six provided current data on public transport safety for analysis. An audit of public transport and stakeholder websites was also undertaken to assess sexual violence and harassment incident reporting pathways. In addition, seven managers from five public transport organizations were interviewed to capture views on gender sensitive data collection and monitoring, and the challenges and enabling factors facing the sector. ResultsThe results uncovered varied sexual violence and harassment reporting formats and subsequent limited reporting of sexual violence and harassment incidents on public transport. In addition, poor-quality data sets lacked gender sensitivity, comprehensiveness, comparability, reliability and accessibility. Three key themes from public transport providers, on sexual violence and harassment data collection included increasing incident reporting, barriers and enablers of collecting and analysing quality data and governance frameworks. A minimum data set collection tool has been developed and could be tested in future. ConclusionTo improve women's safety on public transport, enhanced gender-sensitive data collection and monitoring is required. Long term government investment in sexual violence and harassment primary prevention strategies on public transport are urgently needed.

Oil and gas pipeline robot localization techniques: A review

Globally, pipelines are the primary means for transporting resources. To ensure the safety and reliability of pipeline transportation, it is essential to regularly use pipeline robots for inspections. Localization techniques for these robots are critical as they determine the real-time position and status of the robot inside the pipeline, playing an extremely important role in pipeline operations. Understanding the latest research trends in pipeline robot localization techniques can help advance the overall development of the pipeline field and reduce the potential for research duplication. This paper reviews the global developments in pipeline robot localization techniques over the past decade, categorizing them into three major methods: in-pipe localization, out-of-pipe localization and multi-source information fusion localization. It analyzes the fundamentals, strengths and weaknesses of eight major localization techniques for pipeline robots, identifies the current limitations and solutions in these technologies, discusses the field test analysis and practical design factors, and anticipates the open research challenges and future prospects of this field.

Deep encoder-decoder networks for belt longitudinal tear detection

The belt conveyor is susceptible to longitudinal tearing, which poses a serious threat to the safety of coal mines. Traditional methods for detecting longitudinal tears have limitations such as poor image quality, limited applicability, and high hardware costs. An improved encoder-decoder network was proposed to solve the longitudinal tear detection problem. This method utilizes a line structured light system for image acquisition. The input images are downscaled using a sorting algorithm to extract the information of pixels with high grayscale values as the input feature map for the neural network. The reduced-dimensional encoder-decoder network then semantically segments the input feature map, and the resulting pixel segmentation is mapped to the location of the longitudinal tear. Finally, the position and length of the tear are calculated by back-projecting the semantic segmentation result to the world coordinate system. Experimental results demonstrate that this method effectively reduces hardware resource consumption and improves detection speed. The DICE and MIOU scores for the improved network are 97.69% and 95.47%, respectively, while the recall and precision for improved detection are 96.60% and 95.67%, respectively. Therefore, this method can successfully monitor longitudinal tear failures and ensure the safety of transportation.

Implementation of smart mobility and relationship with transportation planning and regional development: A case study of South Tangerang city

Urbanization and suburbanization have led to high population growth in certain city regions, resulting in increased population density and mobility. Therefore, there is a need for a concept to address congestion, public transportation, information and communication systems, and non-motorized vehicles. Smart mobility is a concept of urban development as part of the smart city concept based on information and communication technology. Through this concept, it is expected that transportation services will be easily accessible, safe, comfortable, fast, and affordable for the community. This research aims to analyze smart mobility and its relationship with regional transportation planning and the development of South Tangerang, as well as to design a policy strategy model for the planning and development of South Tangerang with smart mobility. The research method used in this study is a mixed method, including analyzing the relationships and weighting of relationships between variables using the Cross Impact Multiplication applied to a classification (MICMAC) matrix. Multi-criteria decision analysis (MCDA) with Promethee software is also used to obtain the necessary policies. The results of this research indicate that the measurement of relationships between variables shows that smart mobility influences regional transportation planning, smart mobility affects regional development, and regional planning affects regional development. This research also provides alternative policies that policymakers should implement in a specific order. First, ensure the availability of public transportation; second, improve public transportation safety; third, enhance public transportation security; fourth, improve public transportation routes; fifth, provide real-time information access; sixth, improve transportation schedules; and seventh, increase the number of bicycle lanes.

Leveraging Community Pharmacies to Address Social Needs: A Promising Practice to Improve Healthcare Quality.

Emerging research suggests that chronic conditions such as cardiovascular disease, diabetes, and asthma are often mediated by adverse social conditions that complicate their management. These conditions include circumstances such as lack of affordable housing, food insecurity, barriers to safe and reliable transportation, structural racism, and unequal access to healthcare or higher education. Although health systems cannot independently solve these problems, their infrastructure, funding resources, and well-trained workforce can be realigned to better address social needs created by them. For example, community pharmacies and the professionals they employ can be utilized and are well-positioned to deliver balanced, individualized clinical services, with a focus on the whole person. Because they have deep roots and presence in the community, especially in under-resourced neighborhoods, community pharmacies (independent and chain) represent local entities that community members recognize and trust. In this article, we provide case examples from California, United States, to illustrate and explore how community pharmacies can be leveraged to address patient social needs as part of their core responsibilities and overall strategy to improve healthcare quality.

Multilateral collaborative governance of Arctic shipping safety: Examining the impact of the Arctic Council via collaborative network analysis

Global climate change has dramatically reduced Arctic sea ice, opening new potential shipping routes, which has garnered international attention. This study explores the role of the Arctic Council in the collaborative governance network focused on Arctic shipping safety. For this purpose, a collection of 49 collaborative events initiated by international organisations and the Arctic Council was used as the data sample. These events are divided into two groups, one containing all the events and the other excluding those initiated by the Arctic Council. As a result, two collaborative networks are developed and evaluated based on network density, average path length, network transitivity, centrality indices (degree, closeness, betweenness), and clustering analysis. The results demonstrate that the Arctic Council significantly enhances the network density and transitivity of the international collaboration network, and reshapes core-periphery dynamics and cohesive subgroup structures. For instance, under the influence of the Arctic Council, Canada, France, and Japan surpass the United Kingdom in centrality (degree, closeness, betweenness). Results of the clustering coefficients reveal the Arctic Council's impact on connections among states, leading to shifts in collaboration patterns. Additionally, subgroup cohesion and density coefficients confirm the Arctic Council's role in promoting collaboration among states and restructuring governance networks.