Search Results (22)

In this study, a novel methodology is proposed to evaluate automated driving safety in mixed traffic environments, including autonomous vehicles (AVs) and manually driven vehicles (MVs). An open-source AV dataset obtained from a real-world autonomous mobility testbed in Korea was used for methodology development and evaluations. The driving behavior was evaluated using well-known promising indicators, including the standard deviation of the vehicle speed, acceleration noise, standard deviation of the lane offset, time to collision (TTC), and deceleration to avoid a crash (DRAC). Min-max and max-min normalization was performed to unify the units of the evaluation indicators. The importance of each driving safety indicator was derived through the Analytical Hierarchy Process (AHP) performed by traffic experts, and the weights were estimated based on the average of the collected importance. The normalized indicators were integrated to obtain the automated driving risk score (ADRS), which is regarded as a measure of automated driving safety. The automated driving safety degraded considerably in road sections where right turns were made at intersections and that had a bus stop. Hazardous driving events of AVs were visualized, which is useful for monitoring mixed traffic safety and developing effective countermeasures for proactive road safety management. Full article

This work investigates the risk to Vulnerable Road Users (VRUs) from a novel light rail vehicle using the pedestrian impact scenario outlined in CEN/TR 17420. At a 20 km/h impact speed, a maximum head impact criterion (HIC₁₅) value of 15.9 was obtained for a 50th-percentile anthropometric test device (ATD), with this value increasing to 120.2 at 30 km/h impact speed. Both results are within the CEN/TR 17420 prescribed limit of 1000. In both cases, the vehicle does not fully comply with CEN/TR 17420 recommendations due to insufficient lateral displacement of the ATD post-impact. A vehicle front-end design—which would be exempt from the CEN/TR 17420 impact testing—was designed and tested to the same framework. Despite being formally exempt from testing, the design also did not fully comply with CEN/TR 17420 lateral displacement requirements. Critical evaluation of the CEN/TR 17420 framework is presented, leading to recommendations about how updated frameworks should take a pragmatic approach in how they define VRUs, and the measurement criteria used for assessing VRU risk in collisions. Discussions are presented considering whether alternative frameworks, such as the Bus Safety Standard, should be applicable to assess the safety of the novel light rail vehicle. Full article

Walking benefits older pedestrians but exposes them to traffic crashes. With an aging population, designing age-friendly cities is crucial, yet research on older pedestrian safety at a micro-level is limited. This study aims to reduce older pedestrian–vehicle collisions and create more livable environments through infrastructure policies derived from statistical data analysis. Special attention is focused on collecting a holistic set of infrastructure variables to reflect most of the street built environment elements, which helps policymakers implement short-term safety measures. Using Bayesian Poisson regression, this study analyzes factors contributing to the occurrence of crashes involving older and non-older pedestrians on road segments in Madrid, Spain. The results indicate that different factors affect the occurrence of crashes for all pedestrians versus older pedestrians specifically. Traffic crashes involving all pedestrians are affected by leisure points of interest, bus stops, and crosswalk density. Older pedestrian traffic crashes are influenced by population density, the presence of trees and trash containers, and contour complexity. Proposed measures include relocating trees and trash containers, modifying bus stops, and adding crosswalks and traffic lights. This paper also shows that these countermeasures, aimed at creating age-friendly streets for older pedestrians, are not expected to worsen the road safety of other pedestrians. Full article

The paper examines the integration of novel Transportation Ecology principles into transit operations, aiming to address the environmental impacts associated with surface services in urban areas and with the purpose of creating a comprehensive agenda for integrating ecological principles into transit planning and management. The research problem is to quantify the tangible benefits for transit operators, particularly in the context of mitigating wildlife-vehicle collisions and improving overall operational efficiency as a motivator for transit managers to adopt Transportation Ecology principles. The study design, after analyzing the regulatory requirements, implements scenario-based methodology, utilizing data from an average Italian bus fleet to estimate potential monetary savings and benefits. Key parameters, such as maintenance costs, insurance premiums, and collision-related expenses, are analyzed to provide a realistic assessment of the economic advantages of implementing Transportation Ecology measures. The findings reveal that significant cost reductions can be achieved by minimizing accidents involving wildlife, alongside other operational improvements. The scenario demonstrates that even a small fleet, when adopting these principles, can yield substantial financial benefits, thereby making a compelling case for broader implementation. The paper concludes that while the qualitative nature of the analysis necessitates conservative estimates, the results underscore the value of incorporating ecological considerations into transit planning and management. These insights are vital for transit operators and policymakers seeking to balance environmental sustainability with operational profitability and protect urban ecosystems. This also implies the need for a more holistic and interdisciplinary approach to transportation planning and management. Full article

Frontal crash tests are an essential element in assessing vehicle safety. They simulate a collision that occurs when the front of the bus hits another vehicle or an obstacle. In recent years, much attention has been paid to the frontal crash testing of city buses, especially after a series of accidents resulting in deaths and injuries. Unlike car manufacturers, most bus bodybuilders do not include deformation zones in their designs. The next two regulations are widely used to assess whether a structure can withstand impact loading: UNECE Regulation No. 29—United Nations Economic Commission for Europe (UNECE R29) and the New Car Assessment Program (NCAP), which is more typical of car crash tests. The main goal of the research is to develop an applicable methodology for a frontal impact simulation on a city bus, considering UNECE R29 requirements for the passenger’s safety and distinctive features of the low-entry body layout. Among the contributions to current knowledge are such research results as: unlike suburban and intercity buses, city buses are characterized by lower stiffness in the event of a frontal collision, and therefore, when developing new models, it is necessary to lay deformation zones (currently absent from most city buses). Maximum deformation values in the bus front part are reached earlier for R29 (137 ms) than for most impacts tested by NCAP (170–230 ms) but have higher values: 577 mm vs. 150–250 mm for the sills tested. Such a short shock absorption time and high deformations indicate a significantly lighter front part of a low-entry and low-floor bus compared with classic layouts. Furthermore, it is unjustified to use the R29 boundary conditions of trucks to attach the bus with chains behind its frontal axe both in natural tests and appropriate finite element simulation—the scheme of fixing the city bus should be accordingly adapted and normatively revised. Full article

Currently, ultrashort oligopeptides consisting of fewer than eight amino acids represent a cutting-edge frontier in materials science, particularly in the realm of hydrogel formation. By employing solid-phase synthesis with the Fmoc/tBu approach, a novel pentapeptide, FEYNF-NH₂, was designed, inspired by a previously studied sequence chosen from hen egg-white lysozyme (FESNF-NH₂). Qualitative peptide analysis was based on reverse-phase high performance liquid chromatography (RP-HPLC), while further purification was accomplished using solid-phase extraction (SPE). Exact molecular ion confirmation was achieved by matrix-assisted laser desorption–ionization mass spectrometry (MALDI-ToF MS) using two different matrices (HCCA and DHB). Additionally, the molecular ion of interest was subjected to tandem mass spectrometry (MS/MS) employing collision-induced dissociation (CID) to confirm the synthesized peptide structure. A combination of research techniques, including Fourier-transform infrared spectroscopy (FTIR), fluorescence analysis, transmission electron microscopy, polarized light microscopy, and Congo red staining assay, were carefully employed to glean valuable insights into the self-assembly phenomena and gelation process of the modified FEYNF-NH₂ peptide. Furthermore, molecular docking simulations were conducted to deepen our understanding of the mechanisms underlying the pentapeptide’s supramolecular assembly formation and intermolecular interactions. Our study provides potential insights into amyloid research and proposes a novel peptide for advancements in materials science. In this regard, in silico studies were performed to explore the FEYNF peptide’s ability to form polyplexes. Full article

Interest in advanced driver assistance systems (ADAS) is booming in recent years. One of the most effervescent ADAS features is blind spot detection (BSD), which uses radar sensors or cameras to detect vehicles in the blind spot area and alerts the driver to avoid a collision when changing lanes. However, this kind of BSD system fails to notify nearby vehicle drivers in this blind spot of the possible collision. The goal of this research is to design a proactive bus blind spot warning (PBSW) system that will immediately notify motorcyclists when they enter the blind spot or the area of the inner wheel difference of a target vehicle, i.e., a bus. This will increase the real-time functionality of BSD and can have a significant impact on enhancing motorcyclist safety. The proposed hardware is placed on the motorcycle and consists of a Raspberry Pi 3B+ and a dual-lens stereo camera. We use dual-lens cameras to capture and create stereoscopic images then transmit the images from the Raspberry Pi 3B+ to an Android phone via Wi-Fi and to a cloud server using a cellular network. At the cloud server, we use the YOLOv4 image recognition model to identify the position of the rear-view mirror of the bus and use the lens imaging principle to estimate the distance between the bus and the motorcyclist. Finally, the cloud server returns the estimated distance to the PBSW app on the Android phone. According to the received distance value, the app will display the visible area/blind spot, the area of the inner wheel difference of the bus, the position of the motorcyclist, and the estimated distance between the motorcycle and the bus. Hence, as soon as the motorcyclist enters the blind spot of the bus or the area of the inner wheel difference, the app will alert the motorcyclist immediately to enhance their real-time safety. We have evaluated this PBSW system implemented in real life. The results show that the average position accuracy of the rear-view mirror is 92.82%, the error rate of the estimated distance between the rear-view mirror and the dual-lens camera is lower than 0.2%, and the average round trip delay between the Android phone and the cloud server is about 0.5 s. To the best of our knowledge, this proposed system is one of few PBSW systems which can be applied in the real world to protect motorcyclists from the danger of entering the blind spot and the area of the inner wheel difference of the target vehicle in real time. Full article

This paper presents an efficient method for minimum distance calculation between a robot and its environment and the implementation framework as a tool for the verification of robotic systems’ safety. Collision is the most fundamental safety problem in robotic systems. Therefore, robotic system software must be verified to ensure that there are no risks of collision during development and implementation. The online distance tracker (ODT) is intended to provide minimum distances between the robots and their environments for verification of system software to inspect whether it causes a collision risk. The proposed method employs the representations of the robot and its environment with cylinders and an occupancy map. Furthermore, the bounding box approach improves the performance of the minimum distance calculation regarding computational cost. Finally, the method is applied to a realistically simulated twin of the ROKOS, which is an automated robotic inspection cell for quality control of automotive body-in-white and is actively used in the bus manufacturing industry. The simulation results demonstrate the feasibility and effectiveness of the proposed method. Full article

False Data Injection Attacks (FDIA) on ship Direct Current (DC) microgrids may result in the priority trip of a large load, a black-out, and serious accidents of ship collisions when maneuvering in the port. The key of the prevention of FDIA is the detection of and countermeasures to false data. In this paper, a defense strategy is developed to detect and mitigate against FDIA on ship DC microgrids. First, a DC bus voltage estimator is trained with an Artificial Neural Network (ANN) model. The error between the estimate value and the measure value is compared with a threshold generated from history data to detect the occurrence of FDIA. Combined with the correlation of artificial neural network inputs, bad data are identified and recovered. The method is tested under six cases with different network and physical disturbances in Matlab/Simulink. The results show that the method can identify and mitigate the FDIA effectively; the error of identifying FDIA by ANN is less than 0.5 V. Therefore, the deviation between the actual bus voltage and the reference voltage is less than 0.5 V. Full article

Accurate distance estimation is a requirement for advanced driver assistance systems (ADAS) to provide drivers with safety-related functions such as adaptive cruise control and collision avoidance. Radars and lidars can be used for providing distance information; however, they are either expensive or provide poor object information compared to image sensors. In this study, we propose a lightweight convolutional deep learning model that can extract object-specific distance information from monocular images. We explore a variety of training and five structural settings of the model and conduct various tests on the KITTI dataset for evaluating seven different road agents, namely, person, bicycle, car, motorcycle, bus, train, and truck. Additionally, in all experiments, a comparison with the Monodepth2 model is carried out. Experimental results show that the proposed model outperforms Monodepth2 by 15% in terms of the average weighted mean absolute error (MAE). Full article

The problem of large calculation models in bus–two-wheeled vehicle traffic accidents (TA) leads to the difficulty of balancing the calculation efficiency and accuracy, as well as difficulties in accident reconstruction. Herein, two typical accidents were reconstructed, based on the rigid–flexible coupled human model (HM) and the Facet vehicle model, and the vehicle damage conditions and the human head biomechanical injury were analyzed. The simulation results showed that the physical process of the human–vehicle collision was basically consistent with the accident video, the windshield fracture was consistent with the actual vehicle report, and the human biomechanical injury characteristics were also consistent with the autopsy report, which verified the feasibility of the simulation model, and provides a basis and reference for forensic identification and for traffic police to deal with accident disputes. Full article

Although the school bus is considered a safe form of transportation, school bus crashes are a major safety concern. School bus crashes are a result of driver error of either the at-fault school bus or another at-fault vehicle (where the school bus is not at fault). To examine the risk factors associated with school bus related crashes and crash outcomes, this study segments and develops two binary logit models for each school bus crash type. A total of 1702 school bus related crashes recorded between 2009 and 2016 were used to estimate the model. According to the model results, sideswipe collisions were less likely to result in injury outcomes for at-fault school buses than rear-end and side-impact collisions. Speeding, driving impaired or under the influence, and negotiating a curve all have significant positive associations with injury outcomes in not-at-fault school bus crashes. This study’s practical implications include enforcing the school bus safe driving guidelines, training programs for school bus drivers that include elements of nonroutine trips, training for crossing guards, and awareness programs for drivers of other vehicles to instill safe driving practices around school buses. Full article

Passengers in an apron bus are usually subjected to a standing position because of its limited seats and capacity. Due to this, passengers, especially those with mobility constraints, may expose themselves to musculoskeletal disorder (MSD) risks such as body pain, discomfort, and non-collision injuries. The purpose of this study is to design an ergonomic apron bus to aid the musculoskeletal discomfort experienced by passengers with mobility constraints, specifically the elderly, pregnant women, mothers carrying infants, and persons needing wheelchair assistance. A total of 149 participants are involved in the study. Corlett’s and Bishop’s body discomfort questionnaires and Rapid Entire Body Assessment (REBA) are utilized to evaluate the respondent’s experience of discomfort in different regions of their body. The results show that passengers with mobility constraints experience body discomfort during the apron bus ride. The prevalence of body discomfort is evident in the lower back, knee, thigh, arm, shoulder, and middle back. Finally, principles of anthropometry are used in the study along with quality function deployment (QFD), failure mode and effects analysis (FMEA), and cost-benefit analysis to evaluate the feasibility of the recommended ergonomic design of the apron bus. To meet the requirements of people with disabilities, the ergonomic design of an apron bus is created to minimize the risk of exposure of passengers to certain musculoskeletal discomfort, maximize the space, minimize the delay time of the airlines, and be able to prioritize passengers who require mobility assistance. Full article

The risky behaviours of bus drivers are of great concern to public health and environmental sustainability, especially for the buses operated between cities. With this in mind, the present study examined the distribution of risky behaviours among bus drivers, and the contributing factors to risky performance. To achieve this, 1648 records of GPS trajectory data and 8281 records of advance warning message data from Hong Kong–Zhuhai–Macau Bridge shuttle buses were obtained. The temporal and spatial distribution of risky behaviours was analysed. A random parameters negative binomial model was developed to further investigate the relationship between speed-related factors and risky behaviours. The results indicated that the warning of safety distance, lane departure, forward collision, and distraction were more likely to occur on weekdays. The period between 14 and 16 o’clock obtained the highest frequency of safety distance and lane departure warnings. Regarding the model estimation results, indicators reflecting average speed, acceleration, and number of trips per day showed a statistically significant impact on safety distance and lane departure warnings. Also, the acceleration of bus drivers showed a mixed impact on lane departure warnings. Corresponding implications were discussed according to the findings to reduce the frequency of risky behaviours in shuttle bus operations. Full article

Recently, there has been an increasing interest in targeting the safety of bus operations worldwide; however, little is known about the determinants of the bus crash severity in developing countries. By estimating an ordered logit model using the bus-involved collision data in Hanoi (Vietnam), spanning the period from 2015 to 2019, this study investigates various factors associated with the crash severity. The results reveal that the severity risk increases for (1) large buses, (2) raining conditions, (3) evening or night, (4) sparse traffic, (5) non-urban areas, (6) roads with at least three lanes, (7) curved roads, (8) two-way roads without a physical barrier, (9) head-on collision, and (10) pedestrian-related crashes. Aside from confirming the crucial roles of a wide range of factors, this research has examined the effects of two determinants (traffic density and crash area) that have not been considered for the cases of developing countries previously. Based on the findings on the impacts of factors, a series of policy recommendations regarding improving road conditions in non-urban areas, promoting walking infrastructure, reminders of high-risk situations for drivers, safety notes when improving bus service quality, and recording bus-related crashes are proposed. Full article