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Abstract Truck platooning comprises a number of trucks equipped with automated lateral and longitudinal vehicle control technology, which allows them to move in tight formation with short following distances. This study is an initial step toward developing an understanding of the occupant injury risks associated with the multiple sequential impacts between truck platoons and roadside safety barriers, regardless of whether the crash is associated with a malfunction of automated control or human operation. Full-scale crash impacts of a tractor-trailer platoon into a concrete bridge guardrail were simulated for a specific Test Level condition according to the Manual for Assessing Safety Hardware (MASH) standards. The model of the bridge barrier was developed based on its drawings, and material properties were assigned according to literature data.

Abstract Potential collisions with oncoming traffic while turning left belong to the most safety-critical situations accounting for ~25% of all intersection crossing path crashes. A Left Turn Assist (LTA) was developed to reduce the number of crashes. Crucial for the effectiveness of the system is the design of the human-machine interface (HMI), i.e. defining how the system uses the calculated crash probability in the communication with the driver. A driving simulator study was conducted evaluating a warning strategy for two use cases: firstly, the driver comes to a stop before turning (STOP), and secondly, the driver moves on without stopping (MOVE). Forty drivers drove through three STOP and two MOVE scenarios. For the STOP scenarios, the study compared the effectiveness of an audio-visual warning with an additional brake intervention and a baseline. For the MOVE scenarios, the study analyzed the effectiveness of the audio-visual warning against a baseline.

Abstract Sleep quality and maintenance of the optimal cognitive functioning is of crucial importance for aviation safety. Fatigue Risk Management (FRM) enables the operator to achieve the objectives set in their safety and FRM policies. As in any other risk management cycle, the FRM value can be realized by deploying suitable tools that aid robust decision-making. For the purposes of our article, we focus on fatigue hazard identification to explore the possible developments forward through the enhancement of objective tools in air transport operators. To this end we compare subjective and objective tools that could be employed by an FRM system. Specifically, we focus on an exploratory survey on 120 pilots and the analysis of 250 fatigue reports that are compared with objective fatigue assessment based on the polysomnographic (PSG) and neurocognitive assessment of three experimental cases.

Abstract Management of expressway networks has been mainly focused on defect management without looking at the correlations with accidental risks. This causes unsustainability in expressway infrastructure maintenance since such defects may not be a contributing factor toward public safety. Thus it is necessary to incorporate accidental events for decision-making in infrastructure management. This study has developed a novel approach to machine learning (ML) that incorporates actual primary data from the last 10 years of single-vehicle accidents (SVA) by collisions with motorway facilities, or so-called single-vehicle collisions with fixed objects. The ML is firstly aimed at identifying the influential factors of SVA in relation to finding effective countermeasures for accidents by integrating the correlation analysis, multiple regression analysis, and ML techniques. The study reveals that wet pavement conditions have a significant effect on SVA.

Abstract Purpose: Obesity can be a contributing factor to decrease head injuries in motor vehicle collisions (MVCs). We sought to assess whether obesity is associated with decreased head injury from MVCs by sex. Methods: This study was a retrospective observational study and evaluated crash data from 1997 to 2015 obtained from the International Center for Automotive Medicine. Patients were categorized into normal, overweight, and obesity subgroups. The primary endpoint was serious head injury. Multivariate logistic regression analysis was performed, and adjusted odds ratios (AORs) of subgroups were calculated for study outcomes adjusted for any potential confounders. Results: Among enrolled 588 patients, 262 were male with 30.9% normal, 40.1% overweight, and 29.0% obesity subgroups, and 326 were female with 44.8% normal, 24.8% overweight, and 30.4% obesity subgroups.

Abstract Modern driver compartment restraint systems have at least three key components that work together: safety belt system, airbags, and collapsible steering column. During a crash, a steering column will collapse at a predetermined force called breakaway force. Once the force of a crash has reached the breakaway force threshold, the column will move towards the motor area. When the column moves, the drivers’ peak forces and acceleration are decreased because the time and distance that are given to decelerate are increased. The usage of a breakaway force element inside the steering column allows car manufacturers to control the movement of the steering column at a certain point during a crash. Any load below the breakaway force, such as airbag deployment and normal or misuse forces applied by the driver, is absorbed by the system. Today’s force-based systems are optimized (design/configure) using various crash configurations, leading to one specific behavior of the column.

Abstract Brake systems are one of the essential components of vehicles ensuring the safety of roads and passengers as well as accident prevention. Faulty brake systems, however, can cause inevitable accidents. Fatality analysis reporting system of NHTSA (National Highway Transport Safety Association) has reported that heavy and light trucks, which are obliged to be equipped with dual-circuit air brake system, were, respectively, involved in 8.8% and 38.0% of fatal crashes in the United States, during 2017. Number of heavy vehicle accidents due to complete failure of brake system is far less than accidents due to deficiencies such as worn out brake linings, out-of-adjustment push rod strokes, and leak in the circuits. Severe leakages due to ruptured air hoses or punctured reservoir are highly unlikely to be replenished by compressor and would be distinguished through pressure indicator.

Abstract The frequency of video-capturing collision events from surveillance systems are increasing in reconstruction analyses. The video that has been provided to the investigator may not always include a clear perspective of the relevant area of interest. For example, surveillance video of an incident may have captured a pre- or post-incident perspective that, while failing to capture the precise moment when the pedestrian was struck by a vehicle, still contains valuable information that can be used to assist in reconstructing the incident. When surveillance video is received, a quick and efficient technique to place the subject object or objects into a three-dimensional environment with a known rate of error would add value to the investigation.

Abstract In recent years, to avoid the failure of the onboard perception system, intelligent vehicle infrastructure cooperative systems have been attracting attention in the field of autonomous vehicles. Using the perception technology of roadside sensors to provide supplementary traffic information for autonomous vehicles has become an increasing trend. Several roadside perception solutions select deep learning for three-dimensional (3D) object detection. However, deep learning methods have several issues and lack reliability in practical engineering applications. To tackle this challenge, this study proposes a pedestrian detection algorithm based on roadside Light Detection And Ranging (LiDAR) by combining traditional and deep learning algorithms. To meet real-time demand, Octree with region-of-interest (ROI) selection is introduced and improved to filter the background in each frame, which improves the clustering speed.

Abstract Due to their large volume structure, when a heavy vehicle encounters sudden road conditions, emergency turns, or lane changes, it is very easy for vehicle rollover accidents to occur; however, well-designed suspension systems can greatly reduce vehicle rollover occurrence. In this article, a novel semi-active suspension adaptive control based on AdaBoost algorithm is proposed to effectively improve the vehicle rollover stability under dangerous working conditions. This research first established a vehicle rollover warning model based on the AdaBoost algorithm. Meanwhile, the approximate skyhook damping suspension model is established as the reference model of the semi-active suspension. Furthermore, the model reference adaptive control (MRAC) system is established based on Lyapunov stability theory, and the adaptive controller is designed.

Abstract TOC

Abstract With the growing number of cross-sea flights, the occurrence of maritime-related accidents, which have a high fatality rate, has become increasingly critical. This study is aimed at highlighting the causes of maritime-related accidents and identifying the risk factors that led to fatal crashes in the period 2009-2019. A total of 207 maritime-related accidents, the final reports of which are available in the online database of the National Transportation Safety Board, were considered. The accident cause distribution was obtained from the final reports. A two-step approach, involving uni-variable and multi-variable analysis logistic regression, was implemented to select the significant risk factors from 27 parameters. Results showed that the four main causes of maritime-related accidents were personnel issues (69.6%), aircraft-related aspects (60.4%), environmental issues (36.7%), and organizational issues (3.9%).

Abstract As bicycle design continues to develop, consumers are not satisfied with just the convenience and power-saving features of bicycles, but they also demand a fancy appearance. To achieve dramatic deforming of bike frames, an extreme high-profile difference is required. Thus, this study used rotary swaging, which is the best forging method among shrink forming processes, as the preforming process. The tube diameter reduction rates of 0.28 and 0.31 were set as the main parameters, and the effects of feeding speed, feeding method, and friction factor on the formed tube were analyzed. The results indicated that a higher feeding speed results in a lower rate of tube thickness increase and a lower friction factor results in a lower rate of tube thickness increase. Regarding the effects of feeding methods, the automatic feeding method yielded better surface roughness than the manual method.

Abstract Numerous operational procedures regulate aerodrome ground traffic. Detailed solutions in these procedures often come from preventive recommendations formulated as a result of accident cause analysis. With time, the conclusions drawn based on incidents, i.e., events that did not result in material damage or casualties, are becoming increasingly significant. In this article, we propose a new method for determining the probability of an incident turning into an air accident, based on the example of aerodrome traffic operations. Premises conducive to an accident in the considered class of events depend on both human and physical factors. Thus a hybrid approach was applied. We used a fuzzy inference system to analyze the premises dependent on vehicle operators, while the simulation method was selected to examine the premises dependent on physical factors. Both were integrated using the technique of event trees with fuzzy probabilities (ETFP).

Abstract The driving safety performance of autonomous driving vehicles must be ensured before on-road implementation. Because it is not realistic to evaluate every single test condition in real-world traffic, computer simulation methods can be used. The driving safety performance can be evaluated by simulating various driving scenarios and calculating surrogate indicators representing dangerous collision risk. This study used a near-miss database and introduced a surrogate indicator that represents a potential risk in the driving scenarios for rear-end and cut-in collisions. The near-miss video database includes several driving scenarios experienced by human drivers, such as dangerous situations that lead to accidents, potentially dangerous situations that have a risk probability to escalate into dangerous situations, and normal driving situations. A skilled and attentive human driver foresees dangerous situations while driving and avoids them.

Abstract Safety is always a crucial aspect of developing autonomous systems, and the motivation behind this project comes from the need to address the traffic crashes occurring globally on a daily basis. The present work studies the coexistence of the novel rule-based behavioral planning framework with the five key advanced driver assistance system (ADAS) features as proposed in this article to fulfill the safety requirements and enhance the comfort of the driver/passengers to achieve a receding-horizon autopilot. This architecture utilizes data from the sensor fusion and the prediction module for the prediction time horizon of 2 s iteratively, which is continuously moving forward (hence, the receding horizon), and helps the behavior planner understand the intent of other vehicles on the road in advance.

Abstract The preeminent obligation of the automotive engineers, while designing a car, is to assure the driver’s well-being during any kind of impact by suppressing intrusions into the cockpit or minacious deceleration levels. Technologists and designers are advancing various modern active and passive safety systems to augment vehicle occupants’ safety. To mitigate the research and development expenditure in time and money, it is recommended to utilize computational crash simulations for the early evaluation of safety behavior under vehicle impact tests. Therefore, in this research study, an attempt is made to simulate crashworthiness and design the impact attenuator utilized in Formula SAE vehicles to absorb the kinetic energy of a car during a frontal collision. Closed-cell aluminum foam is selected as its material because of its less density than solid metals and ability to undergo large deformations at almost constant load.

Abstract Aircraft lift bag is the equipment used for the recovery of an aircraft and is considered as a lifting equipment. Boeing 737 is a domestic aircraft considered for designing this bag. The aircraft lift bag is made of composite material, and the most widely used materials are nylon and neoprene. A composite material is used to make the bag lightweight and easy to handle. For calculation of properties and the engineering constant of the respective composite materials, micromechanics approach is used, in which the method of Representative Volume Element (RVE) is taken into consideration. The loading and boundary conditions are the exact replica of the working conditions. The operation of this bag is completely pneumatic. The stresses induced in the bag are analyzed in finite element software and are compared with the calculated theoretical values. CATIA is used to model the bag, and ABAQUS is used for the finite element calculations.

Abstract Public discussions on the wide-scale implementation of connected and autonomous vehicles (CAVs) mostly rely on the media. As such, what is usually understood about “autonomous vehicle technology” by the general society is not necessarily equal to the current stage of the industrial production of “autonomous vehicles” in a similar timeline. To elaborate, society tends to have a misunderstanding about the technology where the autonomous vehicle (AV) is commonly perceived as a “vehicle with the highest level of automation” [1]. In reality, to enable a feasible, market-wide deployment of the technology, CAV technology, as a product, should be released to the market incrementally in a technologically realistic timeline. This unrealistic expectation and misunderstanding by the public, due to the aforementioned misapprehensions, subsequently puts impractical business expectations on engineering and development teams.

Abstract The growing interest from automakers and ride-hailing companies has increased the investment for high automation levels in vehicles. An important challenge in introducing autonomous vehicle (AV) technology to the market is the effort required in the validation. The research shows that AVs have to be test-driven hundreds of millions of miles to demonstrate reliability, which could take hundreds of years. Therefore, the identification of critical test scenarios and reduction of scenario sample space are urgent requirements for providing safe and reliable AVs in a time- and cost-efficient manner. This article proposes an AV test scenario generation system that creates abstract test scenarios using historical fatal accident data. The method processes and prunes the extensive fatal accident data to generate core test scenarios targeting the reasoning systems of AVs.