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With the current trend of including the evaluation of the risk of brain injuries in vehicle crashes due to rotational kinematics of the head, two injury criteria have been introduced since 2013 – BrIC and DAMAGE. BrIC was developed by NHTSA in 2013 and was suggested for inclusion in the US NCAP for frontal and side crashes. DAMAGE has been developed by UVa under the sponsorship of JAMA and JARI and has been accepted tentatively by the EuroNCAP. Although BrIC in US crash testing is known and reported, DAMAGE in tests of the US fleet is relatively unknown. The current paper will report on DAMAGE in NCAP-like tests and potential future frontal crash tests involving substantial rotation about the three axes of occupant heads. Distribution of DAMAGE of three-point belted occupants without airbags will also be discussed. Prediction of brain injury risks from the tests have been compared to the risks in the real world.

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Over the past decade, significant progress has been made in developing algorithms and improving hardware for automated driving. However, conducting research and deploying advanced algorithms on automated vehicles for testing and validation remains costly, especially for academia. This paper presents the efforts of our research team to integrate the newest version of the open-source Autoware software with the commercially available DataSpeed Drive-by-Wire (DBW) system, resulting in the creation of a versatile and robust automated vehicle research platform. Autoware, an open-source software stack based on the 2nd generation Robot Operating System (ROS2), has gained prominence in the automated vehicle research community for its comprehensive suite of perception, planning, and control modules. The DataSpeed DBW system directly communicates with the vehicle's CAN bus and provides precise vehicle control capabilities.

Autonomous driving technology is more and more important nowadays, it has been changing the living style of our society. As for autonomous driving planning and control, vehicle dynamics has strong nonlinearity and uncertainty, so vehicle dynamics and control is one of the most challenging parts. At present, many kinds of specific vehicle dynamics models have been proposed, this review attempts to give an overview of the state of the art of vehicle dynamics models for autonomous driving. Firstly, this review starts from the simple geometric model, vehicle kinematics model, dynamic bicycle model, double-track vehicle model and multi degree of freedom (DOF) dynamics model, and discusses the specific use of these classical models for autonomous driving state estimation, trajectory prediction, motion planning, motion control and so on.

To address the issue of PID control for automotive vibration, this paper supplements and develops the evaluation of automotive vibration characteristics, and proposes a vibration response quantity for evaluating the energy dissipation characteristics of automotive vibration. A two-degree-of-freedom single wheel model for automotive vibration control is established, and the conventional vibration response variables for ride comfort evaluation and the energy consumption vibration response variables for energy dissipation characteristics evaluation are determined. This paper uses the Adaptive Differential Evolution (ADE) algorithm to tune the PID control parameters and introduces an adaptive mutation factor to improve the algorithm's adaptability. Several commonly used adaptive mutation factors are summarized in this paper, and their effects on algorithm improvement are compared.

Considering the current trend towards the electrification of commercial vehicles, the development of Beam eAxle solutions has become necessary. The utilization of an electric drive unit in heavy-duty solid axle-based commercial vehicles presents unique and demanding challenges. These include the necessity for elevated peak and continuous torque while meeting packaging constraints, structural integrity requirements, and extended service life. One such solution was developed by BorgWarner to address these challenges. This paper offers a comprehensive overview of the design and development process undertaken for this Dual Motor Beam eAxle system. This includes the initial comparison of various eAxle solutions, the specifications of components selected for this design, and the initial results from dyno and vehicle development.

Recently, with the advancement of autonomous driving technology, the function of external lamps has been changed. Previously, the focus was on the visibility of drivers, but with the advancement of autonomous driving technology, the concept of autonomous driving systems has been developed. Accordingly, the trend of automotive lamp lighting systems has been developed in terms of design, e-HMI (exterior-human machine interface), It is developing in accordance with three major fields such as sensor connection. Therefore, this paper will cover the prior development of road content projection headlamps that enable e-HMI implementation to reflect these new trends. Since the technology is mass-produced and sold by several manufacturers, our company also needs to quickly develop and apply the technology in advance. Only four types of symbols are allowed in European law.

To ensure adequate visibility without excessive glare, vehicle headlights are designed to use a specific source of illumination. The optical designs of headlights gather the luminous flux produced by the light source to produce a useful beam pattern that meets the relevant requirements and standards for vehicle forward lighting. With the advent of solid state, light emitting diode sources for general illumination, an increasing number of LED replacement headlight bulb products has emerged over the past decade. In most cases, these LED replacement bulbs are not permitted for legal use on public roadways, but some countries have begun to permit specific LED replacement bulbs to be used legally on the road for specific makes, models and production years of certain vehicles. If they can be demonstrated to produce a beam pattern that meets the photometric requirements for a legal headlight, they are permitted to be used legally for on-road use.

A systematic review based on the PRISMA protocol was used to evaluate compounds developed for 3D printing with the incorporation of cellulose nanofibrils into polymers to be used in the automotive sector. The processing parameter is a data of great relevance for the development of durable structural parts and this study can be carried out using the state of the art on this subject. This way, the research was carried out using a search strategy from three different databases (Web of Science, Scopus and Science Direct) limiting studies between the years 2019 and 2023. The keywords used in these searches were: "3D Print" OR "FDM" OR "Fused Deposition Modeling" OR "FFF" OR "Fused Filament Fabrication" AND "Natural Nanofiber" OR "Natural Nanofibril" OR "Cellulose Nanofiber" OR "Cellulose Nanofibril". The same criteria described were also used to search for patents on the PatentScope, Google Patents and Espacenet platforms.

Diffuse Axonal Injury (DAI) is the most common type of traumatic brain injury, and it is associated with the linear and rotational accelerations resulting from head impacts, which often occurs in traffic related and sports accidents. To investigate the degree of influence of linear and rotational acceleration on DAI, a two-factor, two-level rat head impact experimental protocol involving linear and rotational acceleration was established using the L4(23) orthogonal table in this paper. Following the protocol, rats head was injured and diffusion tensor imaging (DTI) was performed at 24h post-injury to obtain the whole brain DAI injury, and the fractional anisotropy (FA) value of the corpus callosum was selected as the evaluation indicator. Using analysis of variance, the sum of squared deviations for the evaluation indicators was calculated to determine the degree of influence of linear acceleration and rotational acceleration on DAI. The results show that, 1.

The head injury mechanisms of occupants in traffic accidents will be more complicated due to the diversified seating postures in autonomous driving environments. The injury risks and assessment parameters in complex collision conditions need to be investigated thoroughly. Mining the simulation data by the support vector machine (SVM) and the random forest algorithms, some head injury predictive models for a 6-year-old child occupant under a frontal 100% overlap rigid barrier crash scenario were developed. In these head injury predictive models, the impact speed and sitting posture of the occupant were considered as the input variables. All of these head injury predictive models were validated to have good regression and reliability (R2>0.93) by the ten-fold cross-validation. When the collision speed is less than 60km/h, rotational load is the primary factor leading to head injury, and the trends of BrIC, von Mise stress, Maxshear stress, and MPS are similar.

Wrap around distance (WAD) is an important index to evaluate the contact position between pedestrian head and vehicle, and is also one of the key parameters of pedestrian accident reconstruction. The purpose of this paper is to explore whether the pedestrian headform testcan reflect the distribution of head injury in the real world. Firstly, in order to study the distribution of pedestrian head WAD in road accidents in China, a head WAD prediction model was established using logistic regression based on pedestrian height and vehicle collision speed. Secondly, in order to study the distribution of the risk of severe head injuries among pedestrians in accidents, the frequency of pedestrian head impact and the proportion of pedestrian head injury were counted respectively for sedans and SUVs. Subsequently, a risk curve for severe head injuries was constructed based on the head impact frequency and the proportion of severe injuries, utilizing a method that incorporates joint probability.

The use of hydrogen in internal combustion engines is an effective approach to significantly support the reduction of CO2 emissions from the transportation sector using technically affordable solutions. The use of direct injection is the most promising approach to fully exploit hydrogen potential as a clean fuel, while preserving targets in terms of power density and emissions. In this frame, the development of an effective combustion system largely relies on the hydrogen-air mixture formation process, so to adequately control the charge stratification to mitigate pre-ignitions and knock and to minimize NOx formation. Hence, improving capabilities of designing a correct gas jet-air interaction is of paramount importance. In this paper the analysis of the evolution of a high-pressure gas jet produced by a single-hole prototype injector operated with different pressure ratios is presented.

Hood insulators are widely used in automotive industry to improve noise insulation, pedestrian impact protection and to provide aesthetic appeal. They are attached below the hood panel and are often complex in shape and size. Pedestrian head impacts are highly dynamic events with a compressive strain rate experienced by the insulator exceeding 300/s. The energy generated by the impact is partly absorbed by the hood insulators thus reducing the head injury to the pedestrian. During this process, the insulator experiences multi-axial stress states. The insulators are usually made of soft multi-layered materials, such as polyurethane or fiberglass, and have a thin scrim layer on either side. These materials are foamed to their nominal thickness and are compression molded to take the required shape of the hood. During this process they undergo thickness reduction, thereby increasing their density.

Symbolic code execution is a powerful cybersecurity testing approach that facilitates the systematic exploration of all paths within a program to uncover previously unknown cybersecurity vulnerabilities. This is achieved through a Satisfiability Modulo Theory (SMT) solver, which operates on symbolic values for program inputs instead of using their concrete counterparts. However, in complex code bases, this approach faces significant limitations, such as program path explosions or unavailable dependencies, which can result in conditions that the SMT solver cannot reason about. Consequently, SMT solvers are often considered as too costly to implement for automotive testing use cases and are rarely employed within this domain. In contrast, fuzz testing has recently gained traction in the automotive industry as an invaluable testing technique for identifying previously unknown vulnerabilities. Its initial setup is straightforward and typically yields useful findings.

The world is on a “take-make-waste,” linear-growth economic trajectory where products are bought, used, and then discarded in direct progression with little to no consideration for recycling or reuse. This unsustainable path now requires an urgent call to action for all sectors in the global society: circularity is a must to restore the health of the planet and people. However, carbon-rich textile waste could potentially become a next-generation feedstock, and the mobility sector has the capacity to mobilize ecologically minded designs, supply chains, financing mechanisms, consumer education, cross-sector activation, and more to capitalize on this “new source of carbon.” Activating textile circularity will be one of the biggest business opportunities to drive top- and bottom-line growth for the mobility industry.

Abstract After a severe lane change, a wind gust, or another disturbance, the driver might be unable to recover the intended motion. Even though this fact is known by any driver, the scientific investigation and testing on this phenomenon is just at its very beginning, as a literature review, focusing on SAE Mobilus® database, reveals. We have used different mathematical models of car and driver for the basic description of car motion after a disturbance. Theoretical topics such as nonlinear dynamics, bifurcations, and global stability analysis had to be tackled. Since accurate mathematical models of drivers are still unavailable, a couple of driving simulators have been used to assess human driving action. Classic unstable motions such as Hopf bifurcations were found. Such bifurcations seem almost disregarded by automotive engineers, but they are very well-known by mathematicians. Other classic unstable motions that have been found are “unstable limit cycles.”

In numerous industries such as aerospace and energy, components must perform under significant extreme environments. This imposes stringent requirements on the accuracy with which these components are manufactured and assembled. One such example is the positional tolerance of drilled holes for close clearance applications, as seen in the “EN3201:2008 Aerospace Series – Holes for metric fasteners” standard. In such applications, the drilled holes must be accurate to within ±0.1 mm. Traditionally, this required the use of Computerised Numerical Control (CNC) systems to achieve such tight tolerances. However, with the increasing popularity of robotic arms in machining applications, as well as their relatively lower cost compared to CNC systems, it becomes necessary to assess the ability of robotic arms to achieve such tolerances. This review paper discusses the sources of errors in robotic arm drilling and reviews the current techniques for improving its accuracy.