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This course highlights the technologies enabling ADAS and how they integrate with existing passive occupant crash protection systems, how ADAS functions perceive the world, make decisions, and either warn drivers or actively intervene in controlling the vehicle to avoid or mitigate crashes. Examples of current and future ADAS functions, and various sensors utilized in ADAS, including their operation and limitations, and sample algorithms, will be discussed and demonstrated. The course utilizes a combination of hands-on activities, including computer simulations, discussion and lecture.

Frontal-crash sled tests were conducted to assess submarining protection and abdominal injury risk for midsized male occupants in the rear seat of modern vehicles. Twelve sled tests were conducted in four rear-seat vehicle-bucks with twelve post-mortem human surrogates (PMHS). Select kinematic responses and submarining incidence were compared to previously observed performance of the Hybrid III 50th-percentile male and THOR-50M ATDs (Anthropomorphic Test Devices) in matched sled tests conducted as part of a previous study. Abdominal pressure was measured in the PMHS near each ASIS (Anterior Superior Iliac Spine), in the inferior vena cava, and in the abdominal aorta. Damage to the abdomen, pelvis, and lumbar spine of the PMHS was also identified. In total, five PMHS underwent submarining. Four PMHS, none of which submarined, sustained pelvis fractures and represented the heaviest of the PMHS tested. Submarining of the PMHS occurred in two out of four vehicles.

The safety and reliability of ground vehicles is a motivating factor for periodic maintenance which includes fluids, lubrication, cleaning, repairs, and general observation of key subsystems. The scheduling of maintenance activities can occur at different rates such as daily, weekly, or perhaps operating time based on collected historical data and general guidelines. The availability of a digital twin (DT), which offers a virtual representation of the vehicle behavior, enables virtual system simulations for different operating cycles to explore the dynamic behavior. When field operating fleet data can be integrated with the digital twin estimates, then this supplemental information can be combined with the existing maintenance plan to provide a more comprehensive approach. In this paper, a digital twin with a statistical based predictive maintenance strategy is investigated for a wheeled military ground vehicle.

The Advanced Driver Assistance System (ADAS) is a comprehensive feature set designed to aid a driver in avoiding or reducing the severity of collisions while operating the vehicle within specified conditions. In General Motors (GM) vehicles, the primary controller for the ADAS is the Active Safety Control Module (ASCM). In the 2013 model year, GM introduced an ASCM utilizing the GM internal nomenclature of External Object Calculation Module (EOCM) in some of their vehicles produced for the North American market. Similar to the Sensing and Diagnostic Module (SDM) utilized in the restraints system, the EOCM3 LC contains an Event Data Recorder (EDR) function to capture and record information surrounding certain ADAS or Supplemental Inflatable Restraint (SIR) events. The ASCM EDR contains information from external object sensors, various chassis and powertrain control modules, and internally calculated data.

The on-board emergency call system with accurate occupant injury prediction can help rescuers deliver more targeted traffic accident rescue and save more lives. We use machine learning methods to establish, train, and validate a number of classification models that can predict occupant injuries (by determining whether the MAIS (Maximum Abbreviated Injury Scale) level is greater than 2) based on crash data, and ranked the correlation of some factors affecting vehicle occupant injury levels in accidents. The optimal model was selected by the model prediction accuracy, and the Grid Search method was used to optimize the hyper-parameters for the model.

The Baja SAE Completion is an extreme off roading event that requires an effective suspension design to survive the many obstacles that make up the racecourses. Without an effective suspension the many participating teams will experience poor performance or even failure within their suspension. This research focuses on the development and optimization of a double wishbone suspension in both the front and rear. Additionally, the design and optimization of a sway bar attached to the rear suspension will be gone through. Both the front and rear suspension will be optimized through three simulations heave, roll, and steering through the use of Optimum Kinematics. The process for placing the coilovers to ensure they will move perpendicular to control arms throughout their travel and ensuring the coilovers length in fully compression and extension are not exceeded will be developed through the use of SolidWorks and Optimum Kinematics.

The handling of flexible components creates a unique problem set for pick and place automation within automotive production processes. Fabrics and woven textiles are examples of flexible components used in car interiors, for air bags, as liners and in carbon-fiber layups. These textiles differ greatly in geometry, featuring complex shapes and internal slits with varying material properties such as drape characteristics, crimp resistance, friction, and fiber weave. Being inherently flexible and deformable makes these materials difficult to handle with traditional rigid grippers. Current solutions employ adhesive, needle-based, and suction strategies, yet these systems prove a higher risk of leaving residue on the material, damaging the weave, or requiring complex assemblies. Pincer-style grippers are suitable for rigid components and offer strong gripping forces, yet inadvertently may damage the fabric, and introduce wrinkles / folded-over edges during the release process.

In this study, an optimized structure for opening the headlining considering the deployment of the face-to-face roof airbag was studied. It was confirmed that the deployment performance differs depending on the skin of the headlining, and a standardized structure with mass production was proposed. Non-woven fabric and Tricot skin, which are economical and high-end specifications, satisfy the performance of PVC fusion application specifications after cutting 80% of the skin. The structure that satisfies the entire body including the knit specifications is a type that separates the roof airbag area piece, the corresponding soft piece is separated, and the deployment performance is satisfied with safety. Therefore, the structure is proposed as a standardized structure. This structure is expected to be applicable to roof DAB (Driver Airbag), PAB (Passenger Airbag), and Sunroof Airbag, which will be necessary technologies to secure indoor space.

Alongside advancements in automated vehicle technologies, occupants within vehicle compartments are enjoying increased freedom to relax and enjoy their journeys. For instance, reclined seating postures have become more prevalent and comfortable compared to upright seating when Highly Automated Vehicles (HAVs) are introduced. Unfortunately, most Anthropomorphic Testing Devices (ATD) do not support reclined postures. THOR-AV 50M is a specially designed dummy for reclined postures. As a crucial tool for developing safety restraint systems to protect reclined occupants, the first question is how to position it correctly on a reclined seat before impact testing. In this study, classical zero gravity seats were selected. H-point coordinators of selected seat at 25°, 40° and 60° seatback angle were measured and compared by using H-point machine (HPM) even though current HPM was not designed for reclined seat.

Improving passenger safety inside vehicle cabins requires continuously monitoring vehicle seat occupancy statuses. Monitoring a vehicle seat’s occupancy status includes detecting if the seat is occupied and classifying the seat’s occupancy type. This paper introduces an innovative non-intrusive technique that employs capacitive sensing and an occupancy classifier to monitor a vehicle seat’s occupancy status. Capacitive sensing is facilitated by a meticulously constructed capacitance-sensing mat that easily integrates with any vehicle seat. When a passenger or an inanimate object occupies a vehicle seat equipped with the mat, they will induce variations in the mat’s internal capacitances. The variations are, in turn, represented pictorially as grayscale capacitance-sensing images (CSI), which yield the feature vectors the classifier requires to classify the seat’s occupancy type.

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.