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Advanced Driver Assistance Systems (ADAS) are becoming common on passenger cars and pickup trucks. Accordingly, the manufacturers and installers of aftermarket equipment for these vehicles have an interest in confirming the functionality of ADAS when their equipment is put in place. However, there is very little publicly available information on the effect of aftermarket components on original equipment ADAS. To address this deficiency, a research program was undertaken in which a 2022 Chevrolet Silverado 1500 light truck was tested in four different hardware configurations, including stock as well as three modified conditions. Aftermarket modifications to the vehicle consisted of increased tire diameters, a level kit, and two different lift kits. A series of physical tests were carried out to evaluate the ADAS performance of the vehicle with modifications.

Objection detection using a camera sensor is essential for developing Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) vehicles. Due to the recent advancement in deep Convolution Neural Networks (CNNs), object detection based on CNNs has achieved state-of-the-art performance during daytime. However, using an RGB camera alone in object detection under poor lighting conditions, such as sun flare, snow, and foggy nights, causes the system's performance to drop and increases the likelihood of a crash. In addition, the object detection system based on an RGB camera performs poorly during nighttime because the camera sensors are susceptible to lighting conditions. This paper explores different pedestrian detection systems at low-lighting conditions and proposes a sensor-fused pedestrian detection system under low-lighting conditions, including nighttime. The proposed system fuses RGB and infrared (IR) thermal camera information.

Data-driven modeling can help improve understanding of the governing equations for systems that are challenging to model. In the current work, the Sparse Identification of Nonlinear Dynamical systems (SINDy) is used to predict the dynamic behavior of dynamic problems for NVH applications. To show the merit of the approach, the paper demonstrates how the equations of motions for linear and nonlinear multi-degree of freedom systems can be obtained. First, the SINDy method is utilized to capture the dynamic behavior of linear systems. Second, the accuracy of the SINDy algorithm is investigated with nonlinear dynamic systems. SINDy can output differential equations that correspond to the data. This method can be used to find equations for dynamical systems that have not yet been discovered or to study current systems to compare with our current understanding of the dynamical system.

Safety is considered one of the most important parameters when designing a ground vehicle. The adverse effect of weather on a vehicle can lead to a surge in safety issues and accidents. Several safety assistance systems are available in modern vehicles, which are designed to lessen the negative effects of weather hazards. Although these safety systems can intervene during crucial conditions to avoid accidents, driving a vehicle on snowy or icy terrain can still be a challenging task. Road conditions with the least tire-road friction often results in poor vehicle handling, and without any kind of safety system it can lead to mishaps. With the use of Adams Car software and vehicle dynamics modeling, a realistic relationship between the vehicle and road surface may be established. The simulation can be used to have a better understanding of vehicle handling in snowy and icy conditions, tire-ice interaction, and tire modeling.

Forward collision warning is one of the most challenging concerns in the safety of autonomous vehicles. A cooperation between many sensors such as LIDAR, Radar and camera helps to enhance the safety. Apart from the importance of having a reliable object detector, the safety system should have requisite capabilities to make reasonable decisions in the moment. In this work, we concentrate on detecting front vehicles of autonomous cars using a monocular camera, beyond only a detection method. In fact, we devise a solution based on a cooperation between a deep object detector and a reinforcement learning method to provide forward collision warning signals. The proposed method models the relation between acceleration, distance and collision point using the area of the bounding box related to the front vehicle. An agent of learning automata as a reinforcement learning method interacts with the environment to learn how to behave in eclectic hazardous situations.

Rapid changes in the automotive industry, including the growth of advanced vehicle controls and autonomy, are driving the need for more dedicated proving ground spaces where these systems can be developed safely. To address this need, Kettering University has created the GM Mobility Research Center, a 21-acre proving ground located in Flint, Michigan at the former “Chevy in the Hole” factory location. Construction of a proving ground on this site represents a beneficial redevelopment of an industrial brownfield, as well as a significant expansion of the test facilities available at the campus of Kettering University. Test facilities on the site include a road course and a test pad, along with a building that has garage space, a conference room, and an indoor observation platform. All of these facilities are available to the students and faculty of Kettering University, along with their industrial partners, for the purpose of engaging in advanced transportation research and education.

This paper is based on, and in continuation of the work previously published in ASEE NCS Conference held in Grand Rapids, MI [1]. Automotive seating rail structures are one of the key components in the automotive industry because they carry the entire weight of passenger and they hold the structure for seating foams and other assembled key components such as side airbag and seatbelt systems. The entire seating is supported firmly and attached to the bottom bodywork of the vehicle through the linkage assembly called the seat rails. Seat rails are adjustable in their longitudinal motion which plays an important role in giving the passengers enough leg room to make them feel comfortable. Therefore, seat rails under the various operating conditions, should be able to withstand the weight of the passenger along with the other assembled parts as mentioned above. Also, functional requirements such as crash safety is very important to avoid or to minimize injuries to the occupants.

Due to the nearly silent operation of an electric motor, it is difficult for pedestrians to detect an approaching electric vehicle. To address this safety concern, the National Highway Traffic Safety Administration issued the Federal Motor Vehicle Safety Standard (FMVSS) No. 141, “Minimum Sound Requirements for Hybrid and Electric Vehicles”. This FMVSS 141 standard requires the measurement of electric vehicle noise according to certain test protocols; however, performing these tests can be difficult since inconsistent results can occur in the presence of transient background noise. Methods to isolate background noise during static sound measurements have already been established, though these methods are not directly applicable to a pass-by noise test where neither the background noise nor the vehicle itself as it travels past the microphone produce stationary sound signals.

The current study examined field data in order to document injury rates, injured body regions, and injury sources for persons seated in the second row of passenger vehicles. It was also intended to identify whether these varied with respect to age and restraint use in vehicles manufactured in recent years. Data from the 2007-2012 National Automotive Sampling System (NASS/CDS) was used to describe occupants seated in the second row of vehicles in frontal crashes. Injury plots, comparison of means and logistic regression analysis were used to seek factors associated with increased risk of injury. Restraint use reduced the risk of AIS ≥ 2 injury from approximately 1.8% to 5.8% overall. Seventy nine percent of the occupants in the weighted data set used either a lap and shoulder belt or child restraint system. The most frequently indicated injury source for persons with a MAIS ≥ 2 was “seat, back support”, across restraint conditions and for all but the youngest occupants.

Lean applications in product development usually start with manufacturing due to the relative experience of measuring improvements and identifying wastes in physical settings. The full potential of lean implementation in any product development, however, can only be realized when applied throughout the process, starting with early process. Considering that the first and most essential principle in lean implementation is the characterization of value from the customer's perspective, it is imperative that the proper definition of value is realized at the beginning of the process. In addition, streaming and flowing of this customer's specified value should be realized throughout the process from start to finish. This paper discusses the application of lean principles to integrated design and manufacturing phases of the Product Development Process.

Use of the top tether attachment in three commonly available anchor points provides added restraint of child restraint systems (CRS). Three tether attachment positions were used; floor, behind the head rest (parcel deck) and at the ceiling. The three anchor points are comparable in efficacy while no tether allows increased travel of the anthropomorphic test device (ATD) head. Two series of six tests were conducted at a max speed of 20 mph and peak deceleration of 16 G's using a deceleration sled test apparatus. The first series of tests was conducted at a 90 degree impact angle. On average there is 9% less head travel when using the tether attachment compared to not using the tether attachment, all other conditions begin equal. The second series of tests was conducted at a 73 degree impact angle, there is 15% less head travel when using the tether attachment compared to not using the tether attachment, all other conditions begin equal.

Mechanical counter-pressure (MCP) spacesuit designs have been a promising, but elusive alternative to historical and current gas pressurized spacesuit technology since the Apollo program. One of the important potential advantages of the approach is enhanced mobility as a result of reduced bulk and joint torques, but the literature provides essentially no quantitative joint torque data or quantitative analytical support. Decisions on the value of investment in MCP technology and on the direction of technology development are hampered by this lack of information since the perceived mobility advantages are an important factor. An experimental study of a simple mechanical counter-pressure suit (elbow) hinge joint has been performed to provide some test data and analytical background on this issue to support future evaluation of the technology potential and future development efforts.

FMVSS 223 and 224 set standards for “Rear Impact Protection” for trailers and semi-trailers with a gross weight rating greater than 10000 pounds. A limited amount of experimental data is available for evaluating the different performance attributes of rear impact guards. The crash tests are usually limited to fixed parameters such as impact speed, guard height, strength and energy absorption, etc. There also seems to be some misunderstanding of the interdependence of guard strength and energy absorption, and their combined effect on the guard's ability to limit underride while keeping occupant acceleration forces in a safe range. In this paper, we validated the Finite Element (FE) model of an existing rear impact guard against actual FMVSS 223 tests. We also modified a previously evaluated FE model of a 1990 Ford Taurus by updating its hood geometry and material properties.

Modeling and simulation of dynamic systems is not always a simple task. In this paper, the mathematical model of a 4 Degree Of Freedom (DOF) ride model is presented using a bond-graph technique with state energy variables. We believe that for the physical model as described in this research, the use of a bond-graph approach is the only feasible solution. Any attempt to use classical methods such as Lagrange equations or Newton's second law, will create tremendous difficulties in the transformation of a set of second order linear differential equations to a set of first order differential equations without violating the existence and the uniqueness of the solution of the differential equations, the only approach is the elimination of the damping of the tires, which makes the model unrealistic. The bond-graph model is transformed to a mathematical model. Matlab is used for writing a computer script that solves the engineering problem.

The current study was designed to compare the surface anatomy of the knee for different human subject anthropometries using a 3-D, non-contact digitizer which converted the anatomy into point clouds. The subjects were studied at flexion angles of 60, 90, and 120 degrees. Multiple subjects fitting narrow anthropometrical specifications were studied: 5th percentile female, 50th percentile male, and 95th percentile male. These data were then compared to a corresponding anthropometrical crash dummy knee which served as an unambiguous control. Intersubject human comparisons showed surface geometry variations which were an order of magnitude smaller than comparisons between the human and dummy knee. Large errors between the human and dummy were associated with the muscle bulk proximal and distal to the popliteal region and the rounder shape of the human knee.

The first objective of this paper was to evaluate a public domain finite element (FE) model of a 1990 Ford Taurus from the perspective of crush energy absorption. The validity of the FE model was examined by first comparing simulation results to several published full-frontal crash tests. Secondly, the suitability of the model for underride simulation was evaluated against two series of full-scale crash tests into vertically offset rigid barriers. Next, the evaluated FE model was used to pursue the main objective of this work, namely to develop an approach for estimating underride crush energy. The linear-spring methodology was adopted whereby the underride crush stiffness was determined by relating the residual upper radiator support deformation to crush energy. An underride crush stiffness estimation method was proposed based on modifying the full-frontal stiffness coefficients.

The objective of this study was to determine risk of injury to the driver during a frontal impact in a Formula SAE vehicle. Formula SAE is a collegiate student design competition where every year universities worldwide build and compete with open-wheel formula-style race cars. Formula SAE 2006 rules stipulate the use of an impact attenuator to absorb energy in the event of a frontal impact. These rules mandated an average deceleration not to exceed 20-g from a speed of 7.0 m/s (23 ft/s), but do not specify a specific time or pulse shape of the deceleration. The pulse shapes tested in this study included an early high-g, constant-g, and late high-g pulse. The tests were performed using the deceleration sled at the Kettering University Crash Safety Center. Using industry standard practices, this study examined the driver's risk of injury with regard to neck and femur loads, head and chest accelerations, as well as kinematic analysis using high speed video.

The “Range-of Motion of the Cervical Spine of Children” study is a collaboration between Kettering University and McLaren Regional Medical Center in Flint, Michigan to quantify and establish benchmarks of “normal” range of motion (ROM) in children. The results will be analyzed to determine mean and standard deviation of degrees of rotation and used to improve the occupant protection in motor vehicles, sports equipment and benefits of physical therapy. The data will be invaluable in the development of computational models to analyze processes involving children in motion.

Analysis of the National Automotive Sampling System (NASS) data reveals that vehicle rollover accidents account for a relatively a small number of accidents, but the associated frequency of serious injury is high compared to frontal or side impact. These data demonstrate the apparently elevated probability of head and neck injury during rollover, with head injury occurring more frequently, injured 4.5 times more frequently than the neck when considering all injuries. Automotive industry researchers have performed numerous rollover tests with instrumented ATD's and have predicted an elevated probability of neck injury with little chance of head injury. This contradicts field data (NASS-CDS) which suggests a high frequency of head injury with little chance of neck injury. This difference may be explained in part, through the different volumes of data presented in the literature.

Rollover crashes are responsible for a significant proportion of traffic fatalities each year, while they represent a relatively small proportion of all motor vehicle collisions. The purpose of this study was to focus on rollover events from an occupant's perspective to understand what type of industry test method, ATD, computer based model, and injury assessment measures are required to provide occupant protection during rollovers. Specific injuries most commonly experienced in rollovers along with the associated injury sources were obtained by review of 1998-2000 NASS-CDS records. These data suggest that models capable of predicting the likelihood of brain injuries, specifically subarachnoid and subdural hemorrhage, are desirable. Ideally, the model should also be capable of predicting the likelihood of rib fractures, lung contusions and shoulder (clavicular and scapular) fractures, and facet, pedicle, and vertebral body fractures in the cervical spine.