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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.

This work aims to present the application of mode coupling to a Formula Student racing vehicle and propose a solution. The major modes of a vehicle are heave, pitch, roll, and warp. All these modes are highly coupled – which means changing suspension rates or geometry will affect all of them – while alleviating some and making others worse characteristics. Decoupling these modes, or at least some of them, would provide more control over suspension setup and more refined race car dynamics for a given layout of the racetrack. This could improve mechanical grip and yield significant performance improvements in closed-circuit racing. If exploited well, this approach could also assist in the operation of the vehicle at an optimal kinematic state of the suspension systems, to gain the best wheel orientations and maximize grip from the tires under the high lateral accelerations and varied excitations seen on a typical road course.

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.

As advanced vehicle controls and autonomy become mainstream in the automotive industry, the need to employ traditional mathematical models and control strategies arises for the purpose of simulating autonomous vehicle handling maneuvers. This study focuses on lane change maneuvers for autonomous vehicles driving at low speeds. The lane change methodology uses PID (Proportional-Integral-Derivative) controller to command the steering wheel angle, based on the yaw motion and lateral displacement of the vehicle. The controller was developed and tested on a bicycle model of an electric vehicle (a Chevrolet Bolt 2017), with the implementation done in MATLAB/Simulink. This simple mathematical model was chosen in order to limit computational demands, while still being capable of simulating a smooth lane change maneuver under the direction of the car’s mission planning module at modest levels of lateral acceleration.

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 objective of this project is to analyze potential design changes that can improve the performance of helical spring in an independent suspension. The performance of the helical spring was based upon the result measure of maximum value of stress acting on it and the amount displacement caused when the spring undergoes loading. The design changes in the spring were limited to coil cross section, spring diameter (constant & variable), pitch and length of the spring. The project was divided into Stage I & Stage II. For Stage I, using all the possible combinations of these design parameters, linear stress analysis was performed on different spring designs and their Stress and displacement results were evaluated. Based on the results, the spring designs were classified as over designed or under designed springs.

For virtual simulation of the vehicle attributes such as handling, durability, and ride, an accurate representation of pneumatic tire behavior is very crucial. With the advancement in autonomous vehicles as well as the development of Driver Assisted Systems (DAS), the need for an Intelligent Tire Model is even more on the increase. Integrating sensors into the inner liner of a tire has proved to be the most promising way in extracting the real-time tire patch-road interface data which serves as a crucial zone in developing control algorithms for an automobile. The model under development in Kettering University (KU-iTire), can predict the subsequent braking-traction requirement to avoid slip condition at the interface by implementing new algorithms to process the acceleration signals perceived from an accelerometer installed in the inner liner on the tire.

The safety of ground vehicles is a matter of critical importance. Vehicle safety is enhanced with the use of control systems that mitigate the effect of unachievable demands from the driver, especially demands for tire forces that cannot be developed. This paper presents the results of a smart tire prototyping and validation study, which is an investigation of a smart tire system that can be used as part of these mitigation efforts. The smart tire can monitor itself using in-tire sensors and provide information regarding its own tire forces and moments, which can be transmitted to a vehicle control system for improved safety. The smart tire is designed to estimate the three orthogonal tire forces and the tire aligning moment at least once per wheel revolution during all modes of vehicle operation, with high accuracy. The prototype includes two in-tire piezoelectric deformation sensors and a rotary encoder.

Vehicles are in contact with the road surface through tires, and the interaction at the tire-road interface is usually the major source of vibrations that is experienced by the passengers in the vehicle. Thus, it is critical to measure the vibrational characteristics of the tires in order to improve the safety and comfort of the passengers and also to make the vehicle quieter. The measurement results can also be used to validate numerical models. In this paper, Digital Image Correlation (DIC) as a non-contact technique is used to measure the dynamics of a racing tire in static and rolling conditions. The Kettering University FSAE car is placed on the dynamometer machine for this experiment. A pair of high-speed cameras is used to capture high-resolution images of the tire in a close-up view. The images are processed using DIC to obtain strain and displacement of the sidewall of the tire during rolling. The experiment is performed for various testing speeds.

Tires are one of the major sources of noise and vibration in vehicles. The vibration characteristic of a tire depends on its resonant frequencies and mode shapes. Hence, it is desirable to study how different parameters affect the characteristics of tires. In the current paper, experimental modal tests are performed on a tire in free-free and fixed conditions. To obtain the mode shapes and the natural frequencies, the tire is excited using a mechanical shaker and the response of the tire to the excitation is measured using three roving tri-axial accelerometers. The mode shapes and resonant frequencies of the tire are extracted using LMS PolyMax modal analysis. The obtained mode shapes in the two configurations are compared using Modal Assurance Criterion (MAC) to show how mode shapes of tires change when the tire is moved from a free-free configuration to a fixed configuration. It is shown that some modes of the tire are more sensitive to boundary conditions.

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.

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.

Steer-by-wire is a system where there are no mechanical connections between the steering wheel and the tires. With the inception of electric and hybrid cars, steer-by-wire is becoming more common. A steer-by-wire car opens many opportunities for additional feedback on the steering wheel. Providing haptic feedback through the steering wheel will add additional depth and capabilities to make the driving experience safer. In this paper we investigated the effects of force feedback on the steering wheel in order to detect and/or avoid blind spot collisions. Two types of force feedback are examined using a driving simulator: a rumble and a counter steering force. A rumble on the steering wheel can avoid blind-spot accidents by providing feedback to drivers about vehicles in their blind spots. Providing counter steering force feedback can help in the reduction in blind-spot accidents. The results show that adding counter steering force feedback did reduce blind-spot related collisions.

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.

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.