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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.

As automated driving becomes more common, simulation of vehicle dynamics and control scenarios are increasingly important for investigating motion control approaches. In this work, a study of the differences between the Pure Pursuit and Stanley autonomous vehicle controllers, based on vehicle dynamics responses, is presented. Both are geometric controllers that use only immediate vehicle states, along with waypoint data, to control a vehicle’s future direction as it proceeds from point to point, and both are among the most popular lateral controllers in use today. The MATLAB Automated Driving Toolbox is employed to implement and virtually test the Pure Pursuit and Stanley lateral controllers in different driving scenarios. These include low intensity scenarios such as city driving, and emergency maneuvers such as the moose test.

Environmental perception is considered an essential module for autonomous driving and Advanced Driver Assistance System (ADAS). Recently, deep Convolutional Neural Networks (CNNs) have become the State-of-the-Art with many different architectures in various object detection problems. However, performances of existing CNNs have been dropping when detecting small objects at a large distance. To deploy any environmental perception system in real world applications, it is important that the system achieves high accuracy regardless of the size of the object, distance, and weather conditions. In this paper, a robust sensor fused object detection system is proposed by utilizing the advantages of both vision and automotive radar sensors. The proposed system consists of three major components: 1) the Coordinate Conversion module, 2) Multi level-Sensor Fusion Detection (MSFD) system, and 3) Temporal Correlation filtering module.

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.

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.

With the recent advances in rapid modeling and rapid prototyping, accurate simulation models for tires are very desirable. Selection of a tire slip model depends on the required frequency range and nonlinearity associated with the dynamics of the vehicle. This paper presents a brief overview of three major slip concepts including “Stationary slip”, “Physical transient slip”, and “Pragmatic transient slip”; tire models use these slip concepts to incorporate tire slip behavior. The review illustrates that there can be no single accurate slip model which could be ideally used for all modes of vehicle dynamics simulations. For this study, a rigid ring based semi-analytical tire model for intermediate frequency (up to 100 Hz) is used.

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.

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.

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.

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.

A Task and Message Schedule for a FlexCAN-based Hybrid-Electric vehicle (HEV) functional unit is described. The resulting schedule is a component of an incremental message and task scheduling approach based on a time-driven message schedule and priority-driven task schedule. The HEV functional unit involves the combined control and monitoring functions of an internal combustion engine working in parallel with a permanent magnet synchronous motor. The control algorithm for the synchronous motor has been simulated using VHDL-AMS. The global message system is supported by FlexCAN and the task scheduler system is supported by a priority based OS (e.g., OSEK or AUTOSAR).

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.

A coupler has been developed to prevent windshield wiper systems from being damaged by excessive loads that can occur when the normal wiping pattern is restricted. The coupler is composed of a pultruded composite rod with injection-molded plastic spherical joints (a.k.a. sockets) attached at either end. The sockets are used to attach the coupler to the crank and rocker of the windshield wiper linkage. Because the loads exerted on a coupler vary in magnitude and direction during a wiping cycle, the joint between the sockets and the pultruded composite rod must be robust. The paradigm for attaching sockets to steel couplers (i.e. over-molding the sockets around holes stamped into the ends of traditional steel couplers) was applied to the pultruded rods, tested, and found to produce inadequate joint strength. This paper details the methodology that was employed to produce and optimize an acceptable means to attach the injection-molded sockets to the pultruded rods.

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.