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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.

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.

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.

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.

Driving comfort and automotive product quality are strongly associated with the vibration that is transmitted to the occupants of a vehicle at the points of contact to the human body, including the seat, steering wheel, and pedals. Of these three contact locations, the seats have the most general importance, as all occupants of a vehicle experience seat vibration. Particularly relevant to driving comfort is the way in which vehicle occupants perceive seat vibration, which may be different than expected considering sensor measured vibration levels. Much of the interest in seat vibration has been focused on internal combustion engine powertrain vibration, especially idle vibration. However, electrification of vehicles changes the focus from low frequency idle vibration to higher frequency vibration sources.

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.

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.

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.

Automakers looking to remake their traditional vehicle line-up into autonomous vehicles, Noise, Vibration, and Harshness (NVH) considerations for autonomous vehicles are soon to follow. While traditional NVH considerations still must be applied to carry-over systems, additional components are required for an autonomous vehicle to operate. These additional components needed for autonomy also require NVH analysis and optimization. Autonomous vehicles rely on a suite of sensors, including Light Detection and Ranging (LiDAR) and cameras placed at optimal points on the vehicle for maximum coverage and utilization. In this study, the NVH considerations of autonomous vehicles are examined, focusing on the additional perception equipment installed in autonomous vehicles.

A large body of knowledge exists regarding the effects of vibration on human beings; however, the emphasis is generally on the damaging effects of vibration. Very little information has been published regarding the effect of vibration on perceived consumer product quality. The perceived loudness of a product is quantified using the Fletcher-Munson equal loudness curves, but the equivalent curves for perceived vibration amplitude as a function of amplitude and frequency are not readily available. This “vibration quality” information would be valuable in the design and evaluation of many consumer products, including automobiles. Vibration information is used in the automobile design process where targets for steering wheel, seat track, and pedal vibration are common. For this purpose, the vibration information is considered proprietary and is generally applicable to a narrow frequency range. In this investigation, work paralleling the original Fletcher-Munson study is presented.

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.

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.

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.