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The adoption of simulation is critical to reducing development time and enhancing system robustness for Advanced Driver Assistance Systems (ADAS). Automotive companies typically have an abundance of real data recorded from a vehicle which is suitable for open-loop simulations. However, recorded data is often not suitable to test closed-loop control systems since the recorded data cannot react to changes in vehicle movement. This paper introduces a methodology to create virtual driving scenarios from recorded vehicle data to enable closed-loop simulation. This methodology is applied to test a lane centering application. A lane centering application helps a driver control steering to stay in the current lane and control acceleration and braking to maintain a set speed or to follow a preceding vehicle. The driver’s vehicle is referred to as the ego vehicle. Other vehicles on the road are referred to as target vehicles.

Road induced structural feel “vehicle feels solidly built” is strongly related to the vehicle ride [1]. Excellent structural feel requires both structural and suspension dynamics considerations simultaneously. Road induced structural feel is defined as customer facing structural and component responses due to tire force inputs stemming from the unevenness of the road surface. The customer interface acceleration and noise responses can be parsed into performance criteria to provide design and tuning vehicle integration program recommendations. A dynamic impact bump method is developed for vehicle level structural feel performance assessment, diagnostics, and development tuning. Current state of on-road testing has the complexity of multiple impacts, averaging multiple road induced tire patch impacts over a length of a road segment, and test repeatability challenges.

The General Motors Aero Lab’s Full-Scale Wind Tunnel Facility, which came into operation in August of 1980[1], has undergone the significant upgrade of installing a state-of-the-art moving ground plane system. After almost four decades of continuous use the full-scale wind tunnel also received some significant maintenance to other areas, including a new heat exchanger, main fan overhaul, and replacement of the test section acoustic treatment. A 5-belt system was installed along with an integrated vehicle lift system. The center belt measures 8.5m long and can accommodate two belt widths of 1100mm and 950mm. Flow quality and other wind tunnel performance parameters were maintained to prior specifications which are on par with the latest industry standards [2]. The new 5-belt rolling road system maintains GM’s industry leading vehicle aerodynamic development and the improved acoustic panels ensure GM continues to develop vehicles with leading class acoustics.

This paper summarizes the development of a wireless message from infrastructure-to-vehicle (I2V) for safety applications based on Dedicated Short-Range Communications (DSRC) under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). During the development of the Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure (RSZW/LC) safety applications [1], the Basic Information Message (BIM) was developed to wirelessly transmit infrastructure-centric information. The Traveler Information Message (TIM) structure, as described in the SAE J2735, provides a mechanism for the infrastructure to issue and display in-vehicle signage of various types of advisory and road sign information. This approach, though effective in communicating traffic advisories, is limited by the type of information that can be broadcast from infrastructures.

This paper summarizes the validation of prototype vehicle-to-infrastructure (V2I) safety applications based on Dedicated Short Range Communications (DSRC) in the United States under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). After consideration of a number of V2I safety applications, Red Light Violation Warning (RLVW), Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure Warning (RSZW/LC) were developed, validated and demonstrated using seven different vehicles (six passenger vehicles and one Class 8 truck) leveraging DSRC-based messages from a Road Side Unit (RSU). The developed V2I safety applications were validated for more than 20 distinct scenarios and over 100 test runs using both light- and heavy-duty vehicles over a period of seven months. Subsequently, additional on-road testing of CSW on public roads and RSZW/LC in live work zones were conducted in Southeast Michigan.

The automotive industry is facing many significant challenges that go far beyond the design and manufacturing of automobile products. Connected, autonomous and electric vehicles, smart cities, urbanization and the car sharing economy all present challenges in a fast-changing environment which the automotive industry must adapt to. Cars no longer are just standalone systems, but have become constituent systems (CS) in larger System of Systems (SoS) context. This is reflected in the emergence of several acronyms such as vehicle-to-everything (V2X), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-grid (V2G) expressions. System of Systems are defined systems of interest whose elements (constituent systems) are managerially and operationally independent systems. This interoperating and/or integrated collection of constituent systems usually produce results unachievable by the individual systems alone, for example the use of car batteries as virtual power plants.

Torque ripple of electric motors is a unique feature in Battery Electric Vehicles (BEV) affecting vehicle performance. It is one of the disturbances from electric motors resulting in unpleasant vehicle fore-aft vibrations at specific vehicle speeds. In this study, the torque ripple modeling and simulation procedure has been developed. Critical modeling contents in a full vehicle ADAMS model and a brief overview of the propulsion control are described. Analytical data sets for torque fluctuations (torque ripple) from a couple of different sources are incorporated in the model. The CAE simulation procedure was applied to simulate vehicle performances of a General Motors Battery Electric Vehicle in an early vehicle design phase. Torque ripple phenomena are simulated both in an open-loop and closed-loop propulsion control environment to see how much vehicle fore-aft vibration suppression is achieved by the motor control methods.

Vehicle to Everything (V2X) communication is a prominent solution for active safety collision avoidance and for providing autonomous vehicles Non-Line of Sight (NLOS) capabilities. For safety purposes, it is essential the V2X technology would support communication between all road users, e.g., Vehicles (V2V), pedestrians (V2P) and road infrastructure (V2I). Hence, the efficiency of a V2V communication solution should be evaluated through system level performance. In addition, the examined performance metrics need to reflect safety related properties. Metrics as Packet Reception Ratio (PRR) and transmission latencies, which are commonly used to assess V2X system’s functionality, aren’t enough since reception latencies are overlooked. The latter is crucial in ensuring messages would reach their destination on time to avoid hazardous incidents. The reception cadence may be much lower than this of the transmission due to various phenomenon (e.g. channel congestion).

With the implementation of the China VI gasoline standards, the use of ethanol is expanding and is intended to further reduce vehicle criteria gaseous and particulate emissions. However, due to the constraints of biomass ethanol production, petroleum derived Methyl tert-Butyl Ether (MTBE) is being used in addition to ethanol to improve fuel octane and maintain oxygen content. The impact of these mixed oxygenates on vehicle emissions are studied in this paper. The correlation of fuel characteristics to vehicle particulate emissions and their predictive indices has been investigated. The results from this study suggest some alternatives to existing fuel indices due to oxygenate contribution. Additionally, this paper studies, the emissions of three direct-injection turbocharged vehicle models focusing on particulate emissions from the Worldwide Harmonized Light Vehicles Test Cycle (WLTC). The test fuels were China VIb gasoline, blended with different ratios of ethanol and MTBE.

Hybrid and electric vehicles utilize high power electric motors to propel the vehicle requiring a significant level of electric current to travel between various modules such as energy storage devices, power inverter modules, energy charging modules, and the motors themselves. This electric current creates magnetic fields around the devices themselves and wiring that delivers this current between devices within the vehicle. These devices and wiring exist throughout the vehicle and can even exist near vehicle occupants, which has prompted investigations looking into the short term biological effect these non-ionizing fields can have on the human body. The findings from these investigations have been published by organizations such as the International Commission on Non-Ionizing Radiation Protection (ICNIRP), and some nations have passed laws regulating the magnetic and electric field exposure to vehicle occupants.

In this paper, a driver identification scheme is studied using general driver inputs such as accelerating, braking and steering behavior, in addition to the settings related to driver’s physical characteristics, such as driver’s seat position. Several drivers are selected with various ages, genders and driving skills to participate in the study. Their driving data is collected using the same test vehicle, and while driving on the same routes. This helps eliminate the inherent vehicle to vehicle variations and the impact of the route differences and enables the identification algorithm to focus on the driving behavior. The driving routes are broken down into shorter segments where the driving features are calculated and populated in these segments. To reduce the identification bias towards certain rare events in the ride, the features are reset at the beginning of each trip segment. This additionally helps to ensure that there is no spill of feature values across the segments.