Search Results

This study assessed a driver’s ability to safely manage Super Cruise lane changes, both driver commanded (Lane Change on Demand, LCoD) and system triggered Automatic Lane Changes (ALC). Data was gathered under naturalistic conditions on public roads in the Washington, D.C. area with 12 drivers each of whom were provided with a Super Cruise equipped study vehicle over a 10-day exposure period. Drivers were shown how to operate Super Cruise (e.g., system displays, how to activate and disengage, etc.) and provided opportunities to initiate and experience commanded lane changes (LCoD), including how to override the system. Overall, drivers experienced 698 attempted Super Cruise lane changes, 510 Automatic and 188 commanded LCoD lane changes with drivers experiencing an average of 43 Automatic lane changes and 16 LCoD lane changes.

Internal organ injuries of the chest are one of the leading causes of deaths in motor vehicle crashes. The issue of initial presence and dynamic formation of voids around the heart and aorta is addressed to improve kinematics, force interaction and injury risk assessment of these organs of the Global Human Body Model. Steps to fill the voids are presented.

This study concerns the generation of response surfaces for kinematics and injury prediction in pedestrian impact simulations using human body model. A 1000-case DOE (Design of Experiments) study with a Latin Hypercube sampling scheme is conducted using a finite element pedestrian human body model and a simplified parametric vehicle front-end model. The Kriging method is taken as the approach to construct global approximations to system behavior based on results calculated at various points in the design space. Using the response surface models, human lower limb kinematics and injuries, including impact posture, lateral bending angle, ligament elongation and bone fractures, can be quickly assessed when either the structural dimensions or the structural behavior of the vehicle front-end design change. This will aid in vehicle front-end design to enhance protection of pedestrian lower limbs.

This paper presents the implementation of an off-line optimized torque vectoring controller on an electric-drive vehicle with four in-wheel motors for driver assistance and handling performance enhancement. The controller takes vehicle longitudinal, lateral, and yaw acceleration signals as feedback using the concept of state-derivative feedback control. The objective of the controller is to optimally control the vehicle motion according to the driver commands. Reference signals are first calculated using a driver command interpreter to accurately interpret what the driver intends for the vehicle motion. The controller then adjusts the braking/throttle outputs based on discrepancy between the vehicle response and the interpreter command.

In recent years, there has been a growing interest in driver visibility. This is, in part, due to increasing emphasis placed on design factors influencing visibility such as: aerodynamics, styling, structural stiffness and vehicle packaging. During the development process of a vehicle, it is important to be able to quantify all of these factors. Visibility, however, owing to its sensory nature, has been harder to quantify. As a result, General Motors (GM) has undertaken a study to gain deeper insight into customer perceptions surrounding visibility. Clinics were conducted to help determine the relative importance of different metrics. The paper also explores several new metrics that can help predict customer satisfaction based on vehicle configuration.

This paper reports a study undertaken by the Crash Safety Working Group (CSWG) of the United States Council for Automotive Research (USCAR) to determine generic acceleration pulses for testing and evaluating advanced batteries subjected to inertial loading for application in electric passenger vehicles. These pulses were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used in this study. Crash test data, in terms of acceleration time histories, were collected from various crash modes conducted by the National Highway Traffic Safety Administration (NHTSA) during their New Car Assessment Program (NCAP) and Federal Motor Vehicle Safety Standards (FMVSS) evaluations, and the Insurance Institute for Highway Safety (IIHS).

General Motors and the Takata Corporation have worked together to bring to production a new, industry first technology called the Front Center Airbag which is being implemented on General Motors' 2013 Midsize Crossover Vehicles. This paper reviews field data, describes the hardware, and presents occupant test data to demonstrate in-position performance in far side impacts. The Front Center Airbag is an airbag that mounts to the inboard side of the driver front seat. It has a tubular cushion structure, and it deploys between the front seating positions in far side impacts, near side impacts and rollovers, with the cushion positioning itself adjacent the driver occupant's head and torso. This paper includes pictures of the technology along with a basic description of the design. In-position occupant performance is also described and illustrated with several examples. Single occupant and two front occupant far side impact test data are included, both with and without the airbag present.

Driving through intersections can be potentially dangerous because nearly 23 percent of the total automotive related fatalities and almost 1 million injury-causing crashes occur at or within intersections every year [1]. The impact of traffic intersections on trip delays also leads to waste of human and natural resources. Our goal is to increase the safety and throughput of traffic intersections using co-operative driving. In earlier work [2], we have proposed a family of vehicular network protocols, which use Dedicated Short Range Communications (DSRC) and Wireless Access in Vehicular Environment (WAVE) technologies to manage a vehicle's movement at intersections Specifically, we have provided a collision detection algorithm at intersections (CDAI) to avoid potential crashes at or near intersections and improve safety. We have shown that vehicle-to-vehicle (V2V) communications can be used to significantly decrease the trip delays introduced by traffic lights and stop signs.

The number of adjustable vehicle interior components features is growing. For example, the number of adjustable components of a vehicle seat has been growing from 4-way to as many as 22-way. The presented study aims to develop understanding on how sensitive drivers and front passengers are to individual component adjustment of vehicle interior features. This understanding could provide insights on which adjustable vehicle interior components features are more important to be precisely adjusted. A commercially available full-size sedan, equipped with a 4-way adjustable steering column & wheel and an 8-way adjustable seat for drivers, and an 8-way adjustable seat for front passengers, was used in this study. A total of 29 and 30 consumers were participating in this study to adjust components to their comfort on driver and front passenger sides, respectively.

As the new features for driver assistance and active safety systems are growing rapidly in vehicles, the simulation within a virtual environment has become a necessity. The current active safety system consists of Electronic Control Units (ECUs) which are coupled to camera and radar sensors. Two methods of implementation exists, integrated sensors with control modules or separation of sensors form control modules. The subsystem integration testing poses new challenges for virtual environment for simulation of active safety features. The comprehensive simulation environment for integration testing consists of chassis controls, powertrain, driver assistance, body and displays controllers. Additional complexity in the system is the serial communication strategy. Multiple communication protocols such as GMLAN, LIN, standard CAN, and Flexray could be present within the same vehicle topology.

This research examined driver acceptance and behavior associated with Speed Limit and Curve Advisor systems, including influences on speed choice. Drivers experienced messages from an emulated Speed Limit and Curve Advisor system during a 2-hour public road drive. Driver tolerance for system errors and message conflicts was also studied by manipulating the accuracy of the information provided by the system. Messages were presented using either a Head-Up Display or on an in-dash Driver Information Center. Results indicate that drivers liked having speed limit information continuously available to them while driving, but the information provided by the Speed Limit Advisor did not significantly influence or alter drivers' speed choice or deceleration profiles in comparison to driving without the system.

An analysis of the first 35 back-over crashes reported by NHTSA's Special Crash Investigations unit was undertaken with two objectives: (1) to test a hypothesized classification of backing crashes into types, and (2) to characterize scenario-specific conditions that may drive countermeasure development requirements and/or objective test development requirements. Backing crash cases were sorted by type, and then analyzed in terms of key features. Subsequent modeling of these SCI cases was done using an adaptation of the Driving Reliability and Error Analysis Methodology (DREAM) and Cognitive Reliability and Error Analysis Methodology (CREAM) (similar to previous applications, for instance, by Ljung and Sandin to lane departure crashes [10]), which is felt to provide a useful tool for crash avoidance technology development.

Forward Collision Alert (or Forward Collision Warning) systems provide alerts intended to assist drivers in avoiding or mitigating the harm caused by rear-end crashes. These systems currently use front-grille mounted, forward-looking radar devices as the primary sensor. In contrast, Lane Departure Warning (LDW) systems employ forward-looking cameras mounted behind the windshield to monitor lane markings ahead and warn drivers of unintended lane violations. The increasing imaging sensor resolution and processing capability of forward-looking cameras, as well recent important advances in machine vision algorithms, have pushed the state-of-the-art for camera-based features. Consequently, camera-based systems are emerging as a key crash avoidance system component in both a primary and supporting sensing role. There are currently no production vehicles with cameras used as the sole FCA sensing device.

Alternative implementations of a Rear Cross Traffic Alert (RCTA) system intended to actively notify drivers of the presence of rear cross-path traffic when backing were evaluated in naturalistic settings. The feature is one of several emerging technologies designed to assist drivers when backing - in this case, enhancing drivers' awareness of traffic approaching from the rear. The study allowed performance under a range of RCTA system driver interface implementations to be contrasted with conventional and wide Field of View (FOV) Rear Vision systems. Evaluations were conducted using a sample of 70 drivers under naturalistic settings and environments with repeated exposures to backing tasks. The study also made use of a staged conflict situation with a confederate vehicle in order to more precisely quantify driver behavior and system usage across drivers under controlled conflict situations.

Vehicle-to-vehicle (V2V) communication systems can enable a number of wireless-based vehicle features that can improve traffic safety, driver convenience, and roadway efficiency and facilitate many types of in-vehicle services. These systems have an extended communication range that can provide drivers with information about the position and movements of nearby V2Vequipped vehicles. Using this technology, these vehicles are able to communicate roadway events that are beyond the driver's view and provide advisory information that will aid drivers in avoiding collisions or congestion ahead. Given a typical communication range of 300 meters, drivers can potentially receive information well in advance of their arrival to a particular location. The timing and nature of presenting V2V information to the driver will vary depending on the nature and criticality of the scenario.

The primary function of an airbag control module is to detect crashes, discriminate and predict if a deployment is necessary, then deploy the restraint systems including airbags and where applicable, pretensioners. At General Motors (GM), the internal term for airbag control module is Sensing and Diagnostic Module (SDM). In the 1994 model year, GM introduced its SDM on some of its North American airbag-equipped vehicles. A secondary function of that SDM and all subsequent SDMs is to record crash related data. This data can include data regarding impact severity from internal accelerometers and pre-crash vehicle data from various chassis and powertrain modules. Previous researchers have addressed the accuracy of both the velocity change data, recorded by the SDM, and the pre-crash data, but the assessment of the timing of the pre-crash data has been limited to a single family of modules (Delphi SDM-G).

Although the measured amount of roof deformation associated with a given rollover crash test is often the residual or post test deformation, rollover crash test researchers are aware that roof deformation occurs dynamically throughout the rollover event with varying magnitude. The challenge to quantifying dynamic roof deformation has been the lack of a reliable method to measure and record the dynamic roof deformation during the rollover test. Researchers have explored various methods to measure dynamic roof deformation including the use of film analysis of external targets, accelerometers, string potentiometers, and 3D photogrammetry. This paper discusses a series of simulated curb trip rollover tests conducted to study and compare different methodologies to measure and record dynamic roof deformation.

There is a growing interest in using pressure sensors to sense side impacts, where the pressure change inside the door cavity is monitored and used to discriminate trigger and non-trigger incidents. In this paper, a pressure sensor simulation capability for side impact sensing calibration is presented. The ability to use simulations for side impact sensing calibration early in the vehicle program development process could reduce vehicle development cost and time. It could also help in evaluating sensor locations by studying the effects of targeted impact points and contents in the door cavity. There are two modeling methods available in LS-DYNA for predicting pressure change inside a cavity, namely airbag method and fluid structure interaction method. A suite of side impact calibration events of a study vehicle were simulated using these two methods. The simulated door cavity pressure time histories were then extracted to calibrate the side sensing system of the study vehicle.

Headliner material plays an important role in occupant protection in situations involving head impact into the interior vehicle roof area. Accurate characterization of its mechanical properties is therefore extremely important for prediction of its behavior during interior impact assessment of a vehicle. Headliner material typically consists of two main layers: the substrate layer which provides structural integrity and impact protection, and the fabric-foam layer which provides proper interior fit and appearance. Both layers vary significantly in thickness and composition between different manufacturers. This paper investigates effects of the layer thickness on compressive strength and deformation of several different headliner materials.

General Motors (GM) and the Virginia Tech Transportation Institute (VTTI) have partnered to conduct a series of studies characterizing the use and effectiveness of technologies designed to assist drivers while backing. A major emphasis of this research has been on Rear Vision Camera (RVC) systems that provide drivers with an enhanced view of the area behind the vehicle. RVC systems are intended to aid in positioning the vehicle when executing low-speed parking and backing-related tasks and are not necessarily well suited for detecting unexpected in-path obstacles (particularly if the RVC image is not coupled with object detection alerts issued to the driver).