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Vehicle safety systems may use occupant physiological information, e.g., occupant heights and weights to further enhance occupant safety. Determining occupant physiological information in a vehicle, however, is a challenging problem due to variations in pose, lighting conditions and background complexity. In this paper, a novel occupant height estimation approach is presented. Depth information from a depth camera, e.g., Microsoft Kinect is used. In this 3D approach, first, human body and frontal face views (restricted by the Pitch and Roll values in the pose estimation) based on RGB and depth information are detected. Next, the eye location (2D coordinates) is detected from frontal facial views by Haar-cascade detectors. The eye-location co-ordinates are then transferred into vehicle co-ordinates, and seated occupant eye height is estimated according to similar triangles and fields of view of Kinect.

A dual-chambered passenger airbag was developed for the 2011 USNCAP to minimize neck loading for the belted 5th female dummy while restraining the unbelted 50th dummy for FMVSS208. This unique, patented design adaptively controlled venting between chambers based on occupant stature. A patented pressure-responsive vent on the second chamber permitted aspiration into the second chamber before a delayed outflow to the environment. The delayed flow through the pressure-responsive vent from the second chamber acted like a pressure-limiting membrane vent to advantageously reduce the injury assessment values for the HIC and the Nij for the 5th female dummy.

The IGBTs are dominantly used in traction inverters for automotive applications. Because the Si-based device technology is being pushed to its theoretical performance limit in such applications during recent years, the gate driver design is playing a more prominent role to further improve the traction inverter loss performance. The conventional gate driver design in traction inverter application needs to consider worst case scenarios which adversely limit the semiconductor devices' switching speed in its most frequent operation regions. Specifically, when selecting the gate resistors, the IGBT peak surge voltage induced by fast di/dt and stray inductance must be limited below the device rated voltage rating under any conditions. The worst cases considered include both highest dc bus voltage and maximum load current. However, the traction inverter operates mainly in low current regions and at bus voltage much lower than the worst case voltage.

An experimental study was conducted using a dynamic rollover component test system (ROCS) to study the effects of activating a pyro-mechanical buckle pre-tensioner and an electric retractor on the driver and front right passenger head and pelvis excursions. The ROCS is a unique system capable of producing vehicle responses that replicate four distinct phases of a tripped rollover: trip initiation, roll initiation, free-flight vehicle rotation, and vehicle to ground contact. This component test system consists of a rigid occupant compartment derived from a mid-size SUV with complete 1st row seating and interior trim, a simulated vehicle suspension system and an elastic vehicle-to-ground-contact surface. The ROCS system was integrated with a Deceleration Rollover Sled (DRS). Dynamic responses of the ROCS system, including both the rigid compartment and occupant, were measured and recorded.

This paper presents two brake control functions which are initiated when there is an impact force applied to a host vehicle. The impact force is generated due to the host vehicle being collided with or by another vehicle or object. The first function - called the post-impact braking assist - initiates emergency brake assistance if the driver is braking during or right after the collision. The second function - called the post-impact braking - initiates autonomous braking up to the level of the anti-lock-brake system if the driver is not braking during or right after the collision. Both functions intend to enhance the current driver assistance features such as emergency brake assistance, electronic stability control, anti-brake-lock system, collision mitigation system, etc.

Researchers and engineers are utilizing big data analytics to draw further insights into transportation systems. Large amounts of data at the individual vehicle trip level are being collected and stored. The true potential of such data is still to be determined. In this paper, we are presenting a data-driven, novel, and intuitive approach to model driver behaviors using microscopic traffic simulation. Our approach utilizes metaheuristic methods to create an analytical tool to assess vehicle performance. Secondly, we show how microscopic simulation run outputs can be post-processed to obtain vehicle and trip level performance metrics. The methodology will form the basis for a data-driven approach to unearthing trip experiences as realized by drivers in the real world. The methodology will contribute to, A.) Using vehicle trajectory traces to identify underlying vehicle maneuver distributions as obtained from real-world driver data, B.)

A theoretical, mathematical, risk assessment procedure was developed to estimate the fraction of drivers that incurred head and thoracic AIS3+ injuries in full-engagement frontal crashes. The estimates were based on numerical simulations of various real-world events, including variations of crash severity, crash speed, level of restraint, and occupant size. The procedure consisted of four steps: (1) conduct the simulations of the numerous events, (2) use biomechanical equations to transform the occupant responses into AIS3+ risks for each event, (3) weight the maximum risk for each event by its real-world event frequency, and (4) sum the weighted risks. To validate the risk assessment procedure, numerous steps were taken. First, a passenger car was identified to represent average field performance.

In December 2015, the National Highway Traffic Safety Administration (NHTSA) published a Request for Comments on proposed changes to the New Car Assessment Program (NCAP). One potential change is the addition of a frontal oblique impact (OI) crash test using the Test Device for Human Occupant Restraint (THOR). The resultant acetabulum force, which is a unique and specifically defined in the THOR dummy, will be considered as a new injury metric. In this study, the results of ten OI tests conducted by NHTSA on current production mid-sized vehicles were investigated. Specifically, the test data was used to study the lower extremity kinematics for the driver and front passenger THOR dummies. It was found that the acetabulum force patterns varied between the driver and passenger and between the left leg and the right leg of the occupants. The maximum acetabulum force can occur either on the left side or right side of a driver or a front passenger in an OI event.

Reductions of hardware costs as well as implementations of new innovative functions are the main drivers of today's automotive electronics. Indeed more and more resources are spent on adapting existing solutions to different environments. At the same time, due to the increasing number of networked components, a level of complexity has been reached which is difficult to handle using traditional development processes. The automotive industry addresses this problem through a paradigm shift from a hardware-, component-driven to a requirement- and function-driven development process, and a stringent standardization of infrastructure elements. One central standardization initiative is the AUTomotive Open System ARchitecture (AUTOSAR). AUTOSAR was founded in 2003 by major OEMs and Tier1 suppliers and now includes a large number of automotive, electronics, semiconductor, hard- and software companies.

The development of the Advanced Restraint System has lead to an innovative way in which we evaluate the systems effect on the occupant. This paper presents some initial investigation into the driver airbag system that consists of an inflator, cushion fold, tear seam pattern, and offset of the airbag cover to steering wheel rim plane. An initial DOE is reviewed to establish significant parameters and to identify equations for further investigation.

This study investigated the effects of three navigation system human-machine interfaces (HMIs) on driver eye-glance behavior, navigational errors, and subjective assessments. Thirty-six drivers drove an unfamiliar 3-segment route in downtown Detroit. HMIs were 2D or 3D (level-of-detail) electronic map display + standard voice prompts, or 3D map-display augmented by photorealistic images + landmark-enhanced voice prompts. Participants drove the same three route segments in order but were assigned a different HMI condition/segment in a 3-period/3-treatment crossover experimental design. Results indicate that drivers’ visual attention using the advanced navigation systems HMIs were within US Department of Transportation recommended visual distraction limits. More turns missed in the first route segment, regardless of HMI, were attributable to greater route complexity and a late-onset voice prompt. Participant’s ratings of HMIs were influenced by the context in which that HMI was used.

This paper proposes a low-cost but indirect method for occupancy detection and occupant counting purpose in current and future automotive systems. It can serve as either a way to determine the number of occupants riding inside a car or a way to complement the other devices in determining the occupancy. The proposed method is useful for various mobility applications including car rental, fleet management, taxi, car sharing, occupancy in autonomous vehicles, etc. It utilizes existing on-board motion sensor measurements, such as those used in the vehicle stability control function, together with door open and closed status. The vehicle’s motion signature in response to an occupant’s boarding and alighting is first extracted from the motion sensors that measure the responses of the vehicle body. Then the weights of the occupants are estimated by fitting the vehicle responses with a transient vehicle dynamics model.

Vehicle motion prior to a rollover can influence an occupant's position in the vehicle. Lateral deceleration prior to a tripped rollover may cause the occupant to move outboard. This outboard motion may have several effects on the occupant such as, repositioning the occupant with relation to the seat and seat restraint, and allowing the occupant's head to travel further into the side curtain deployment zone. To reduce occupant lateral motion, the effectiveness of applying tension to the seatbelt was evaluated. The evaluation consisted of two test conditions simulating vehicle lateral motion prior to a trip using a Deceleration Rollover Sled [1]. The test conditions were designed to ensure a vehicle experiences a period of pure lateral motion before the onset of a lateral trip. A standard seat belt combined with various means of applying tension and activated at different times during the test were evaluated.

Historical driver behavior and drive style are crucial inputs in addition to V2X connectivity data to predict future events as well as fuel consumption of the vehicle on a trip. A trip is a combination of different maneuvers a driver executes to navigate a route and interact with his/her environment including traffic, geography, topography, and weather. This study leverages big data analytics on real-world customer driving data to develop analytical modeling methodologies and algorithms to extract maneuver-based driving characteristics and generate a corresponding maneuver distribution. The distributions are further segmented by additional categories such as customer group and type of vehicle. These maneuver distributions are used to build an aggressivity distribution database which will serve as the parameter basis for further analysis with traffic simulation models.

The interaction of Connect and Automated vehicles (CAV) with regular vehicles in the traffic stream has been extensively researched. Most studies, however, focus on calibrating driver behavior models for CAVs based on various levels of automation and driver aggressiveness. Other related studies largely focus on the coordination of CAVs and infrastructure like traffic signals to optimize traffic. However, the effects of different strategic flow management of CAVs in the traffic stream in the comparative scenario-based analysis is understudied. Thus, this study develops a framework and simulations for integrating CAVs in a corridor section. We developed a calibrated model with CAVs for a corridor section in Corktown, Michigan, and simulate how dedicated CAV lane operations can be implemented without significant change in existing infrastructure.

Blunt impacts to the back of the torso can occur in vehicle crashes due to interaction with unrestrained occupants, or cargo in frontal crashes, or intrusion in rear crashes, for example. Six pendulum tests were conducted on the back of an instrumented 50th percentile male Hybrid III ATD (Anthropomorphic Test Device) to determine kinematic and biomechanical responses. The impact locations were centered with the top of a 15-cm diameter impactor at the T1 or at T6 level of the thoracic spine. The impact speed varied from 16 to 24 km/h. Two 24 km/h tests were conducted at the T1 level and showed repeatability of setup and ATD responses. The 16 and 24 km/h tests at T1 and T6 were compared. Results indicated greater head rotation, neck extension moments and neck shear forces at T1 level impacts. For example, lower neck extension was 2.6 times and 3.8 times greater at T1 versus T6 impacts at 16 and 24 km/h, respectively.

The FMEA and DV&PV process of developing automotive products requires identifying and repeatedly testing critical vehicle attributes and their response to noise factors that may impair vehicle function. Ford has developed a new automated scripting tool to streamline in-vehicle robustness testing and produce more accurate and repeatable results. Similar noise factors identified during the FMEA process are grouped together, condensed, and scripts are developed to simulate these noise factors using calibration parameters and vehicle controls. The automated testing tool uses the API of a calibration software tool and a graphical scripting interface to consistently simulate driver inputs with greater precision than a human calibrator and enable more sophisticated controls, which would have previously required experimental software builds. The noise factor scripts are executed with minimal intervention from a human operator, and the collected data is analyzed to determine robustness.

Today, the interior noise perceived by the occupants is becoming an important factor driving the design standards for the design of most of the interior assemblies in an automotive vehicle. Buzz, Squeak and Rattle (BSR) is a major contributor towards the perceived noise of annoyance to the vehicle occupants. An automotive vehicle consists of many assemblies such as instrumentation panel, doors, sun/moon-roof, deck lids, hood, etc. which are the potential sources of BSR noise. The potential locations of critical BSR noise could be contained within such assemblies as well as across their boundaries. An extensive study is made regarding the overall structural behavior as well as their interaction under typical road loads to come up with enhanced design for improved quality from the BSR noise perspective. The alternative designs were comparatively evaluated for their relative noise level from buzz, squeak and rattle perspective using an analytical tool - N-hance.BSR.

This paper takes a look at one of the problems associated with the concept of autonomous control of vehicles in the current traffic environment, namely the changing of lanes. Given the increase in traffic density on highways and interstate roads over the past few decades, safe navigation of individual vehicles has required increased driver attention and diligence to an increased number of visual information cues. The concept of autonomous vehicles operating without driver intervention in the present traffic system appears daunting. One aspect of traffic maneuvering involves changing lanes to a position between two other vehicles. Although this aspect appears straightforward, it is the lack of accurate knowledge of other vehicle maneuvering which makes the task difficult. Using Model Predictive Control (MPC) techniques, the task is addressed in an optimization problem framework.

This study applies a detailed finite element model of the human body to simulate occupant knee impacts experienced in vehicular frontal crashes. The human body model includes detailed anatomical features of the head, neck, chest, thoracic and lumbar spine, abdomen, and lower and upper extremities. The material properties used in the model for each anatomic part of the human body were obtained from test data reported in the literature. The total human body model used in the current study has been previously validated in frontal and side impacts. Several cadaver knee impact tests representing occupants in a frontal impact condition were simulated using the previously validated human body model. Model impact responses in terms of force-time and acceleration-time histories were compared with test results. In addition, stress distributions of the patella, femur, and pelvis were reported for the simulated test conditions.