Search Results

The Test Device for Human Occupant Restraint (THOR) is an advanced crash test dummy designed for frontal impact. Originally released in a 50th percentile male version (THOR-50M), a female 5th version (THOR-05F) was prototyped in 2017 (Wang et al., 2017) and compared with biofidelity sub-system tests (Wang et al., 2018). The same year, Trosseille et al. (2018) published response corridors using nine 5th percentile female Post Mortem Human Subjects (PMHS) tested in three sled configurations, including both submarining and non-submarining cases. The goal of this paper is to provide an initial evaluation of the THOR-05F biofidelity in a full-scale sled test, by comparing its response with the PMHS corridors published by Trosseille et al. (2018). Significant similarities between PMHS and THOR-05F were observed: as in Trosseille et al. (2018), the THOR-05F did not submarine in configuration 1, and submarined in configurations 2 and 3.

Controller area network (CAN), FlexRay and local interconnect network (LIN) digital protocols are commonly used for communication in modern vehicles. A modern vehicle contains up to 70 electronic control units. This paper is a literature review of these protocols. We have also implemented LIN protocol. The communication cycle, process, message structure, and hardware elements are discussed for all three protocols. Performance is measured in terms of reliability and latency. In addition, a comparison between the CAN, FlexRay and LIN protocols is made. Experimental results indicate that CAN protocol has advantages when it comes to real-time priority-based communication. However, if all the events have equal priority, then FlexRay works well. The LIN protocol is budget friendly and has lowest cost in all 3 protocols but at the same time it is unreliable.

Recently developed gasoline engines utilize more aggressive EGR rate to meet the emissions and fuel economy regulations. The EGR temperature is often estimated by the ECU and its accuracy affects the estimations of EGR flow rate and intake air flow rate and temperature. Therefore, the accuracy of EGR temperature estimation becomes more important than ever for precise EGR rate control. Typical lookup map based EGR cooler model without the sensitivity to the coolant flow rate is acceptable and widely used if the heat capacity of the coolant side is high enough. However, the coolant flow rate under real vehicle driving conditions often visit low-speed high-load part of the engine map where the lookup map based model suffers from the accuracy issues. This paper presents an investigation of the accuracy of the lookup map based model under different heat capacity conditions. In this study, a simple EGR cooler model based on effectiveness-NTU method was also developed.

Controller area network (CAN) is used as a legacy protocol for in-vehicle communication. However, it lacks basic security features such as message authentication, integrity, confidentiality, etc., because the sender information in the message is missing. Hence, it is prone to different attacks like spoofing attacks, denial of service attacks, man in the middle and masquerade attacks. Researchers have proposed various techniques to detect and prevent these attacks, which can be split into two classes: (a) MAC-based techniques and (b) intrusion detection-based techniques. Further, intrusion detection systems can be divided into four categories: (i) message parameter- based, (ii) entropy-based, (iii) machine Learning-based and (iv) fingerprinting-based. This paper details state-of- the-art survey of fingerprinting-based intrusion detection techniques. In addition, the advantages and limitations of different fingerprinting-based intrusion detection techniques methods will be discussed.

Adverse weather conditions degrade the quality of images used in vision-based advanced driver assistance systems (ADAS) and autonomous driving algorithms. Adherent raindrops onto a vehicle’s windshield occlude parts of the input image and blur background texture in regions covered by them. Rain also changes image intensity and disturbs chromatic properties of color images. In this work, we collected a dataset using a camera mounted behind a windshield at different rain intensities. The data was processed to generate a set of distorted images by adherent raindrops along with ground truth data of clear images (just after a windshield wipe). We quantitatively evaluated the amount of distortion caused by the raindrops, using the Normalized Cross-Correlation and Structural Similarity methods.

Worldwide projections anticipate a fast-growing market share of the battery electric vehicles (BEVs) to meet stringent emissions regulations for global warming and climate change. One of the new challenges of BEVs is the effective and efficient thermal management of the BEV to minimize parasitic power consumption and to maximize driving range. Typically, the total efficiency of BEVs depends on the performance and power consumption of the thermal management system, which is highly affected by several factors, including driving environments (ambient temperature and traffic conditions) and driver's behavior (aggressiveness). Therefore, this paper investigates the influence of these factors on energy consumption by using a comprehensive BEV simulation integrated with a thermal management system model. The vehicle model was validated with experimental data, and a simulation study is performed by using the vehicle model over various traffic scenarios generated from a traffic simulator.

Several studies, available in the literature, were conducted to establish the most relevant criterion for predicting the thoracic injury risk on the THOR dummy. The criteria, such as the maximum deflection or a combination of parameters including the difference between the chest right and left deflections, were all developed based on given samples of Post Mortem Human Subject (PMHS). However, they were not validated against independent data and they are not always consistent with the observations from field data analysis. For this reason, 8 additional PMHS and matching THOR tests were carried out to assess the ability of the criteria to predict risks. Accident investigations showed that a reduction of the belt loads reduces the risk of rib fractures. Two configurations with different levels of force limitation were therefore chosen. A configuration representing an average European vehicle was chosen as a reference.

In the last decade, extensive efforts have been made to understand the physics of submarining and its consequences in terms of abdominal injuries. For that purpose, 27 Post Mortem Human Subject (PMHS) tests were performed in well controlled conditions on a sled and response corridors were provided to assess the biofidelity of dummies or human body models. All these efforts were based on the 50th percentile male. In parallel, efforts were initiated to transfer the understanding of submarining and the prediction criteria to the THOR dummies. Both the biofidelity targets and the criteria were scaled down from the 50th percentile male to the 5th percentile THOR female. The objective of this project was to run a set of reference PMHS tests in order to check the biofidelity of the THOR F05 in terms of submarining. Three series of tests were performed on nine PMHS, the first one was designed to avoid submarining, the second and third ones were designed to result in submarining.

In a previous study (Song et al. 2017), an adjustable generic simplified vehicle buck was developed; eleven PMHS were impacted by the buck representing a SUV, a van and a sedan successively; and biofidelity corridors were established. The objectives of the current study were 1) to develop the computational model of the buck, and 2) to simulate these PMHS tests with the buck model and to assess the biofidelity of the GHBMC 50th percentile male pedestrian simplified model (GHBMC M50-PS). First, coupon tensile tests and static and dynamic compression tests were performed on the steel tubes representing the bonnet leading edge (BLE), the bumper and the spoiler used in the above PMHS tests. Based on these tests, the computational models of the above components were then developed and validated. Next, the buck model was built with the component models, and used to simulate the PMHS tests with the GHBMC M50-PS model.

Cameras and image processing hardware are rapidly evolving technologies, which enable real-time applications for passenger cars, ground robots, and aerial vehicles. Visual odometry (VO) algorithms estimate vehicle position and orientation changes from the moving camera images. For ground vehicles, such as cars, indoor robots, and planetary rovers, VO can augment movement estimation from rotary wheel encoders. Feature-based VO relies on detecting feature points, such as corners or edges, in image frames as the vehicle moves. These points are tracked over frames and, as a group, estimate motion. Not all detected points are tracked since not all are found in the next frame. Even tracked features may not be correct since a feature point may map to an incorrect nearby feature point. This can depend on the driving scenario, which can include driving at high speed or in the rain or snow.

Global surrogate modeling aims to build surrogate model with high accuracy in the whole design domain. A major challenge to achieve this objective is how to reduce the number of function evaluations to the original computer simulation model. To date, the most widely used approach for global surrogate modeling is the adaptive surrogate modeling method. It starts with an initial surrogate model, which is then refined adaptively using the mean square error (MSE) or maximizing the minimum distance criteria. It is observed that current methods may not be able to effectively construct a global surrogate model when the underlying black box function is highly nonlinear in only certain regions. A new surrogate modeling method which can allocate more training points in regions with high nonlinearity is needed to overcome this challenge. This article proposes an efficient global surrogate modeling method based on a multi-layer sampling scheme.

Petit et al. 2015 and Lebarbé et al. 2016 reported on two studies where the injury mechanism and threshold of the sacroiliac joint were investigated in two slightly oblique crash test conditions from 18 Post Mortem Human Subjects (PMHS) tests. They concluded that the sacroiliac joint fractures were associated with pubic rami fractures. These latter being reported to occur first in the time history. Therefore it was recommended not to define a criterion specific for the sacroiliac joint. In 2012, injury risk curves were published for the WorldSID dummy by Petitjean et al. For the pelvis, dummy and PMHS paired tests from six configurations were used (n = 55). All of these configurations were pure lateral impacts. In addition, the sacroiliac joint and femur neck loads were not recorded, and the dummy used was the first production version (WorldSID revision 1). Since that time, the WorldSID was updated several times, including changes in the pelvis area.

Simulation based design and control optimization is widely used to assist the development of highly complex modern downsized turbocharged gasoline direct injection (GDI) engines. In such engines, knock phenomenon is a major constraint that limits performance and fuel economy enhancements. Thus, an accurate knock prediction model is critically important for virtual engine development process. In this paper, an enhanced ignition delay model is proposed for spark ignition (S)I combustion model based on previously developed empirical two-stage ignition delay model using fuel blends [1]. The ignition delay model provides a capability of predicting ignition delay of the end-gas zone for different fuel blends without additional calibration when fuel blending ratio changes. To adapt the ignition delay model to the SI combustion environment, the model is modified to have the sensitivity to the dilution effect by residual gas.

This study aims to provide a set of reference post-mortem human subject tests which can be used, with easily reproducible test conditions, for developing and/or validating pedestrian dummies and computational human body models against a road vehicle. An adjustable generic buck was first developed to represent vehicle front-ends. It was composed of four components: two steel cylindrical tubes screwed on rigid supports in V-form represent the bumper and spoiler respectively, a quarter of a steel cylindrical tube represents the bonnet leading edge, and a steel plate represents the bonnet. These components were positioned differently to represent three types of vehicle profile: a sedan, a SUV and a van. Eleven post-mortem human subjects were then impacted laterally in a mid-gait stance by the bucks at 40 km/h: three tests with the sedan, five with the SUV, and three with the van.

The potential for Augmented Reality (AR) spans many domains. Among other applications, AR can improve the discovery and learning experience for users inspecting a particular item. This paper discusses the use of AR in the automotive context; particularly, on improving the user experience in a dealership show room. Visual augmentation, through a tablet computer or glasses allows users to take part in a self-guided tour in learning about the various features, details, and options associated with a vehicle. The same approach can be applied to other learning scenarios, such as training and maintenance assistance. We evaluated a set of AR Glasses and a general purpose tablet. A table-top showroom was developed demonstrating what the actual user experience would be like for a self-guided dealership tour using natural markers and three-dimensional content spatially registered to physical objects in the user’s field of view.

To reliably implement driver-assist features and ultimately self-driving cars, autonomous driving systems will likely rely on a variety of sensor types including GPS, RADAR, LASER range finders, and cameras. Cameras are an essential sensory component because they lend themselves to the task of identifying object types that a self-driving vehicle is likely to encounter such as pedestrians, cyclists, animals, other cars, or objects on the road. In this paper, we present a feature-based visual odometry algorithm based on a stereo-camera to perform localization relative to the surrounding environment for purposes of navigation and hazard avoidance. Using a stereo-camera enhances the accuracy with respect to monocular visual odometry. The algorithm relies on tracking a local map consisting of sparse 3D map points. By tracking this map across frames, the algorithm makes use of the full history of detected features which reduces the drift in the estimated motion trajectory.

The aim of this study was to investigate the sacroiliac joint injury mechanism. Two test configurations were selected from full scale car crashes conducted with the WorldSID 50th dummy resulting in high sacroiliac joint loads and low pubic symphysis force, i.e. severe conditions for the sacroiliac joint. The two test conditions were reproduced in laboratory using a 150-155 kg guided probe propelled respectively at 8 m/s and 7.5 m/s and with different shapes and orientations for the plate impacting the pelvis. Nine Post Mortem Human Subject (PMHS) were tested in each of the two configurations (eighteen PMHS in total). In order to get information on the time of fracture, eleven strain gauges were glued on the pelvic bone of each PMHS. Results - In the first configuration, five PMHS out of nine sustained AIS2+ pelvic injuries. All five presented sacroiliac joint injuries associated with pubic area injuries.

Injury Risk Curves are developed from cadaver data for sternal deflections produced by anterior, distributed chest loads for a 25, 45, 55, 65 and 75 year-old Small Female, Mid-Size Male and Large Male based on the variations of bone strengths with age. These curves show that the risk of AIS ≥ 3 thoracic injury increases with the age of the person. This observation is consistent with NASS data of frontal accidents which shows that older unbelted drivers have a higher risk of AIS ≥ 3 chest injury than younger drivers.

Injury risk curves for SID-IIs thorax and abdomen rib deflections proposed for future NCAP side impact evaluations were developed from tests conducted with the SID-IIs FRG. Since the floating rib guide is known to reduce the magnitude of the peak rib deflections, injury risk curves developed from SID-IIs FRG data are not appropriate for use with SID-IIs build level D. PMHS injury data from three series of sled tests and one series of whole-body drop tests are paired with thoracic rib deflections from equivalent tests with SID-IIs build level D. Where possible, the rib deflections of SID-IIs build level D were scaled to adjust for differences in impact velocity between the PMHS and SID-IIs tests. Injury risk curves developed by the Mertz-Weber modified median rank method are presented and compared to risk curves developed by other parametric and non-parametric methods.

In 1983, General Motors Corporation (GM) petitioned the National Highway Traffic Safety Administration (NHTSA) to allow the use of the biofidelic Hybrid III midsize adult male dummy as an alternate test device for FMVSS 208 compliance testing of frontal impact, passive restraint systems. To support their petition, GM made public to the international automotive community the limit values that they imposed on the Hybrid III measurements, which were called Injury Assessment Reference Values (IARVs). During the past 20 years, these IARVs have been updated based on relevant biomechanical studies that have been published and scaled to provide IARVs for the Hybrid III and CRABI families of frontal impact dummies. Limit values have also been developed for the biofidelic side impact dummies, BioSID, ES-2 and SID-IIs.