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Data-driven driving safety assessment is crucial in understanding the insights of traffic accidents caused by dangerous driving behaviors. Meanwhile, quantifying driving safety through well-defined metrics in real-world naturalistic driving data is also an important step for the operational safety assessment of automated vehicles (AV). However, the lack of flexible data acquisition methods and fine-grained datasets has hindered progress in this critical area. In response to this challenge, we propose a novel dataset for driving safety metrics analysis specifically tailored to car-following situations. Leveraging state-of-the-art Artificial Intelligence (AI) technology, we employ drones to capture high-resolution video data at 12 traffic scenes in the Phoenix metropolitan area. After that, we developed advanced computer vision algorithms and semantically annotated maps to extract precise vehicle trajectories and leader-follower relations among vehicles.

Realistic vehicle fuel economy studies require real-world vehicle driving behavior data along with various factors affecting the fuel consumption. Such studies require data with various vehicles usages for prolonged periods of time. A project dedicated to collecting such data is an enormous and costly undertaking. Alternatively, we propose to utilize two publicly available vehicle travel survey data sets. One is Puget Sound Travel Survey collected using GPS devices in 484 vehicles between 2004 and 2006. Over 750,000 trips were recorded with a 10-second time resolution. The data were obtained to study travel behavior changes in response to time-and-location-variable road tolling. The other is Atlanta Regional Commission Travel Survey conducted for a comprehensive study of the demographic and travel behavior characteristics of residents within the study area.

The explosion of big data has created challenges for both cloud-based systems and Autonomous Vehicles (AVs) in data collection and management. The same challenges are now being realized in developing databases for integrated sensors, streaming, real-time and on-demand services in AVs. With just one AV expecting to generate over 30 Terabytes of data a day, modern NoSQL databases provide opportunities to horizontally scale AV data seamlessly. NoSQL provides solutions designed to accommodate a wide variety of data models such as, key-value, document, column and graph databases. Key-value stores are by nature scalable, fast processing, and distribute horizontally. These databases are tasked with handling several data types including IoT, radar, lidar, ultra-sonic sensors, GPS, odometry, and sensor data while providing streaming and real-time services. NoSQL can store and utilize structured, semi-structured, and unstructured data necessary for multimedia storage needs.

Cavitating flows inside a two-dimensional valve covered orifice (VCO) nozzle were simulated by using the Space-Time Conservation Element and Solution Element (CE/SE) method in conjunction with a homogeneous equilibrium cavitation model. As a validation for present model, cavitation over a NACA0015 hydrofoil was predicted and compared with previous simulation results as well as experimental observations. The model was then used to investigate the effects on internal cavitating flows of different nozzle design parameters, such as the hole size, hole aspect-ratio, hydro-erosion radius, and orifice inclination. Under different conditions, cavitating flows through fuel injectors generated hydraulic flip, supercavitation, full cavitation, and cyclical cavitation phenomena, which are commonly observed in experiments.

Many metrics have been used in an attempt to predict the effects of secondary tasks on driving behavior. Such metrics often give rise to seemingly paradoxical results, with one metric suggesting increased demand and another metric suggesting decreased demand for the same task. For example, for some tasks, drivers maintain their lane well yet detect events relatively poorly. For other tasks, drivers maintain their lane relatively poorly yet detect events relatively well. These seeming paradoxes are not time-accuracy trade-offs or experimental artifacts, because for other tasks, drivers do both well. The paradoxes are resolved if driver demand is modeled in two orthogonal dimensions rather than a single “driver workload” dimension. Principal components analysis (PCA) was applied to the published data from four simulator, track, and open road studies of visual-manual secondary task effects on driving.

Three-dimensional boundary-layer experiments are currently being conducted on a 45° swept wing in the Arizona State University Unsteady Wind Tunnel. Crossflow-dominated transition is produced via a model with contoured end liners to simulate infinite swept-wing flow. Fixed-wavelength stationary and travelling crossflow vortices are observed. The stationary vortex wavelengths vary with Reynolds number as predicted by linear-stability theory but with observed wavelengths which are about 25% smaller than theoretically predicted. The frequencies of the most-amplified moving waves are in agreement with linear-stability theory; travelling waves at higher frequencies than predicted are also observed. These higher-frequency waves may be harmonics of the primary crossflow waves generated by a parametric resonance phenomena. Boundary-layer profiles measured at several spanwise locations show streamwise disturbance profiles characteristic of the crossflow instability.

An equation has been derived to calculate the burning velocity in a CFR engine from the measured flame speed under different turbulent flow fields. The turbulence is generated during the intake stroke as the fresh charge flows through different perforated 360° shrouded intake valves. The shrouds have holes of different sizes, but of the same total flow area. Results show that these valves decrease the cycle-to-cycle variation and produce higher burning velocities than conventional valves, particularly at higher engine speeds. The burning velocity depends on the Reynolds number as well as the turbulence scale.

At the collision moment, a driver’s lower extremity will be in different foot position, which leads to the different posture of the lower extremity with various muscle activations. These will affect the driver’s injury during collision, so it is necessary to investigate further. A simulated collision scene was constructed, and 20 participants (10 male and 10 female) were recruited for the test in a driving simulator. The braking posture and muscle activation of eight major muscles of driver’s lower extremity (both legs) were measured. The muscle activations in different postures were then analyzed. At the collision moment, the right leg was possible to be on the brake (male, 40%; female, 45%), in the air (male, 27.5%; female, 37.5%) or even on the accelerator (male, 25%; female, 12.5%). The left leg was on the floor all along.

The Department of Defense (DOD) has adopted the use of JP-8 under the “single battlefield fuel” policy. Fuel properties of JP-8 which are different from ULSD include cetane number, density, heating value and compressibility (Bulk modulus). While JP8 has advantages compared to ULSD, related to storage, combustion and lower soot emissions, its use cause a drop in the peak power in some military diesel engines. The engines that has loss in power use the Hydraulically actuated Electronic Unit Injection (HEUI) fuel system. The paper explains in details the operation of HEUI including fuel delivery into the injector and its compression to the high injection pressure before its delivery in the combustion chamber. The effect of fuel compressibility on the volume of the fuel that is injected into the combustion chamber is explained in details.

This paper investigates the utilization of Low Earth Orbit (LEO) satellites for vehicle localization and conducts a comparative analysis with traditional Global Navigation Satellite Systems (GNSS)-based methods. With the rise of LEO satellite constellations, such as Starlink, LEO-based vehicle localization may offer solutions to GNSS-related challenges. With a large number of satellites and short communication distance, the LEO-based method has great potential to improve accuracy, reduce warm-up time, and provide a robust localization solution for vehicle applications. In this paper, a dedicated LEO satellite simulator is presented, adaptable to various LEO constellations, making it relevant for evolving technologies beyond older LEO systems like Orbcomm or Iridium. The simulator includes satellite trajectory generation, observable satellite identification, and vehicle localization.

Shell Elements based Parametric Frame Modeling is a powerful CAE tool, which can generate robust frame design concept optimized for NVH and durability quickly when combined with Taguchi Design of Experiments. The scalability of this modeling method includes cross members length/location/section/shape, frame rail segments length/section and kick in/out/up/down angle, and access hole location & size. In the example of the D. O. E. study, more than fifteen parameters were identified and analyzed for frequency and weight. The upper and lower bounds were set for each design parameter based on package and manufacturing constraints. Sixteen Finite Element frame were generated by parametrically updating the base model, which shows this modeling method is comparatively convenient. Sensitivity of these sixteen parameters to the frequency and weight was summarized through statics, so the favorable design alternative can be achieved with the major parameters' combination.

As the deployment of automated vehicles (AVs) on public roadways expands, there is growing interest in establishing metrics that can be used to evaluate vehicle operational safety. The set of Operational Safety Assessment (OSA) metrics, that include several safety envelope-type metrics, previously proposed by the Institute of Automated Mobility (IAM) are a step towards this goal. The safety envelope OSA metrics can be computed using kinematics derived from video data captured by infrastructure-based cameras and thus do not require on-board sensor data or vehicle-to-infrastructure (V2I) connectivity, though either of the latter data sources could enhance kinematic data accuracy. However, the calculation of some metrics includes certain vehicle-specific parameters that must be assumed or estimated if they are not known a priori or communicated directly by the vehicle.

Methods of achieving crash-worthiness of aircraft in general are discussed. Specific conclusions are drawn with regard to the design loads for occupant restraint systems. A “ programmed break” concept for the fuselage of large aircraft is presented, and additional research which is needed to provide increased survival in accidents is suggested.

In this age of the Internet of Things, people expect in-vehicle interfaces to work just like a smartphone. Our understanding of the reality of in-vehicle interfaces is quite contrary to that. We review the fundamental principles and metrics for automotive visual-manual driver distraction guidelines. We note the rise in portable device usage in vehicles, and debunk the myth of increased crash risk when conversing on a wireless device. We advocate that portable electronic device makers such as Apple and Google should adopt driver distraction guidelines for application developers (whether for tethered or untethered device use in the vehicle). We present two design implications relevant to safe driving. First, the Rule of Platform Appropriateness: design with basic principles of ergonomics, and with driver's limited visual, manual and cognitive capacity, in mind. Second, the Rule of Simplicity: thoughtful reduction in the complexity of in-vehicle interfaces.

Stability and transition experiments are conducted in the Arizona State University Unsteady Wind Tunnel on a 45° swept airfoil. The pressure gradient is designed so that transition and stability are purely crossflow-dominated. Flow visualization and hot-wire measurements show that the development of the crossflow vortices is influenced by roughness near (not at) the attachment-line. Comparisons of transition location are made between a painted surface (distributed 9 μm peaks and valleys on the surface), a machine-polished surface (0.5 μm rms finish), and a hand-polished surface (0.25 μm rms finish). Then, isolated 6 - 9 μm roughness elements are placed near the attachment line on the airfoil surface under conditions of the final polish (0.25 μm rms). These elements amplify a centered stationary crossflow vortex and its neighbors, resulting in localized early transition. The diameter and height of these roughness elements are varied in a systematic manner.

There has been recent progress over the past 10 years in research comparing 6-year-old thoracic and abdominal response of pediatric volunteers, pediatric post mortem human subjects (PMHS), animal surrogates, and 6-year-old ATDs. Although progress has been made to guide scaling laws of adult to pediatric thorax and abdomen data for use in ATD design and development of finite element models, further effort is needed, particularly with respect to lateral impacts. The objective of the current study was to use the impact response data of age equivalent swine from Yaek et al. (2018) to assess the validity of scaling laws used to develop lateral impact response corridors from adult porcine surrogate equivalents (PSE) to the 3-year-old, 6-year-old, and 10-year-old for the thorax and abdominal body regions.

The piston secondary motion is an important phenomenon in internal combustion (IC) engine. It occurs due to the piston transverse and rotational motion during piston reciprocating motion. The piston secondary motion results in engine friction and engine noise. There has been lot of research activities going on in piston secondary motion using both analytical models and experimental studies. These studies are aimed at reducing the engine friction as well as the noise generated due to piston secondary motion. The aim of this paper is to compile the research actives carried out on the piston secondary motion and discuss the possible research opportunities for reducing the IC engine piston secondary motion.

Dr. Edwards Deming spirited organizations “If you can't define what you do as a process, you don't know what your job is” (Weinstein, 1999). Significant effort has been conducted to engineer, deploy and control a process to product development. This coverage reflects impact of product development process on developing and producing consumer products effectively and successfully for the future. Reflecting on the past and observing mistakes and lessons learned would be key to help our companies to engineer future or modify existing product development processes. This paper examines views, types and needs of product development process from a six sigma perspective to enable deliver of competitive products with cost and time in mind. Learning from the past enlightens us to identify opportunities that would drive evolution and trend of product development process into the future. A recommended view is presented that changes the way product development process is designed and implemented.

The Wayne State University (WSU) EcoCAR2 student team designed, modeled, Model-In-the-Loop (MIL) tested, Software-In-the-Loop (SIL) simulation tested, and Hardware-In-the-Loop (HIL) simulation tested the team's conversion design for taking a 2013 Chevrolet Malibu and converting it into a Parallel-Through-The-Road (PTTR) plug-in hybrid. The 2013 Malibu is a conventional Front Wheel Drive (FWD) vehicle and the team's conversion design keeps the conventional FWD and adds a Rear Wheel Drive (RWD) powertrain consisting of an electric motor, a single speed reduction gearbox and a differential to drive the rear wheels -where none of these previously existed on the rear wheels. The RWD addition creates the PTTR hybrid powertrain architecture of two driven axles where the mechanical torque path connection between the two powertrains is through the road, rather than a mechanical torque path through gears, chains, or shafts.

Today’s advanced vehicles have high degree of interaction due to numerous sensors, actuators and also with complex communication within the control units. In order to hack a vehicle, it has to be within a certain range of communication. Here, we discuss the On-Board Diagnostic (OBD) regulations for next generation BEV/HEV, its vulnerabilities and cybersecurity threats that come with hacking. We propose three cybersecurity attack detection and defense methods: Cyber-Attack detection algorithm, Time-Based CAN Intrusion Detection Method and, Feistel Cipher Block Method. These control methods autonomously diagnose a cybersecurity problem in a vehicle’s onboard system using an OBD interface, such as OBD-II when a fault caused by a cyberattack is detected, All of this is achieved in an internal communication network structure. The results discussed here focus on the first detection method that is Cyber-Attack detection algorithm.