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Often, when assessing the distraction or ease of use of an in-vehicle task (such as entering a destination using the street address method), the first question is “How long does the task take on average?” Engineers routinely resolve this question using computational models. For in-vehicle tasks, “how long” is estimated by summing times for the included task elements (e.g., decide what to do, press a button) from SAE Recommended Practice J2365 or now using new static (while parked) data presented here. Times for the occlusion conditions in J2365 and the NHTSA Distraction Guidelines can be determined using static data and Pettitt’s Method or Purucker’s Method. These first approximations are reasonable and can be determined quickly. The next question usually is “How likely is it that the task will exceed some limit?”

With the development of vehicles equipped with automated driving systems, the need for systematic evaluation of AV performance has grown increasingly imperative. According to ISO 34502, one of the safety test objectives is to learn the minimum performance levels required for diverse scenarios. To address this need, this paper combines two essential methodologies - scenario-based testing procedures and scoring systems - to systematically evaluate the behavioral competence of AVs. In this study, we conduct comprehensive testing across diverse scenarios within a simulator environment following Mcity AV Driver Licensing Test procedure. These scenarios span several common real-world driving situations, including BV Cut-in, BV Lane Departure into VUT Path from Opposite Direction, BV Left Turn Across VUT Path, and BV Right Turn into VUT Path scenarios.

In-flight icing significantly influences the design of large passenger aircraft. Relevant aspects include sizing of the main aerodynamic surfaces, provision of anti-icing systems, and setting of operational restrictions. Empennages of large passenger aircraft are particularly affected due to the small leading edge radius, and the requirement to generate considerable lift for round out and flare, following an extended period of descent often in icing conditions. This paper describes a CFD-based investigation of the effects of sweep on the aerodynamic performance of a novel forward-swept horizontal stabilizer concept in icing conditions. The concept features an unconventional forward sweep, combined with a high lift leading edge extension (LEX) located within a fuselage induced droplet shadow zone, providing passive protection from icing.

This paper introduces the Lagrangian particle tracking technology readily available in Ansys Fluent in the in-flight icing simulation workflow, which normally uses the Eulerian approach for droplet flows. The Lagrangian solver is incorporated in the Fluent Icing workspace which is to become the next-gen in-flight icing simulation tool provided by Ansys. Lagrangian tracking will eventually be used for SLD and ice crystal rebound and re-impingement calculations in the Ansys workflow. Here we introduce some preliminary results with the current state of its implementation as of Fluent Icing release 2023R2. Example cases include several selections from the 1st Ice prediction workshop with experimental comparisons as well as results obtained earlier with the Eulerian droplet solution strategy. Collection efficiency comparisons on clean geometries show good agreement between Eulerian and Lagrangian methods when the particle seeds are in the millions range.

This paper presents the current state of a three-layer surface icing model for ice crystal icing risk assessment in aircraft engines, being developed jointly by Ansys and Honeywell to account for possible heat transfer from inside an engine into the flow path where ice accretion occurs. The bottom layer of the proposed model represents a thin metal sheet as a substrate surface to conductively transfer heat from an engine-internal reservoir to the ice layer. The middle layer is accretion ice with a porous structure able to hold a certain amount of liquid water. A shallow water film layer on the top receives impinged ice crystals. A mass and energy balance calculation for the film determines ice accretion rate. Water wicking and recovery is introduced to transfer liquid water between film layer and porous ice accretion layer.

This paper studies the level of confidence and applicability of CFD simulations using steady-state Reynolds-Averaged Navier-Stokes (RANS) in predicting aerodynamic performance losses on swept-wings due to contamination with ice accreted in-flight. The wing geometry selected for the study is the 65%-scale Common Research Model (CRM65) main wing, for which NASA Glenn Research Center’s Icing Research Tunnel has generated experimental ice shapes for the inboard, mid-span, and outboard sections. The reproductions at various levels of fidelity from detailed 3D scans of these ice shapes have been used in recent aerodynamic testing at the Office National d’Etudes et Recherches Aérospatiales (ONERA) and Wichita State University (WSU) wind tunnels. The ONERA tests were at higher Reynolds number range in the order of 10 million, while the WSU tests were in the order of 1 million.

Motor vehicle crashes involving child Vulnerable Road Users (VRUs) remain a critical public health concern in the United States. While previous studies successfully utilized the crash scenario typology to examine traffic crashes, these studies focus on all types of motor vehicle crashes thus the method might not apply to VRU crashes. Therefore, to better understand the context and causes of child VRU crashes on the U.S. road, this paper proposes a multi-step framework to define crash scenario typology based on the Fatality Analysis Reporting System (FARS) and the Crash Report Sampling System (CRSS). A comprehensive examination of the data elements in FARS and CRSS was first conducted to determine elements that could facilitate crash scenario identification from a systematic perspective. A follow-up context description depicts the typical behavioral, environmental, and vehicular conditions associated with an identified crash scenario.

Making manned and remotely-controlled wheeled and tracked vehicles easier to drive, especially off-road, is of great interest to the U.S. Army. If vehicles are easier to drive (especially closed hatch) or if they are driven autonomously, then drivers could perform additional tasks (e.g., operating weapons or communication systems), leading to reduced crew sizes. Further, poorly driven vehicles are more likely to get stuck, roll over, or encounter mines or improvised explosive devices, whereby the vehicle can no longer perform its mission and crew member safety is jeopardized. HMI technology and systems to support human drivers (e.g., autonomous driving systems, in-vehicle monitors or head-mounted displays, various control devices (including game controllers), navigation and route-planning systems) need to be evaluated, which traditionally occurs in mission-specific (and incomparable) evaluations.

The automotive industry widely accepted the launch of electric vehicles in the global market, resulting in the emergence of many new areas, including battery health, inverter design, and motor dynamics. Maintaining the desired thermal stress is required to achieve augmented performance along with the optimal design of these components. The HVAC system controls the coolant and refrigerant fluid pressures to maintain the temperatures of [Battery, Inverter, Motor] in a definite range. However, identifying the prominent factors affecting the thermal stress of electric vehicle components and their effect on temperature variation was not investigated in real-time. Therefore, this article defines the vector electric vehicle thermal operating point (EVTHOP) as the first step with three elements [instantaneous battery temperature, instantaneous inverter temperature, instantaneous stator temperature].

With the evolution of telemetry technology in vehicles, Advanced Automatic Collision Notification (AACN), which detects occupants at risk of serious injury in the event of a crash and triages them to the trauma center quickly, may greatly improve their treatment. An Injury Severity Prediction (ISP) algorithm for AACN was developed using a logistic regression model to predict the probability of sustaining an Injury Severity Score (ISS) 15+ injury. National Automotive Sampling System Crashworthiness Data System (NASS-CDS: 1999-2015) and model year 2000 or later were filtered for new case selection criteria, based on vehicle body type, to match Subaru vehicle category. This new proposed algorithm uses crash direction, change in velocity, multiple impacts, seat belt use, vehicle type, presence of any older occupant, and presence of any female occupant.

Tanker trucks are commonly used for transporting liquid material including chemical and petroleum products. On the one hand, tanker trucks are susceptible to rollover accidents due to the high center of gravity when they are loaded and due to the liquid sloshing effects when the tank is partially filled. On the other hand, tanker truck rollover accidents are among the most dangerous vehicle crashes, frequently resulting in serious to fatal driver injuries and significant property damage, because the liquid cargo is often hazardous and flammable. Therefore, effective schemes for tanker truck rollover avoidance are highly desirable and can bring a considerable amount of societal benefit. Yet, the development of such schemes is challenging, as tanker trucks can operate in various environments and be affected by manufacturing variability, aging, degradation, etc. This paper considers the use of Learning Reference Governor (LRG) for tanker truck rollover avoidance.

In order to achieve the purpose of saving energy and reducing emission, the improvement of aerodynamic performance plays an increasingly crucial role for car manufacturers. Previous studies have confirmed the validity of gradient-based adjoint algorithm for its high efficiency in shape optimization. In this paper, two important aspects of adjoint approach were explored. One is vehicle aerodynamic optimization with multiple objectives, and the other is using time-averaged flow results as the primal solution, both are issues of high interest in recent applications. First, adjoint shape optimization with steady-state and time-averaged flow simulations were respectively calculated and comparatively discussed based on a production SUV. The shape modifications of the two cases indicated that the impact of primal solution on design change could not be neglected, due to the different intrinsic codes of steady and transient turbulence models.

Knee airbags (KABs) are one countermeasure in newer vehicles that could influence lower extremity (LEX) injury, the most frequently injured body region in frontal crashes. To determine the effect of KABs on LEX injury for drivers in frontal crashes, the analysis examined moderate or greater LEX injury (AIS 2+) in two datasets. Logistic regression considered six main effect factors (KAB deployment, BMI, age, sex, belt status, driver compartment intrusion). Eighty-five cases with KAB deployment from the Crash Injury Research and Engineering Network (CIREN) database were supplemented with 8 cases from the International Center for Automotive Medicine (ICAM) database and compared to 289 CIREN non-KAB cases. All cases evaluated drivers in frontal impacts (11 to 1 o’clock Principal Direction of Force) with known belt use in 2004 and newer model year vehicles. Results of the CIREN/ICAM dataset were compared to analysis of a similar dataset from NASS-CDS (5441 total cases, 418 KAB-deployed).

In-vehicle infotainment (IVI) platforms are getting increasingly connected. Besides OEM apps and services, the next generation of IVI platforms are expected to offer integration of third-party apps. Under this anticipated business model, vehicular sensor and event data can be collected and shared with selected third-party apps. To accommodate this trend, Google has been pushing towards standardization among proprietary IVI operating systems with their Android Automotive platform which runs natively on the vehicle’s IVI platform. Unlike Android Auto’s limited functionality of display-projecting certain smartphone apps to the IVI screen, Android Automotive will have access to the in-vehicle network (IVN), and will be able to read and share various vehicular sensor data with third-party apps. This increased connectivity opens new business opportunities for both the car manufacturer as well as third-party businesses, but also introduces a new attack surface on the vehicle.

Due to the increasingly stringent environmental regulations all around the world confronted by exhaust emission and energy consumption, improving fuel economy has been the top priority for most automotive manufacturers. In this context, the basic process for vehicle shape development has evolved into optimizing the design to achieve better aerodynamic characteristics, especially drag reduction. Of all the optimization approaches, the gradient-based adjoint method has currently received extensive attention for its high efficiency in calculating the objective sensitivity with respect to geometry parameters, which is the first and foremost step for subsequent shape modification. In this work, the main goal is to explore the adjoint method through optimizing the vehicle shape for a lower drag based on a production SUV. Firstly, the influence of different mesh schemes was discussed on sensitivity prediction of aerodynamic drag.

This SAE EDGE Research Report explores the many legal issues raised by the advent of automated vehicles. While promised to bring major changes to our lives, there are significant legal challenges that have to be overcome before they can see widespread use. A century’s worth of law and regulation were written with only human drivers in mind, meaning they have to be amended before machines can take the wheel. Everything from key federal safety regulations down to local parking laws will have to shift in the face of AVs. This report undertakes an examination of the AV laws of Nevada, California, Michigan, and Arizona, along with two failed federal AV bills, to better understand how lawmakers have approached the technology. States have traditionally regulated a great deal of what happens on the road, but does that still make sense in a world with AVs? Would the nascent AV industry be able to survive in a world with fifty potential sets of rules?

A full-automated CFD mesh generation technique has been developed and implemented for 3-D aircraft icing simulations to permit robust 45-minute ice accretion simulations in support of icing certification campaigns. The changes in the shape of the aircraft surfaces due to accreting ice and their effects on the air and droplet flow are accounted for in a quasi-steady manner by subdividing the total icing time into sequential steps of shorter duration, updating the computational grid at each step. This “multi-shot” ice accretion approach requires robust and accurate grid re-meshing for it to be embedded in engineering design and analysis workflows. ANSYS FENSAP-ICE has been coupled to Fluent Meshing to take advantage of generic and highly automated surface displacement and mesh wrapping tools. A wide spectrum of geometries is supported, ranging from full-size aircraft to air data probes, turbomachinery components, rotors and propellers.

A 3D CFD methodology is presented to simulate ice build-up on propeller blades exposed to known icing conditions in flight, with automatic blade pitch variation at constant RPM to maintain the desired thrust. One blade of a six-blade propeller and a 70-passenger twin-engine turboprop are analyzed as stand-alone components in a multi-shot quasi-steady icing simulation. The thrust that must be generated by the propellers is obtained from the drag computed on the aircraft. The flight conditions are typical for a 70-passenger twin-engine turboprop in a holding pattern in Appendix C icing conditions: 190 kts at an altitude of 6,000 ft. The rotation rate remains constant at 850 rpm, a typical operating condition for this flight envelope.

A CFD simulation methodology for the inclusion of the post-impact trajectories of splashing/bouncing Supercooled Large Droplets (SLDs) and film detachment is introduced and validated. Several scenarios are tested to demonstrate how different parameters affect the simulations. Including re-injecting droplet flows due to splashing/bouncing and film detachment has a significant effect on the accuracy of the validations shown in the article. Validation results demonstrate very good agreement with the experimental data. This approach is then applied to a full-scale twin-engine turboprop to compute water impingement on the wings and the empennage.

A CFD simulation methodology is presented to evaluate the ice that sheds from rotating components. The shedding detection is handled by coupling the ice accretion and stress analysis solvers to periodically check for the propagation of crack fronts and possible detachment. A novel approach for crack propagation is highlighted where no change in mesh topology is required. The entire computation from flow to impingement, ice accretion and crack analysis only requires a single mesh. The accretion and stress module are validated individually with published data. The analysis is extended to demonstrate potential shedding scenarios on three complex industrially-relevant 3D cases: a helicopter blade, an engine fan blade and a turboprop propeller. The largest shed fragment will be analyzed in the context of FOD damage to neighboring aircraft/component surfaces.