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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.

ADAS features development involves multidisciplinary technical fields, as well as extensive variety of different sensors and actuators, therefore the early design process requires much more resources and time to collaborate and implement. This paper will demonstrate an alternative way of developing prototype ADAS concept features by using remote control car with low cost hobby type of controllers, such as Arduino Due and Raspberry Pi. Camera and a one-beam type Lidar are implemented together with Raspberry Pi. OpenCV free open source software is also used for developing lane detection and object recognition. In this paper, we demonstrate that low cost frame work can be used for the high level concept algorithm architecture, development, and potential operation, as well as high level base testing of various features and functionalities. The developed RC vehicle can be used as a prototype of the early design phase as well as a functional safety testing bench.

The purpose of this paper is to demonstrate the impact of low- floor bus seating configuration, passenger load factor (PLF) and passenger characteristics on individual boarding and disembarking (B-D) times -a key component of vehicle dwell time and overall transit system performance. A laboratory study was conducted using a static full-scale mock-up of a low-floor bus. Users of wheeled mobility devices (n=48) and walking aids (n=22), and visually impaired (n=17) and able-bodied (n=17) users evaluated three bus layout configurations at two PLF levels yielding information on B-D performance. Statistical regression models of B-D times helped quantify relative contributions of layout, PLF, and user characteristics viz., impairment type, power grip strength, and speed of ambulation or wheelchair propulsion. Wheeled mobility device users, and individuals with lower grip strength and slower speed were impacted greater by vehicle design resulting in increased dwell time.

This study is to explore the application of electrorheology (ER) to the real-time control of damping forces that are transmitted through the nose landing gear for an F-106B aircraft. The main part of the landing gear is a strut that consists of a pneumatic spring and an ER controlled damper that is situated on the strut centerline and applies a force directly opposing the vertical displacement of the nose wheel. The damping element rotates in response to strut displacement, employing a co-axial arrangement of stator and rotor plates connected to the opposing electrodes in the control circuit. The vertical displacement is converted into rotation of the damper through a screw-nut mechanism. The ER fluid between the electrodes is thus engaged in shear along circumferential lines of action. This design results in a fast time response and a high ratio of strut forces achieved under ER- vs. zero-field control. Compact size and simplicity in fabrication are also attained.

In FOA (First Order Analysis) any vehicle body structure might be interpreted as a collective simple structure that can be decomposed into 3 fundamental structure types. The first structure is the “BEAM”, whose cross sectional properties as well as its material dominates the mechanical behavior, the second is the “PANEL (shear panel, plate, and shell)”, whose mechanical behavior can be varied by changing its geometrical properties in the thickness direction, i.e. adding beads or flanges. The third structure is the “JOINT”, which connects the proceeding structures, and transfer complex three-dimensional loads with three-dimensional deformation. In the present work, we shall propose a methodology to identify a portion of an arbitrary FE model of an automotive body structure, with a “BEAM” structure in the FOA approach. In the latter chapter of this paper, cross section loads will be related with cross sectional properties in the aspect of the element strain energy concept.

Automated vehicles (AVs)—and the automated driving systems (ADSs) that enable them—are increasing in prevalence but remain far from ubiquitous. Progress has occurred in spurts, followed by lulls, while the motor transportation system learns to design, deploy, and regulate AVs. Automated Vehicles: A Human/Machine Co-learning Experience focuses on how engineers, regulators, and road users are all learning about a technology that has the potential to transform society. Those engaged in the design of ADSs and AVs may find it useful to consider that the spurts and lulls and stakeholder tussles are a normal part of technology transformations; however, this report will provide suggestions for effective stakeholder engagement. Click here to access the full SAE EDGETM Research Report portfolio.

The characterization of human drivers' performance is of great significance for highway design, driver state monitoring, and the development of automotive active safety systems. Many earlier studies are restricted by experimental scope, the number and diversity of human subjects, and the accuracy and extent of measured variables. In this work, driver lateral control performance on limited-access highways is quantified by utilizing a comprehensive naturalistic driving database, with the emphasis on measures of vehicle lateral position and time to lane crossing (TLC). Normative values at various speed ranges are reported. The results represent a statistical view of baseline on-road naturalistic driving performance, and can be used for quantitative studies such as driver impairment and alertness monitoring, the triggering of lane departure warning systems, and highway design.

The Hybrid Finite Element Analysis (HFEA) method is based on combining conventional Finite Element Analysis (FEA) with analytical solutions and energy methods for mid-frequency computations. The method is appropriate for computing the vibration of structures which are comprised by stiff load bearing components and flexible panels attached to them; and for considering structure-borne loadings with the excitations applied on the load bearing members. In such situations, the difficulty in using conventional FEA at higher frequencies originates from requiring a very large number of elements in order to capture the flexible wavelength of the panel members which are present in a structure. In the HFEA the conventional FEA model is modified by de-activating the bending behavior of the flexible panels in the FEA computations and introducing instead a large number of dynamic impedance elements for representing the omitted bending behavior of the panels.

Strain gage instrumented transducers were used to measure the cord loads at a number of locations in several different automotive tires loaded against both flat and cylindrical road wheel surfaces. The two basic types of cord load fluctuation encountered in all automobile tires have been identified from these measurements, and the most severe location for cord load fluctuations has been closely bracketed. By these measurements, it has been possible to show that for each tire definite relations exist between the cord loads induced while running on a cylindrical drum and while running on a flat surface. The maximum cord load fluctuations in a tire are the same for the NBS roadwheel and flat surface when the tire is loaded against the roadwheel with a load of between 85 and 90% of that used on the flat surface.

A new method for crashworthiness optimization of vehicle structures is presented, where an early design exploration is done by the optimization of an equivalent mechanism approximating a vehicle structure. An equivalent mechanism (EM) is a network of rigid bodies connected by prismatic and revolute joints with special nonlinear springs. These springs are designed to mimic the force-displacement characteristics of thin-walled beams often found in the vehicle body structures. A computer software is implemented that allows the designer to quickly construct an equivalent mechanism model of a structure using a graphical user interface (GUI) to optimize the model for given objectives prior to final tuning using finite element (FE) models. A case study of a vehicle front substructure consisting of mid and lower rails is presented, which demonstrates that the new approach can obtain a better design with less computational resources than the direct optimization of a FE model.

A method is presented here that detects aircraft tail surface icing that might normally be unobserved by the flight crew. Such icing can be detected through the action of highly computationally efficient signal processing of existing sensor signals using a so-called failure detection filter (FDF). The FDF creates a unique output signature permitting relatively early detection of tail surface icing. The FDF incorporates a stable state estimator from which the icing signature is created. This estimator is robust to analytical modeling errors or uncertainties, and to process noise (e.g. turbulence). Excellent performance of the method is demonstrated via simulation.

Testing for vehicle emissions and fuel economy certification occurs primarily on chassis dynamometers in a laboratory setting and therefore the actual road conditions, such as forces due to tire rolling resistance and internal friction, must be simulated. Test track coastdown procedures measure vehicle road load forces and produce an equation which relates these forces to velocity. The recent inclusion of onboard anemometry has allowed the coastdown procedure to account for varying wind effects; however, the new anemometer based mechanical loss coefficients do not take into account ambient weather conditions. The two purposes of this study are (1) to determine the new tire rolling resistance temperature correction coefficient that should be used when test ambient temperature is different from the standard reference value of 68°F, and (2) to investigate the effects of auxiliary measurements, such as other ambient conditions and vehicle settings, on this correction coefficient.

Intelligent Vehicle-Highway Systems (IVHS) improve the operation of cars and trucks on public roads by combining information technology with road transportation technologies. The basic ideas about IVHS are by no means new but a number of converging forces have encouraged significant IVHS development in North America recently. Based on the results of a Delphi survey to project realistic future scenarios, both applied and fundamental research agenda are being formulated in a Michigan-based IVHS program to push the IVHS technologies for advanced motorist information systems and for backup vehicle controls under emergency conditions. The scope of the research agenda includes social/human elements as well as hardware and software technological systems. The Michigan research program is expected to contribute to the development of IVHS in North America, both technically and institutionally.

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?”

As new technology is added to vehicles and traffic congestion increases, there is a concern that drivers will be overloaded. As a result, there has been considerable interest in measuring driver workload. This can be achieved using many methods, with subjective assessments such as the NASA Task Loading Index (TLX) being most popular. Unfortunately, the TLX is unanchored, so there is no way to compare TLX values between studies, thus limiting the value of those evaluations. In response, a method was created to anchor overall workload ratings. To develop this method, 24 subjects rated the workload of clips of forward scenes collected while driving on rural, urban, and limited-access roads in relation to 2 looped anchor clips. Those clips corresponded to Level of Service (LOS) A and E (light and heavy traffic) and were assigned values of 2 and 6 respectively.

The results of an experimental investigation of the flow in the near wake of a generic Sport Utility Vehicle (SUV) model are presented. The main goals of the study are to gain a better understanding of the external aerodynamics of SUVs, and to obtain a comprehensive experimental database that can be used as a benchmark to validate math-based CFD simulations for external aerodynamics. Data obtained in this study include the instantaneous and mean pressures, as well as mean velocities and turbulent quantities at various locations in the near wake. Mean pressure coefficients on the base of the SUV model vary from −0.23 to −0.1. The spectrum of the pressure coefficient fluctuation at the base of the model has a weak peak at a Strouhal number of 0.07. PIV measurements show a complex three-dimensional recirculation region behind the model of length approximately 1.2 times the width of the model.

A failure prediction methodology that can predict sheet metal failure under arbitrary deformation histories including rotating principal stretch directions and bending/unbending with consideration of damage evolution is reviewed in this paper. An anisotropic Gurson yield criterion is adopted to characterize the effects of microvoids on the load carrying capacity of sheet metals where Hill’s quadratic anisotropic yield criterion is used to describe the matrix normal anisotropy and planar isotropy. The evolution of the void damage is based on the growth, nucleation and coalescence of microvoids. Mroz’s anisotropic hardening rule, which was proposed based on the cyclic plastic behavior of metals observed in experiments, is generalized to characterize the anisotropic hardening behavior due to loading/unloading with consideration of the evolution of void volume fraction. The effects of yield surface curvature are also included in the plasticity model.

We have developed new CAE tools in the concept design process based on First Order Analysis (FOA). Joints are often modeled by rotational spring elements. However, it is very difficult to obtain good accuracy. We think that one of the reasons is the influence of the nonlinear behavior due to local elastic buckling. Automotive body structures have the possibility of causing local buckling since they are constructed by thin walled cross sections. In this paper we focus on this behavior. First of all, we present the concept of joint analysis in FOA, using global-local analysis. After that, we research nonlinear behavior in order to construct an accurate joint reduced model. (1) The influence of local buckling is shown using uniform beams. (2) Stiffness decrease of joints due to a local buckling is shown. (3) The way of treating joint modeling considering nonlinear behavior is proposed.

Many highway accidents are caused by distracted drivers and those suffering from drowsy driver syndrome. A driver alert indicating a lane departure could thwart such accidents, saving lives and making our roads safer. Products called Lane Departure Warning Systems (LDWS) have been developed to alert drivers of a lane departure. However, due to their high cost, lane departure warning systems are available only on luxury vehicles, barring their benefits from the majority of drivers. With Field Programmable Gate Arrays (FPGA) becoming more powerful and more affordable, a LDWS implementation utilizing hardware rather than software to conduct image processing eliminates the need for a costly high-power microprocessor, and could bring LDWS to a broader user base. This paper will discuss an FPGA based approach to LDWS. The proof-of-concept system is based on a Xilinx FPGA, taking its image data from an off-the-shelf NTSC camera.

The front rail, as one main energy absorption component of vehicle front structures, should present steady progressive collapse along its axis and avoid bending collapse during the front oblique impact, but when the angle of loading direction is larger than some critical angle, it will appear bending collapse causing reduced capability of crash energy absorption. This paper is concerned with crashworthiness design of the front rail on a vehicle chassis frame structure considering uncertain crash directions. The objective is to improve the crash direction adaptability of the front rail, without deteriorating the vehicle's crashworthiness performance. Magic Cube (MQ) approach, a systematic design approach, is conducted to analyze the design problem. By applying Space Decomposition of MQ, an equivalent model of the vehicle chassis frame is generated, which simplifies the design problem.