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Investigating human driver behavior enhances the acceptance of the autonomous driving and increases road safety in heterogeneous environments with human-operated and autonomous vehicles. The previously established driver fingerprint model, focuses on the classification of driving style based on CAN bus signals. However, driving styles are inherently complex and influenced by multiple factors, including changing driving environments and driver states. To comprehensively create a driver profile, an in-car measurement system based on the Driver-Driven vehicle-Driving environment (3D) framework is developed. The measurement system records emotional and physiological signals from the driver, including ECG signal and heart rate. A Raspberry Pi camera is utilized on the dashboard to capture the driver's facial expressions and a trained convolutional neural network (CNN) recognizes emotion. To conduct unobtrusive ECG measurements, an ECG sensor is integrated into the steering wheel.

Uncrewed Aerial vehicles are useful for a multitude of applications in today’s age, covering a wide variety of fields such as defense, environmental science, meteorology, emergency responders, search and rescue operations, entertainment robotics, etc. Different types of aircrafts such as fixed wing UAVs, rotor wing UAVs are used for the mentioned applications depending upon the application requirements. One such category of UAVs is the lighter-than-air aircrafts, that provide their own set of advantages over the other types of UAVs. Blimps are among the participants of the lighter-than-air category that are expected to offer advantages such as higher endurance and range, and safer and more comfortable Human-machine-Interaction, etc. as compared to fixed wing and rotor wing UAVs due to their design. A ROS (Robot Operating System) based control system was developed for controlling the blimp.

The paramount importance of titanium alloy in implant materials stems from its exceptional qualities, yet the optimization of bone integration and mitigation of wear and corrosion necessitate advanced technologies. Consequently, there has been a surge in research efforts focusing on surface modification of biomaterials to meet these challenges. This project is dedicated to enhancing the surface of titanium alloys by employing shot peening and powder coatings of titanium oxide and zinc oxide. Comparative analyses were meticulously conducted on the mechanical and wear properties of both treated and untreated specimens, ensuring uniformity in pressure, distance, and time parameters across all experiments. The outcomes underscore the efficacy of both methods in modifying the surface of the titanium alloy, leading to substantial alterations in surface properties.

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

With the current trend of including the evaluation of the risk of brain injuries in vehicle crashes due to rotational kinematics of the head, two injury criteria have been introduced since 2013 – BrIC and DAMAGE. BrIC was developed by NHTSA in 2013 and was suggested for inclusion in the US NCAP for frontal and side crashes. DAMAGE has been developed by UVa under the sponsorship of JAMA and JARI and has been accepted tentatively by the EuroNCAP. Although BrIC in US crash testing is known and reported, DAMAGE in tests of the US fleet is relatively unknown. The current paper will report on DAMAGE in NCAP-like tests and potential future frontal crash tests involving substantial rotation about the three axes of occupant heads. Distribution of DAMAGE of three-point belted occupants without airbags will also be discussed. Prediction of brain injury risks from the tests have been compared to the risks in the real world.

With the development of internet technology and autonomous vehicles (AVs), the multimodal transportation and distribution model based on AVs will be a typical application paradigm in the smart city scenario. Before AVs carry out logistics distribution, it is necessary to plan a reasonable distribution path based on each customer point, and this is also known as Vehicle Routing Problem (VRP). Unlike traditional VRP, the urban logistics distribution process based on multimodal transportation mode will use a set of different types of AVs, mainly including autonomous ground vehicles and unmanned aerial vehicles (UAVs). It is worth pointing out that there is currently no research on combining the planning of AVs distribution paths with the trajectory planning of UAVs. To address this issue, this article establishes a bilevel programming model. The upper-level model aims to plan the optimal delivery plan for AVs, while the lower-level model aims to plan a driving trajectory for UAVs.

With the development of hardware and control theory, the application of quadcopters is constantly expanding. Quadcopters have emerged in many fields, including transportation, exploration, and object grabbing and placement. These application scenarios require accurate, stable, and rapid control, and a suitable dynamic model is one of the prerequisites. At present, many works are related to it, most of which are modeled using the Newton-Euler method. Some works have also adopted other methods, including the Lagrangian and Hamiltonian methods. This article proposes a new method that solves the Hamiltonian equation of a quadcopter expressed in quasi-coordinate. The external forces and motion of the body are expressed in the quasi-coordinate system of the body, and solved through the Hamiltonian equation. This method simplifies operations and improves computational efficiency. Additionally, a single pendulum is attached to the quadcopter to simulate application scenarios.

The flight mechanisms of birds have long inspired efforts to develop bioinspired aerial vehicles. This study presents a computational framework to analyze a flapping mechanism's structural behavior and performance based on the Scotch yoke principle. A three-dimensional CAD model is developed and meshed for finite element analysis in ANSYS. Structural steel is chosen as the material. Static analysis is performed under simulated flapping loads to predict deformation, stresses, fatigue life, and failure points. Preliminary results identify regions of high-stress concentration requiring optimization. Topology optimization is conducted to determine an optimal material layout within defined constraints. Additional shape and compliance optimizations are employed. Comparison of initial and optimized designs significantly reduces maximum deformation and stresses throughout the structure. Fatigue life and safety factors are markedly improved.

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.

The author has developed UV based photocatalytic air purification system (Mathur, 2021, 2122, 2023) that can eliminate all pathogens from the cabin air including COVID-19. In this study, the focus is to determine the risk of infection due to pathogens/germs in the cabin of an automobile. Author has determined the risk of infection by using Wells-Riley model and conducted CFD analysis to determine propagation of virus in cabin as a function of: 1 Cabin Volume & Number of Occupants (Wells-Riley Model in OSA mode): (i) Cabin volume from: Small Sedan, Large Sedan and a SUV; with 4 occupants (males & females); Number of infector 1; Air flowrate (m3/min); (ii) A 15-seater minibus – with 10 occupants (males); Number of infectors 1 & 2; Air flowrate (m3/min) 2 CFD to simulate 4 occupants and 1 infector in an automotive cabin – Current investigation is for talking, coughing and sneezing with blower off in Recirc mode wit (i) Infector in the front seat; (ii) Infector in the rear seat.

Temporal light modulation (TLM), colloquially known as “flicker,” is an issue in almost all lighting applications, due to widespread adoption of LED and OLED sources and their driving electronics. A subset of LED/OLED lighting systems delivers problematic TLM, often in specific types of residential, commercial, outdoor, and vehicular lighting. Dashboard displays, touchscreens, marker lights, taillights, daytime running lights (DRL), interior lighting, etc. frequently use pulse width modulation (PWM) circuits to achieve different luminances for different times of day and users’ visual adaptation levels. The resulting TLM waveforms and viewing conditions can result in distraction and disorientation, nausea, cognitive effects, and serious health consequences in some populations, occurring with or without the driver, passenger, or pedestrian consciously “seeing” the flicker.

Ergonomics plays an important role in automobile design to achieve optimal compatibility between occupants and vehicle components. The overall goal is to ensure that the vehicle design accommodates the target customer group, who come in varied sizes, preferences and tastes. Headroom is one such metric that not only influences accommodation rate but also conveys a visual perception on how spacious the vehicle is. An adequate headroom is necessary for a good seating comfort and a relaxed driving experience. Headroom is intensely discussed in magazine tests and one of the key deciding factors in purchasing a car. SAE J1100 defines a set of measurements and standard procedures for motor vehicle dimensions. H61, W27, W35, H35 and W38 are some of the standard dimensions that relate to headroom and head clearances.

The Large Omnidirectional Child (LODC) developed by the National Highway Traffic Safety Administration (NHTSA) has an improved biofidelity over the currently available Hybrid III 10-year-old (HIII-10C) Anthropomorphic Test Device (ATD). The LODC design incorporates enhancements to many body region subassemblies, including a redesigned HIII-10C head with pediatric mass properties, and the neck, which produces head lag with Z-axis rotation at the atlanto-occipital joint, replicating the observations made from human specimens. The LODC also features a flexible thoracic spine, a multi-point thoracic deflection measurement system, skeletal anthropometry that simulates a child's sitting posture, and an abdomen that can measure belt loading directly. This study presents the development and validation of a dynamic nonlinear finite element model of the complete LODC dummy. Based on the three-dimensional CAD model, Hypermesh was used to generate a mesh of the finite element (FE) LODC model.