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Recently, various calibration techniques proposed for extrinsic calibration for Autonomous Vehicles (AVs) mostly rely on the camera 2D images and depth map to calibrate the 3D LiDAR points. While most methods work with the whole frame, some methods use the objects in the frame to perform the calibration.

The Steel and Foam Energy Reduction (SAFER) barrier, which encloses the whole oval, is detected by a three-dimensional (3D)-LiDAR, and the transformation of the barrier to the ego vehicle is estimated. We have validated the new approach via different simulation methods.

A cooperation between many sensors such as LIDAR, Radar and camera helps to enhance the safety. Apart from the importance of having a reliable object detector, the safety system should have requisite capabilities to make reasonable decisions in the moment.

The Chrono::Sensor module provides simulation of a variety of sensor (IMU, GPS, Camera, Lidar); the exteroceptive sensors simulation is based on ray-tracing. SynChrono was demonstrated to run more than 120 vehicles in real time, using the Message Passing Interface (MPI) standard in which one CPU core runs the simulation of one vehicle.

In the early days, vehicles sensed the surrounding environment through sensors such as cameras, radar, and lidar. With the development of 5G technology and the Vehicle-to-everything (V2X), other information from the roadside can also be received by vehicles.

Abstract This article presents a novel approach to optimize the placement of light detection and ranging (LiDAR) sensors in autonomous driving vehicles using machine learning. As autonomous driving technology advances, LiDAR sensors play a crucial role in providing accurate collision data for environmental perception. ...As autonomous driving technology advances, LiDAR sensors play a crucial role in providing accurate collision data for environmental perception.

As for LiDAR SLAM system, it faces great challenges in scenarios where there are repetitive and sparse features. ...This paper proposes a construction method of LiDAR anchor constraints to improve the robustness of the SLAM system in the above challenging environment.

Environment simulation is obtained using the AV simulator, CARLA which provides realistic scenarios and sensor information such as Radar, Lidar etc. MATLAB runs the vehicle, powertrain and control models of the vehicle allowing for the implementation and testing of customized models and algorithms.

However, the global positioning system (GPS) cannot be used in the underground parking lot and the localization method based on lidar is too expensive. In response to solve this problem, we propose a simultaneous localization and mapping system with the semantic information of parking slots (PS-SLAM), which is based on visual-inertial and around view images.

This challenge is addressed in this work for lidar sensors. The lidar equation was previously employed in this context to derive estimates of a lidar’s maximum range in different weather conditions. ...In this work, we present a stochastic simulation framework based on a probabilistic extension of the lidar equation, to quantify the effect of adverse rainfall conditions on a lidar’s raw detection performance. ...Combining the effect of other noise sources with the presented framework in a ray tracer is an opportunity for realistic physical lidar simulations and would allow to virtually estimate the performance of a lidar’s object detection and tracking performance.

The suggested method doesn’t need expensive additional sensors such as optical or lidar sensor, also it shows better performance in real car environment compared to other algorithms based on vehicle dynamics.

Firstly, based on the principle that parking spaces should be parallel or vertical to a corresponding path, a topological parking lot map is designed by using the point cloud data collected by LiDAR sensor. This map is consist of road node coordinates, adjacent matrix and parking space information.

Editorial Safety sells, they say. Should it sell driving automation? The Navigator Vehicle connectivity moves to the next generation Lockered and Loaded With its innovative Transporter, AV startup Udelv rethinks the entire concept of parcel delivery. Navigating Deep Learning to Improve ADAS How edge computing drives real-time decision making in AI for smarter, safer automated vehicles. Ensuring No Child Left Inside Up-armed with new key technologies, Gentex is making 'holistic' driver and cabin monitoring a core-brand hallmark. Precision Tech the 'Backbone' to CNH's Digital Strategy The ag and construction equipment OEM bolsters its tech stack to accelerate development of precision and autonomous solutions. AV Powers Bring May Flowers Michigan-based May Mobility survived rocky roads thanks to faith in its founders' vision and the company's autonomous tech. The Short-flight Alternative The Budget Airline Car is an EV alt-shuttle seating six adults, with luggage storage in each door.

As technology and functionality of vehicle systems change, so do data recording needs. In ADS-dedicated vehicles (DV), the ADS perceives the environment and handles vehicle motion control, i.e., the dynamic driving task (DDT), as described in SAE J3016. When an ADS takes the place of a human driver, its sensing, processing, and control systems necessitate new considerations for data recording. Data recording is important to crash reconstruction, system performance investigations, and event analysis. It enables industry-wide improvements in ADS safety. This best practice makes recommendations for the ADS-DV data needed to support: (1) information about what the ADS "saw" and "did" and (2) identify the technology-relevant factors that contributed to the event.

Apple’s mobile phone LiDAR capabilities were previously evaluated to obtain geometry from multiple exemplar vehicles, but results were inconsistent and less accurate than traditional ground-based LiDAR (SAE Technical Paper 2022-01-0832. ...Apple’s mobile phone LiDAR capabilities were previously evaluated to obtain geometry from multiple exemplar vehicles, but results were inconsistent and less accurate than traditional ground-based LiDAR (SAE Technical Paper 2022-01-0832. Miller, Hashemian, Gillihan, Helms). This paper builds upon existing research by utilizing the newest version of the mobile LiDAR hardware and software previously studied, as well as evaluating additional objects of varying sizes and a newly released software not yet studied. ...This paper builds upon existing research by utilizing the newest version of the mobile LiDAR hardware and software previously studied, as well as evaluating additional objects of varying sizes and a newly released software not yet studied.

Electronic Warfare Next Generation FPGAs for Electronic Warfare Systems Materials: Composites Managing the Impact of Nanomaterials in Aerospace Manufacturing Aerospace Materials/Manufacturing Turbine Flow Meters Alternative Power Sources Designing a Power Generation System for a More-Electric Aircraft

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What system Designers Should Know About MOSA Standards Microtube Technology A Catalyst for Next-Gen Aerospace Thermal Control Space Industry Test Challenges Advancing Metrology at Mach Speed Drone Mounted Inspection Breaks Barriers for F-35 RF Technology Helps Connect Avionics Systems Using Open-Cavity Plastic Packages in Avionics Applications Electronic Prognostics - A Case Study Using Global Positioning System (GPS) Prognostic health management (PHM) of electronic systems presents challenges traditionally viewed as either insurmountable or not worth the cost of pursuit, but recent changes in weapons platform acquisition and support requirements has spurred renewed interest in electronics PHM, revealing possible applications, accessible data sources, and previously unexplored predictive techniques.

Using an Open Architecture Approach to Military Avionics Can Embedded Electronics Components Meet the Demands of Hypersonic Missiles? CMOSS/CMFF Trades Interoperability for Free-Thinking Innovation Exploring High-Performance Applications for Distributed Transport Property Thermoelectrics Heterogeneous Integration and SiPs Benefit SWaP-C Reduction The Future of Automated Guided Vehicles for Aerospace and Defense Next-generation AGVs are already starting to deliver labor and cost savings for the U.S. defense industry, and the commercial aerospace sector is watching closely Deep Reinforcement Learning Achieves Multifunctional Morphing Airfoil Control Smooth camber morphing aircraft offer increased control authority and improved aerodynamic efficiency. Smart material actuators have become a popular driving force for shape changes, capable of adhering to weight and size constraints and allowing for simplicity in mechanical design.

Certified Machine Learning-Based Avionics: Unlocking Safer Revolutionizing Electronic Warfare: Unleashing the Power of High-Performance Software Defined Radios Deterministic and Modular Architecture for Embedded Vehicle Systems Approximating the Material Stresses and System Requirements for Hypersonic Flight Design Approaches for Established and Emerging RF Receiver Architectures Rydberg Technologies Shows Potential of Long-Range RF with Quantum Sensor at NetModX23 New Method to Measure Wind Speed Could Unlock Drones' Potential A fundamentally different approach to wind estimation using unmanned aircraft than the vast majority of existing methods. This method uses no on-board flow sensor and does not attempt to estimate thrust or drag forces. Report on Human Factors Issues Likely to Affect Air-Launched Effects This report reviews human factors research on the supervision of multiple unmanned vehicles (UVs) as it affects human integration with Air-Launched Effects (ALE).