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To be able to transfer highly automated driving functions into a simulation, models of the vehicle’s perception sensors such as lidar, radar and camera are required. In addition to the classic pulsed time-of-flight (ToF) lidars, the growing availability of commercial frequency modulated continuous wave (FMCW) lidars sparks interest in the field of environment perception. ...In addition to the classic pulsed time-of-flight (ToF) lidars, the growing availability of commercial frequency modulated continuous wave (FMCW) lidars sparks interest in the field of environment perception. This is due to advanced capabilities such as directly measuring the target’s relative radial velocity based on the Doppler effect. ...In this work, an FMCW lidar sensor simulation model is introduced, which is divided into the components of signal propagation and signal processing.

This paper describes the analysis and performance testing of a uniquely designed external heat exchanger. The heat exchanger is attached externally to an aircraft and is used to cool a laser system within the fuselage. Estimates showed insufficient cooling capacity with a conventional staggered tube array in the limited space available. Thus, a non-conventional design was developed with larger tube and fin area exposed to the ram air to increase the heat transfer performance. The basic design consists of 28 circular finned aluminum tubes arranged in two parallel banks. Wind tunnel tests were performed to simulate air and liquid flight conditions for the non-conventional parallel bank arrangement and the conventional staggered tube arrangement. Performance comparisons of each of the two designs are presented. Test results are used in a computer model of the heat exchanger to predict the operating performance for the entire flight profile.

There is a requirement for constant exchange of information between the vehicle and its surrounding environment, which is assisted by sensors such as Camera, LiDAR, and RADAR. However, exposure to harsh environmental conditions such as rain, dirt, snow, and bird droppings can hamper the functioning of the sensors and in turn interrupt accurate vehicle maneuvers. ...This work presents a digital methodology to test the LiDAR cleaning system in the advent of mud clearing at different vehicle speeds. The cleaning mechanism consists of a telescopic nozzle placed above the LiDAR translating back and forth. ...The cleaning mechanism consists of a telescopic nozzle placed above the LiDAR translating back and forth. As the dirt or mud is deposited on screen, water jet is sprayed from nozzle.

To overcome the limitations of physical testing, a physics-based simulation workflow was developed by coupling computational fluid dynamics (CFD) with optical simulations of camera and lidar sensors. The computational data of various weather conditions can be rapidly generated by CFD and used to assess the impact of weather conditions on the sensors and perception algorithms. ...The developed CFD-optical workflow was tested using rainy conditions as a test case, the data for which were generated using CFD and exported to optical simulation software to assess how rainy conditions affect the performance of a visible camera, lidar, and an open-source perception algorithm. The results of the analysis indicate that the rainy conditions and intensification of the conditions by other vehicles on the road degrade the performance of camera and lidar sensors. ...The results of the analysis indicate that the rainy conditions and intensification of the conditions by other vehicles on the road degrade the performance of camera and lidar sensors. The ability of the perception algorithm to detect vehicles significantly deteriorated when rainy conditions changed to moderate rain.

In this paper, a 3600 2-D LiDAR is used to capture the spatial information of the surrounding, the scanning results are presented in a local map and global map. ...In this paper, a 3600 2-D LiDAR is used to capture the spatial information of the surrounding, the scanning results are presented in a local map and global map. The LiDAR’s output is further transformed into an Occupancy grid for the comprehension of the Motion planning module to process the path.

This paper uses three-dimensional Light Detection And Ranging (3D LiDAR) to efficiently search parking slots around without passing by them and highlights the accuracy of detecting and tracking. ...During this process, given LiDAR’s blind spots and visual field occlusion, it is necessary to select the most reliable corner as a positioning reference in each step to update the relative position of the ego-vehicle and slot.

Therefore, failure diagnosis is possible regardless of environmental sensors, such as radar, lidar, and camera. This paper's sensor data is the failure of Delphi's Electronically Scanning Radar (ESR) and Ibeo's LUX Lidar installed in an autonomous vehicle. ...This paper's sensor data is the failure of Delphi's Electronically Scanning Radar (ESR) and Ibeo's LUX Lidar installed in an autonomous vehicle. The emergency deceleration control algorithm employs the sliding mode control with adaptive convergence time.

Digital 3-D models of a test track facility may be available from the construction of the grounds, or they can be created with laser measurement techniques, such as LIDAR. Tire-terrain contact patch simulation techniques provide for the use of validated physics models to study 3-D vehicle behavior undergoing simulated tests for handling, ride, braking compliance or other maneuvers.

The considered sensors are radar, lidar, and camera. To get a common understanding and a common language in sensor model research, a new classification method into low-, medium-, and high-fidelity sensor models is introduced.

The parking lot occupancy detection algorithm determine the occupancy of the parking space, using LiDAR sensors mounted at each side of front bumper. Euclidean minimum spanning tree (EMST) method is used to cluster that information.

Our work merges the traffic simulation software Vissim to create realistic traffic, the vehicle dynamic simulation software CarMaker along with soft-sensors such as 3D Lidar and Camera, and the dedicated Nvidia Drive PX2 hardware platform for autonomous vehicles for data processing and decision-making in order to bring together simulation environments into a single simulation platform.

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.

Considering sensors like camera, LiDAR, radar, and V2X used in autonomous vehicles, it is essential to create a simulation environment that can provide these sensor simulations as realistically as possible.

These methods use the vehicle’s current heading and generate a light detection and ranging (LIDAR) view through rectangular box regions. These box regions mimic the actual vision sensor regions, and logic can easily be applied to real vehicle conditions.

dSpace Simphera new AV simulation application

Horiba expands virtual AV vetting with physical body testing

Empowering Soldiers Through ISPDS Dispensable Gels vs Gap Filler Pads An Analysis of Thermal Management Materials Electronic Warfare Vying for Control of the Electromagnetic Spectrum More Bang for the Buck A New Design and Manufacturing Method for Deep Penetrating Bomb Cases A Comprehensive Way to Use Bonding to Improve RF Performance of Low Noise Amplifiers Army and Universities Deploy New Warfighter Communication Technology Radiation Effects on Electronics in Aligned Carbon Nanotube Technology (RadCNT) Characterizing the fundamental mechanisms and charge transport phenomena governing the interactions between ionizing and non-ionizing radiation with carbon-based (nanotube and graphene) field-effect transistors (FETs) devices and integrated circuits (ICs).

With COSMOsim, OTSL is looking to better virtually recreate diverse driving conditions to enable safe and accurate verifications at a point when autonomous driving continues to move toward practical use around the world.