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“…The points detected in vehicle proximity (between 0m-20m) are mainly ground points, conversely points in the regions 20m-30m, 40m-50m, and 70m-80m represent the objects in the scene. It is worth noting that the number of ground points decreases steeply when the distance increases, and also that due to the resolution and accuracy degradation with the distance [2].…”
Section: Resultsmentioning
confidence: 99%
“…This technique also enables relative velocity to be determined through the Doppler shift [24]. A recent in depth review on LiDAR technologies and its working principles can be found in [2].…”
Section: ) Frequency Modulated Continuous Wave (Fmcw)mentioning
confidence: 99%
“…The distance to the object and the properties returned from the raycast are then used in an attenuation equation to calculate a relative returned intensity; values of returned intensity above the detection threshold will add the specific point to the pointcloud. The relative returned intensity is an inverse exponential equation, modified from (2). The number of raindrops encountered along the beam trajectory increasingly reduces the intensity returned and may result in an object not detected and therefore a False Negative (FN) point.…”
Section: A Lidar Modelmentioning
confidence: 99%
“…These systems rely on an array of perception sensors (camera, LiDAR, RADAR, ultrasonic, etc.) to recognize the environment around the vehicle, plan and adapt its actions as it goes from point A to B [2]. The Society of Automotive Engineers (SAE) have defined 6 levels of autonomy which are widely used by many research groups and developers [3].…”
The global Connected and Autonomous Mobility industry is growing at a rapid pace. To ensure the successful adoption of connected automated mobility solutions, their safety, reliability and hence the public acceptance are paramount. It is widely known that in order to demonstrate that L3+ automated systems are safer with respect to human drivers, upwards of several millions of miles need to be driven. The only way to efficiently achieve this amount of tests in a timely manner is by using simulations and high fidelity virtual environments. Two key components of being able to test an automated system in a synthetic environment are validated sensor models and noise models for each sensor technology. In fact, the sensors are the element feeding information into the system in order to enable it to safely plan the trajectory and navigate. In this paper, we propose an innovative real-time LiDAR sensor model based on beam propagation and a probabilistic rain model, taking into account raindrop distribution and size. The model can seamlessly run in real-time, synchronised with the visual rendering, in immersive driving simulators, such as the WMG 3xD simulator. The models are developed using Unreal engine, therefore demonstrating that gaming technology can be merged with the Automated Vehicles (AVs) simulation toolchain for the creation and visualization of high fidelity scenarios and for AV accurate testing. This work can be extended to add more sensors and more noise factors or cyberattacks in real-time simulations.
“…The points detected in vehicle proximity (between 0m-20m) are mainly ground points, conversely points in the regions 20m-30m, 40m-50m, and 70m-80m represent the objects in the scene. It is worth noting that the number of ground points decreases steeply when the distance increases, and also that due to the resolution and accuracy degradation with the distance [2].…”
Section: Resultsmentioning
confidence: 99%
“…This technique also enables relative velocity to be determined through the Doppler shift [24]. A recent in depth review on LiDAR technologies and its working principles can be found in [2].…”
Section: ) Frequency Modulated Continuous Wave (Fmcw)mentioning
confidence: 99%
“…The distance to the object and the properties returned from the raycast are then used in an attenuation equation to calculate a relative returned intensity; values of returned intensity above the detection threshold will add the specific point to the pointcloud. The relative returned intensity is an inverse exponential equation, modified from (2). The number of raindrops encountered along the beam trajectory increasingly reduces the intensity returned and may result in an object not detected and therefore a False Negative (FN) point.…”
Section: A Lidar Modelmentioning
confidence: 99%
“…These systems rely on an array of perception sensors (camera, LiDAR, RADAR, ultrasonic, etc.) to recognize the environment around the vehicle, plan and adapt its actions as it goes from point A to B [2]. The Society of Automotive Engineers (SAE) have defined 6 levels of autonomy which are widely used by many research groups and developers [3].…”
The global Connected and Autonomous Mobility industry is growing at a rapid pace. To ensure the successful adoption of connected automated mobility solutions, their safety, reliability and hence the public acceptance are paramount. It is widely known that in order to demonstrate that L3+ automated systems are safer with respect to human drivers, upwards of several millions of miles need to be driven. The only way to efficiently achieve this amount of tests in a timely manner is by using simulations and high fidelity virtual environments. Two key components of being able to test an automated system in a synthetic environment are validated sensor models and noise models for each sensor technology. In fact, the sensors are the element feeding information into the system in order to enable it to safely plan the trajectory and navigate. In this paper, we propose an innovative real-time LiDAR sensor model based on beam propagation and a probabilistic rain model, taking into account raindrop distribution and size. The model can seamlessly run in real-time, synchronised with the visual rendering, in immersive driving simulators, such as the WMG 3xD simulator. The models are developed using Unreal engine, therefore demonstrating that gaming technology can be merged with the Automated Vehicles (AVs) simulation toolchain for the creation and visualization of high fidelity scenarios and for AV accurate testing. This work can be extended to add more sensors and more noise factors or cyberattacks in real-time simulations.
“…The radiation length of 1.47 mm yields a corresponding 3-dB beamwidth of 0.052° in the far-field region at the wavelength of 1.55 μm. Such narrow beam width is very favorable for automotive LiDAR applications where an angular resolution around 0.1° is required for distinguishing any potential hazards even at a distance of 200 m [30,31].…”
Section: B Radiation Rates and Frequency-scanning Characteristicsmentioning
In this work, a compact sub-wavelength-pitch silicon waveguide array with low crosstalk is proposed and analyzed. The crosstalk is suppressed by periodic silicon nano-blocks symmetrically arranged along the silicon strip waveguides. The silicon nano-blocks are properly designed to work in the resonant region as a high-reflection boundary so that the evanescent fields of the silicon waveguide, which directly contribute to the coupling between waveguides, can be truncated. Meanwhile, the nanoblocks periodically perturb the evanescent fields to form a weakradiating grating, leading to a millimeter-long effective radiation length required for highly directive optical phased arrays. Simulation results show that the crosstalk between the waveguides in the proposed design is at least 10 dB lower than traditional waveguide array with identical sizes within the 1500 ~ 1590 nm bandwidth. Furthermore, the proposed design achieves an effective radiation length up to 1.47 mm, resulting in a theoretical narrow beam width of 0.052°. Combining both the low crosstalk and the long effective radiating length, our design offers a promising platform for high-performance two-dimensional scanning optical phased array with a large field of view and a narrow beam width.
Extended measurement ranges with coherent ranging necessitate an increase in the digitizer sampling rate. Subsampled coherent ranging can reduce the sampling rate, but it has been demonstrated in a short range below around 10 cm. Herein, programmable optical Vernier-sampled coherent ranging over several tens of meters with a reduced sampling rate using a newly developed stepped-frequency-swept laser (stepped-FSL) is proposed. The measurable range of three-dimensional subsampled coherent ranging can be extended by increasing the coherence length of the stepped-FSL. The proposed stepped-FSL sequentially emits a discrete frequency output by applying a programmable voltage signal to an electro-optic modulator. The free spectral range of the stepped-FSL output can be rapidly and akinetically adjusted by changing the number of steps in the programmable voltage signal. The proposed system realizes an extended measurable range (over 20 m) and a high repetition rate (200 kHz). A low sampling rate of 10 MS s −1 is sufficient for operation at a subsampled interference frequency of 1 MHz. This rate is an order of magnitude lower than that of the conventional coherent ranging using an FSL. Experimental results demonstrate that the programmable optical Vernier-sampled coherent ranging can be improved by leveraging novel optical subsampling with a stepped-FSL.
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