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High Fidelity Physics Simulation-Based Convolutional Neural Network for Automotive Radar Target Classification Using Micro-Doppler
2021
IEEE Access
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INDEX TERMS Automotive radar, micro-Doppler, machine learning, convolutional neural networks, FMCW, simulation. ...
Radar-based classification of VRUs can be achieved by exploiting differences in the micro-Doppler signatures associated with VRUs. ...
In [47] micro-Doppler spectrograms of a pedestrian, bicycle and car were measured while following defined trajectories using a 7.5 GHz radar. ...
doi:10.1109/access.2021.3085985
fatcat:wohkarumfzaudn6kvxbv3kobpu
Practical classification of different moving targets using automotive radar and deep neural networks
2018
IET radar, sonar & navigation
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A fast implementation of radar algorithms for detection, tracking, and micro-Doppler extraction is proposed in conjunction with the automotive radar transceiver TEF810X and microcontroller unit SR32R274 ...
In this work, the authors present results for classification of different classes of targets (car, single and multiple people, bicycle) using automotive radar data and different neural networks. ...
This also allows to capture the micro-motions contributing most to the MD effect, such as hands, torso and the upper leg parts from walking people; the body of a moving vehicle; and bicycle frame/pedalling ...
doi:10.1049/iet-rsn.2018.0103
fatcat:ouy5zvqe75hmplytroib4y2ppu
Advancing Active Safety Towards The Protection Of Vulnerable Road Users By Evolution Of Adas Solutions That Meet Real-World Deployment Challenges: The Project Prospect
2018
Zenodo
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The objective of PROSPECT is to significantly improve the effectiveness of active VRU safety systems compared to those currently on the market by: (i) expanding the scope of scenarios addressed (ii) improving ...
The findings contribute not only to the augmentation of state-of-the-art knowledge but as well to technical innovations like assessment methodologies and tools for testing. ...
University of Budapest, University of Amsterdam, IFSTTAR, 4activeSystems, TME, Daimler, and Chalmers. ...
doi:10.5281/zenodo.1222118
fatcat:e3ovdqhk4rehpjwuq7rvxot3ky
Traffic participants classification based on 3D radio detection and ranging point clouds
2021
IET radar, sonar & navigation
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First, a 22-dimensional feature vector of the 3D RADAR point cloud distribution was extracted to describe the shape, discrete, Doppler, and reflection intensity features of the targets. ...
Millimetre wave radio detection and ranging (RADAR) is a cost-effective and robust means of performing this task in adverse traffic scenarios such as inclement weather (e.g. fog, snow, and rain) and poor ...
ACKNOWLEDGEMENTS This work was supported by prospective study funding of Nanchang Automotive Innovation Institute, Tongji University (NO. QZKT2020-10). ...
doi:10.1049/rsn2.12182
fatcat:goubjbsqtjbkxeikikmnwnezny
A Bayesian Framework for Integrated Deep Metric Learning and Tracking of Vulnerable Road Users Using Automotive Radars
2021
IEEE Access
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Subsequently, feature embedding corresponding to target's micro-Doppler signature are learned using novel Bayesian based deep metric learning approaches. ...
In this work, we demonstrate the performance of the proposed Bayesian framework using several vulnerable user targets based on a 77 GHz automotive radar. ...
In Section III, we present the traditional automotive radar signal processing involving range, Doppler, angle processing, target detection, target clustering, extraction of micro-Doppler spectra and target ...
doi:10.1109/access.2021.3077690
fatcat:6hbklgq6s5fn5me6utfu7sh4yi
Road Users Classification Based on Bi-Frame Micro-Doppler With 24-GHz FMCW Radar
2022
Frontiers in Signal Processing
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The proposed model is based on obtaining micro-Doppler information; only one receiver is used. Therefore, in addition to the target reflectivity, no geometrical information is used. ...
This study shows an approach for classifying road users using a 24-GHz millimeter-wave radar. ...
Moreover, we design a set of simple features that extract the distinguishing characteristics of each class from the micro-Doppler spectrum of the target. ...
doi:10.3389/frsip.2022.864538
fatcat:t2khtoby2fh6rpdl5sv76tpvmm
Improving safety of Vulnerable Road Users by addressing barriers of current Autonomous Emergency Braking (AEB) systems
2019
Zenodo
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Driving simulator studies were used in a controlled environment for the collection of data regarding the interaction between the driver and the safety function. ...
A benefit estimation methodology was developed and includes an assessment of the combined effect of active and passive safety measures of PROSPECT-like systems. ...
University of Budapest, University of Amsterdam, IFSTTAR, 4activeSystems, TME, Daimler, and Chalmers. ...
doi:10.5281/zenodo.3369614
fatcat:aaby2eo2zfbodco4wjfjbyu34u
Advancing Active Safety And Testing Methodologies Towards The Protection Of Vulnerable Road Users: The Project Prospect
2018
Zenodo
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The objective of PROSPECT is to improve significantly the effectiveness of active VRU safety systems compared to those currently on the market by: (i) expanding the scope of urban scenarios addressed ( ...
User acceptance tests with the participation of drivers are also crucial in PROSPECT for the success of all active safety systems. ...
increased up to 270° covering vehicle front and one side), highresolution and sensitive microwave radar sensors with enhanced micro-Doppler capabilities for a better radar-based VRU classification. ...
doi:10.5281/zenodo.1422458
fatcat:76wb5dufxngsvhuo3dwzjq2qgu
A Review on Driving Control Issues for Smart Electric Vehicles
2021
IEEE Access
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Despite advancements in these areas, the realization of optimal smart EVs still requires considerable effort. ...
Smart electric vehicles (EVs) are attractive because of their clean, zero-emission, low impact on the environment whilst providing a safer and smoother riding experience. ...
In [157] , a radar-based pedestrian detection system is built using the SVM and Micro-Doppler effects. ...
doi:10.1109/access.2021.3116353
fatcat:prd46jrgsncydbtasfkxia6w3e
IMPROVING THE EFFECTIVENESS OF ACTIVE SAFETY SYSTEMS TO SIGNIFICANTLY REDUCE ACCIDENTS WITH VULNERABLE ROAD USERS
2019
Zenodo
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Driving simulator studies were then used in a controlled and repeatable environment for the collection of data regarding the interaction between the driver and the safety function. ...
The objective of PROSPECT was to improve significantly the effectiveness of active VRU safety systems compared to those currently on the market by: (i) expanding the scope of urban scenarios addressed ...
University of Budapest, University of Amsterdam, IFSTTAR, 4activeSystems, TME, Daimler, and Chalmers. ...
doi:10.5281/zenodo.3247142
fatcat:qawxuyx755eyvg7smjsdo3nba4
Towards Self-Powered Sensing Using Nanogenerators for Automotive Systems
2018
Nano Energy
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A few novel types self-powered sensing mechanisms are presented for each of the abovementioned sensor categories using nanogenerators. ...
The last section includes the automotive systems and subsystems, which have the potential to be used for energy harvesting, such as suspension and tires. ...
, pulsed Doppler radar, monopulse radar, laser, far-infrared (FIR), and near-infrared (NIR). ...
doi:10.1016/j.nanoen.2018.09.032
fatcat:cafunos6r5hpjlz3oee4s32euq
A Bayesian framework for integrated deep metric learning and tracking of vulnerable road users using automotive radars
2021
Preserved Fulltext
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Subsequently, feature embedding corresponding to target's micro-Doppler signature are learned using novel Bayesian based deep metric learning approaches. ...
In this work, we demonstrate the performance of the proposed Bayesian framework using several vulnerable user targets based on a 77 GHz automotive radar. ...
In Section III, we present the traditional automotive radar signal processing involving range, Doppler, angle processing, target detection, target clustering, extraction of micro-Doppler spectra and target ...
doi:10.15480/882.3709
fatcat:qbxyiix3nzfmfcxtohup22dbxa
Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies
[article]
2020
arXiv
pre-print
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Almost at the same time, deep learning has made breakthrough by several pioneers, three of them (also called fathers of deep learning), Hinton, Bengio and LeCun, won ACM Turin Award in 2019. ...
This is a survey of autonomous driving technologies with deep learning methods. ...
[280] , which uses an instance layer to learn instances (vehicles, bicycles, and pedestrians)' movements and interactions and has a category layer to learn the similarities of instances belonging to ...
arXiv:2006.06091v3
fatcat:nhdgivmtrzcarp463xzqvnxlwq
Polarimetric Radar for Automotive Applications
2019
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On the basis of successful state-of-the-art applications, this work presents the first in-depth analysis and ground-breaking, novel results of polarimetric millimeter wave radars for automotive applications ...
Current automotive radar sensors prove to be a weather robust and low-cost solution, but are suffering from low resolution and are not capable of classifying detected targets. ...
automotive radars. ...
doi:10.5445/ksp/1000090003
fatcat:t3tliipm5zgqda6pw35oel7cha
Program
2021
2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)
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Then, lossless or lossy watermark extraction is used. ...
Software is also developed to coordinate with the
hardware so the system is ready for commercial automotive radar test and calibration. ...
doi:10.1109/icce-tw52618.2021.9602919
fatcat:aetmvxb7hfah7iuucbamos2wgu
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