A Low-Cost Deep Neural Network-Based Autonomous Car
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User Manual - S.USV Solutions Compatible with Raspberry Pi, up Board and Tinker Board Revision 2.2 | Date 07.06.2018
User Manual - S.USV solutions Compatible with Raspberry Pi, UP Board and Tinker Board Revision 2.2 | Date 07.06.2018 User Manual - S.USV solutions / Revision 2.0 Table of Contents 1 Functions .............................................................................................................................................. 3 2 Technical Specification ........................................................................................................................ 4 2.1 Overview ....................................................................................................................................... 5 2.2 Performance .................................................................................................................................. 6 2.3 Lighting Indicators ......................................................................................................................... 6 3 Installation Guide................................................................................................................................. 7 3.1 Hardware ...................................................................................................................................... 7 3.1.1 Commissioning S.USV ............................................................................................................ 7 3.1.2 Connecting the battery .......................................................................................................... 8 3.1.3 Connecting the external power supply ................................................................................. -
Performance Analysis and Optimization Opportunities for NVIDIA Automotive Gpus
Performance Analysis and Optimization Opportunities for NVIDIA Automotive GPUs Hamid Tabani∗, Fabio Mazzocchetti∗y, Pedro Benedicte∗y, Jaume Abella∗ and Francisco J. Cazorla∗ ∗ Barcelona Supercomputing Center y Universitat Politecnica` de Catalunya Abstract—Advanced Driver Assistance Systems (ADAS) and products such as Renesas R-Car H3 [1], NVIDIA Jetson Autonomous Driving (AD) bring unprecedented performance TX2 [20] and NVIDIA Jetson Xavier [35], [27] have already requirements for automotive systems. Graphic Processing Unit reached the market building upon GPU technology inherited (GPU) based platforms have been deployed with the aim of meeting these requirements, being NVIDIA Jetson TX2 and from the high-performance domain. Automotive GPUs have its high-performance successor, NVIDIA AGX Xavier, relevant inherited designs devised for the high-performance domain representatives. However, to what extent high-performance GPU with the aim of reducing costs in the design, verification and configurations are appropriate for ADAS and AD workloads validation process for chip manufacturers. remains as an open question. Unfortunately, reusability of high-performance hardware This paper analyzes this concern and provides valuable does not consider GPUs efficiency in the automotive domain insights on this question by modeling two recent automotive NVIDIA GPU-based platforms, namely TX2 and AGX Xavier. In and, to the best of our knowledge, the design space for GPUs, particular, our work assesses their microarchitectural parameters where resources are sized with the aim of optimizing specific against relevant benchmarks, identifying GPU setups delivering goals such as performance, has not been yet thoroughly increased performance within a similar cost envelope, or decreas- performed for the automotive domain. ing hardware costs while preserving original performance levels. -
Building a Distribution: Openharmony and Openmandriva
Two different approaches to building a distribution: OpenHarmony and OpenMandriva Bernhard "bero" Rosenkränzer <[email protected]> FOSDEM 2021 -- February 6, 2021 1 MY CONTACT: [email protected], [email protected] Way more important than that, he also feeds LINKEDIN: dogs. https://www.linkedin.com/in/berolinux/ Bernhard "bero" Rosenkränzer I don't usually do "About Me", but since it may be relevant to the topic: Principal Technologist at Open Source Technology Center since November 2020 President of the OpenMandriva Association, Contributor since 2012 - also a contributor to Mandrake back in 1998/1999 2 What is OpenHarmony? ● More than an operating system: Can use multiple different kernels (Linux, Zephyr, ...) ● Key goal: autonomous, cooperative devices -- multiple devices form a distributed virtual bus and can share resources ● Initial target devices: Avenger 96 (32-bit ARMv7 Cortex-A7+-M4), Nitrogen 96 (Cortex-M4) ● Built with OpenEmbedded/Yocto - one command builds the entire OS ● Fully open, developed as an Open Source project instead of an inhouse product from the start. ● For more information, visit Stefan Schmidt's talk in the Embedded devroom, 17.30 and/or talk to us at the Huawei OSTC stand. 3 What is OpenMandriva? ● A more traditional Linux distribution - controlled by the community, continuing where Mandriva left off after the company behind it went out of business in 2012. Its roots go back to the first Mandrake Linux release in 1998. ● Originally targeting only x86 PCs - Support for additional architectures (aarch64, armv7hnl, RISC-V) added later ● Repositiories contain 17618 packages, built and updated individually, assembled into an installable product with omdv-build-iso or os-image-builder. -
NVIDIA Launches Tegra X1 Mobile Super Chip
NVIDIA Launches Tegra X1 Mobile Super Chip Maxwell GPU Architecture Delivers First Teraflops Mobile Processor, Powering Deep Learning and Computer Vision Applications NVIDIA today unveiled Tegra® X1, its next-generation mobile super chip with over one teraflops of processing power – delivering capabilities that open the door to unprecedented graphics and sophisticated deep learning and computer vision applications. Tegra X1 is built on the same NVIDIA Maxwell™ GPU architecture rolled out only months ago for the world's top-performing gaming graphics card, the GeForce® GTX 980. The 256-core Tegra X1 provides twice the performance of its predecessor, the Tegra K1, which is based on the previous-generation Kepler™ architecture and debuted at last year's Consumer Electronics Show. Tegra processors are built for embedded products, mobile devices, autonomous machines and automotive applications. Tegra X1 will begin appearing in the first half of the year. It will be featured in the newly announced NVIDIA DRIVE™ car computers. DRIVE PX is an auto-pilot computing platform that can process video from up to 12 onboard cameras to run capabilities providing Surround-Vision, for a seamless 360-degree view around the car, and Auto-Valet, for true self-parking. DRIVE CX is a complete cockpit platform designed to power the advanced graphics required across the increasing number of screens used for digital clusters, infotainment, head-up displays, virtual mirrors and rear-seat entertainment. "We see a future of autonomous cars, robots and drones that see and learn, with seeming intelligence that is hard to imagine," said Jen-Hsun Huang, CEO and co-founder, NVIDIA. -
Automotive Foundational Software Solutions for the Modern Vehicle Overview
www.qnx.com AUTOMOTIVE FOUNDATIONAL SOFTWARE SOLUTIONS FOR THE MODERN VEHICLE OVERVIEW Dear colleagues in the automotive industry, We are in the midst of a pivotal moment in the evolution of the car. Connected and autonomous cars will have a place in history alongside the birth of industrialized production of automobiles, hybrid and electric vehicles, and the globalization of the market. The industry has stretched the boundaries of technology to create ideas and innovations previously only imaginable in sci-fi movies. However, building such cars is not without its challenges. AUTOMOTIVE SOFTWARE IS COMPLEX A modern vehicle has over 100 million lines of code and autonomous vehicles will contain the most complex software ever deployed by automakers. In addition to the size of software, the software supply chain made up of multiple tiers of software suppliers is unlikely to have common established coding and security standards. This adds a layer of uncertainty in the development of a vehicle. With increased reliance on software to control critical driving functions, software needs to adhere to two primary tenets, Safety and Security. SAFETY Modern vehicles require safety certification to ISO 26262 for systems such as ADAS and digital instrument clusters. Some of these critical systems require software that is pre-certified up to ISO 26262 ASIL D, the highest safety integrity level. SECURITY BlackBerry believes that there can be no safety without security. Hackers accessing a car through a non-critical ECU system can tamper or take over a safety-critical system, such as the steering, brakes or engine systems. As the software in a car grows so does the attack surface, which makes it more vulnerable to cyberattacks. -
Co-Optimizing Performance and Memory Footprint Via Integrated CPU/GPU Memory Management, an Implementation on Autonomous Driving Platform
Co-Optimizing Performance and Memory Footprint Via Integrated CPU/GPU Memory Management, an Implementation on Autonomous Driving Platform Soroush Bateni*, Zhendong Wang*, Yuankun Zhu, Yang Hu, and Cong Liu The University of Texas at Dallas Abstract—Cutting-edge embedded system applications, such as launches the OpenVINO toolkit for the edge-based deep self-driving cars and unmanned drone software, are reliant on learning inference on its integrated HD GPUs [4]. integrated CPU/GPU platforms for their DNNs-driven workload, Despite the advantages in SWaP features presented by the such as perception and other highly parallel components. In this work, we set out to explore the hidden performance im- integrated CPU/GPU architecture, our community still lacks plication of GPU memory management methods of integrated an in-depth understanding of the architectural and system CPU/GPU architecture. Through a series of experiments on behaviors of integrated GPU when emerging autonomous and micro-benchmarks and real-world workloads, we find that the edge intelligence workloads are executed, particularly in multi- performance under different memory management methods may tasking fashion. Specifically, in this paper we set out to explore vary according to application characteristics. Based on this observation, we develop a performance model that can predict the performance implications exposed by various GPU memory system overhead for each memory management method based management (MM) methods of the integrated CPU/GPU on application characteristics. Guided by the performance model, architecture. The reason we focus on the performance impacts we further propose a runtime scheduler. By conducting per-task of GPU MM methods are two-fold. -
Product Catalogue 2017
PRODUCT CATALOGUE 2017 EXCELLENCE IN AUTOMOTIVE ENGINEERING CONTENTS INTRODUCTION 4 VEHICLE TRACKING 5 VEHICLE SECURITY 8 MOTORBIKE SECURITY 12 PARKING SENSORS 14 REAR SEAT ENTERTAINMENT 16 SPEED LIMITER AND CRUISE CONTROL 18 LED LIGHTING 20 VEHICLE CAMERA SYSTEMS 23 BLUETOOTH 24 NOTES 25 VESTATEC PRODUCT CATALOGUE 2017 3 DISTRIBUTED LINES AND SEAMLESS SOLUTIONS TAILORED DIRECTLY TO YOUR NEEDS Established in 1987, Vestatec celebrates its 30th anniversary this year. Today we are Tier 1 suppliers, supplying to the vehicle production line, to seven vehicle manufacturers and we are approved accessory suppliers to 14 brand in the UK. This experience allows us to provide tailored original equipment products to the specialist aftermarket. Our range of services include dedicated installation manuals, installer training, technical helpline and in-house field support team, enabling us to match the vehicle's manufacturer warranty. Whatever you need, we have the expertise and experience to deliver, every time. 4 VESTATEC PRODUCT CATALOGUE 2017 VEHICLE TRACKING From Europe’s number 1 telematics manufacturer, MetaSystem SPA (over 2 million units a year) Meta Trak is a state of the art connected car platform. The perfect combination of mobile App and in-vehicle hardware, delivering live vehicle tracking, driver scoring and multi vehicle access as well as old school stolen vehicle tracking. Meta Trak works seamlessly with any vehicle or machine, delivering peace of mind with always-on-tracking and fast theft alerts. 4 VESTATEC PRODUCT CATALOGUE 2017 VESTATEC PRODUCT CATALOGUE 2017 5 META TRAK VTS A Thatcham Category VTS Insurance Accredited GPS Tracking System. Mobile/Tablet App for IOS and Android, Web Platform with Locate on Demand, Driver Recognition Tags, Driver Card Not Present Alerts, 12 and 24 Volt Compatible, Waterproof, Transferable from Vehicle to Vehicle, Battery Disconnect Alerts, Tow-Away Alerts, Battery Low Alerts via Push Notification/ Email, Monitored by SOC. -
Developing & Deploying Autonomous Driving
DEVELOPING & DEPLOYING AUTONOMOUS DRIVING APPLICATIONS WITH THE NVIDIA DRIVE PX PLATFORM Shri Sundaram, Product Manager, DRIVE PX Platform DRIVE PX: AV Development Platform AV Developers: DRIVE PX as your tool AV HW/SW Ecosystem: DRIVE PX as your platform to reach developers 2 NVIDIA DRIVE PX Open AV Computing Platform for the Transportation Industry Powerful and scalable AV computer Deep Neural Network, Sensor Fusion and Computing Extensive I/O to interface with wide range of sensors and vehicle networks An open SW stack Level 3 to Level 5; ASIL-D functional safety 3 DRIVE PX DRIVING AV AI DRIVE Platform Engagements 400 350 300 250 Launched CES 2015 200 150 Spike in AV AI engagements after 100 50 we powered on discrete GPU 0 FY18 Q1 FY18 Q3 More than doubled in last 6 months Plus >145 AV Startups on NVIDIA DRIVE Source: NVIDIA statistics 4 AV DEVELOPMENT Path from Idea to Production IDEA DEVELOPMENT PROTOTYPE PRODUCTION Develop Test Deploy Perception Feature development Safety hardening OBJECTIVE Mapping/Localization Validation Performance tuning Path Planning SW upgrades Combination/More… PC PC DRIVE Platform TOOL Automotive Sensors Production SW OTA framework Scalable compute with discrete GPUs Ecosystem of sensors + other HW/SW peripherals TensorRT, CUDA, Open Source Frameworks 5 Autonomous Vehicle DEVELOPMENT FLOW Application Development 4 Using DRIVE PX Platform Test/Drive 3 1 Data Acquired Curated/Annotated Neural Network Deep Neural From Sensors Training Data Training Network Autonomous Vehicle Applications 2 1 Data Acquisition -
D I E B Ü C H S E D E R P a N D O R a Seite 1
D i e B ü c h s e d e r P a n d o r a Infos zur griechischen Mythologie siehe: http://de.wikipedia.org/wiki/B%C3%BCchse_der_Pandora ______________________________________________________________________________________________________________________________________________________ „Das Öffnen der Büchse ist absolute Pflicht, um die Hoffnung in die Welt zu lassen!“ Nachdruck und/oder Vervielfältigungen, dieser Dokumentation ist ausdrücklich gestattet. Quellenangabe: Der Tux mit dem Notebook stammt von der Webseite: http://www.openclipart.org/detail/60343 1. Auflage , © 9-2012 by Dieter Broichhagen | Humboldtstraße 106 | 51145 Köln. e-Mail: [email protected] | Web: http://www.broichhagen.de | http://www.illugen-collasionen.com Satz, Layout, Abbildungen (wenn nichts anderes angegeben ist): Dieter Broichhagen Alle Rechte dieser Beschreibung liegen beim Autor Gesamtherstellung: Dieter Broichhagen Irrtum und Änderungen vorbehalten! Seite 1 - 12 D i e B ü c h s e d e r P a n d o r a Infos zur griechischen Mythologie siehe: http://de.wikipedia.org/wiki/B%C3%BCchse_der_Pandora ______________________________________________________________________________________________________________________________________________________ Hinweis: Weitere Abbildungen von meiner „Büchse der Pandora“ finden Sie unter http://broichhagen.bplaced.net/ilco3/images/Pandora-X1.pdf Bezeichnungen • SheevaPlug ist kein Katzenfutter und kein Ausschlag • DreamPlug ist kein Auslöser für Alpträume • Raspberry Pi ist kein Himbeer-Kuchen • Pandaboard ist kein Servbrett für Pandabären • Die „Büchse der Pandora“ ist keine Legende Was haben SheevaPlug, DreamPlug, Raspberry Pi und Pandaboard gemeinsam? Sie haben einen ARM und sind allesamt Minicomputer. Wer einen ARM hat, ist nicht arm dran. Spaß bei Seite oder vielmehr, jetzt geht der Spaß erst richtig los. Am Anfang war der ... SheevaPlug Das Interesse wurde durch Matthias Fröhlich geweckt, der einen SheevaPlug- Minicomputer vor 2 Jahren im Linux- Workshop vorstellte. -
Diseño De Un Prototipo Electrónico Para El Control Automático De La Luz Alta De Un Vehículo Mediante Detección Inteligente De Otros Automóviles.”
Tecnológico de Costa Rica Escuela Ingeniería Electrónica Proyecto de Graduación “Diseño de un prototipo electrónico para el control automático de la luz alta de un vehículo mediante detección inteligente de otros automóviles.” Informe de Proyecto de Graduación para optar por el título de Ingeniero en Electrónica con el grado académico de Licenciatura Ronald Miranda Arce San Carlos, 2018 2 Declaración de autenticidad Yo, Ronald Miranda Arce, en calidad de estudiante de la carrera de ingeniería Electrónica, declaro que los contenidos de este informe de proyecto de graduación son absolutamente originales, auténticos y de exclusiva responsabilidad legal y académica del autor. Ronald Fernando Miranda Arce Santa Clara, San Carlos, Costa Rica Cédula: 207320032 3 Resumen Se presenta el diseño y prueba de un prototipo electrónico para el control automático de la luz alta de un vehículo mediante la detección inteligente de otros automóviles, de esta forma mejorar la experiencia de manejo y seguridad al conducir en la noche, disminuyendo el riesgo de accidentes por deslumbramiento en las carreteras. Se expone el uso de machine learning (máquina de aprendizaje automático) para el entrenamiento de una red neuronal, que permita el reconocimiento en profundidad de patrones, en este caso identificar el patrón que describe un vehículo cuando se acerca durante la noche. Se entrenó exitosamente una red neuronal capaz de identificar correctamente hasta un 89% de los casos ocurridos en las pruebas realizadas, generando las señales para controlar de forma automática los cambios de luz. 4 Summary The design and testing of an electronic prototype for the automatic control of the vehicle's high light through the intelligent detection of other automobiles is presented. -
Introduction 3 Acknowledgement 3 Problem and Project Statement 3
Introduction 3 Acknowledgement 3 Problem and Project Statement 3 Operational environment 5 Intended uses and users 5 Assumptions and limitations 6 End Product 7 Specifications and analysis 9 Proposed Design 9 Design Analysis 10 Implementation details 10 Testing process and testing results 11 Placing your work in the context of: 21 • Related products 21 • Related literature If/When needed, you should resort to Appendices. 22 Appendix I – Operation Manual 23 Raspberry PI 3 Model B 23 Nvidia Drive PX2 29 Software Licensing 31 Appendix II: Alternative/ other initial versions of the design 32 1) The DSRC 32 2) The Mobile Wireless Data 32 3) The Arduino & XBEE 32 Appendix III: Other Considerations 34 Appendix IV: Code 35 Introduction 35 External Libraries 35 Native Libraries 35 Gather Component Information 35 Finding and Initializing Devices 36 Initialize The GPS 37 Parsing and Transmission 37 Introduction As part of our senior design we had to create the means for the communication between two vehicles. The information that had to be communicated was the latitude, longitude coordinates, and the time. For this we have come up with several solutions throughout our design and testing process. We looked into DSRC, Cellular Communication, Raspberry Pi’s over a LAN network, and Xbee transceivers. All these are viable options and several can complement the others pretty well. We will have more details in following sections. Acknowledgement First off, we would like to formally thank Dr. Hegde for guidance on our project and the insightful advice on how to approach and overcome different obstacles of our progress. Also we would like to thank Vishal as our project manager who made sure we stuck to our milestones and meeting with us every week to make sure we were working towards our goals. -
Procurement of Electric-Electronic
REQUEST FOR QUOTATION (RFQ) Procurement of Electric-Electronic Laboratory Equipment and Supplies for Adana and Mersin Innovation Centers Adana ve Mersin Yenilik Merkezleri için Elektrik-Elektronik Laboratuvarları Ekipman ve Sarf Malzemeleri Alım İhalesi Please enter Name, Address & Contact Details of your Firm DATE: February 10, 2020 Lütfen Firma Adı, Adresi ve İrtibat Bilgilerini buraya giriniz TARİH: 10 Şubat 2020 REFERENCE: UNDP-TUR-RFQ(MC1)-2020/07 Dear Sir / Madam: Sayın İlgili: We kindly request you to submit your Teklife Davet Ek 1’deki Teknik Şartnamede ve Ek quotation for “Procurement of Electric-Electronic 2’de yer alan Malzeme Listesi’nde detayları verilmiş Laboratory Equipment and Supplies for Adana and olan “Adana ve Mersin Yenilik Merkezleri için Mersin Innovation Centers”, as detailed in Technical Elektrik-Elektronik Laboratuvarları Ekipman ve Sarf Specifications and Supplies List provided as Annex Malzemeleri Alım İhalesi” için teklifinizi sunmanızı 1 and Annex 2 (respectively) of this RFQ. When rica ederiz. preparing your quotation, please be guided by the forms attached hereto as ANNEX 1, ANNEX 2 and Teklifinizi lütfen EK 1, EK 2 ve EK 3’de sunulmuş ANNEX 3. formların rehberliğinde hazırlayınız. Quotations shall be submitted on or before 27 Teklifler aşağıda belirtilen adrese, 27 Şubat 2020, February 2020, 14:00 hrs. Turkey Local Time, via Türkiye saati ile 14:00’a kadar elden, e-posta veya hand delivery, e-mail or courier mail to the address kargo yolu ile teslim edilmelidir: below: United Nations Development Programme Birleşmiş Milletler Kalkınma Programı (UNDP) (UNDP) Yıldız Kule, Yukarı Dikmen Mahallesi, Turan Güneş Yıldız Kule, Yukarı Dikmen Mahallesi, Turan Bulvarı, No:106, 06550, Çankaya, Ankara/Türkiye Güneş Bulvarı, No:106, 06550, Çankaya, İlgili Kişi: Ümit ALSAÇ Ankara/Turkey Satın Alma Yetkilisi, UNDP Attn: Mr.