Public presentation for nvidia gtc 2019. You can also refer to the public recorded video at: https://on-demand.gputechconf.com/gtc/2019/video/_/S91049/
The Future of the Drone Industry and the Role of Market Research: CeBIT, Hann...Kay Wackwitz
This presentation shows the importance of market research in a new and extremely fast growing market.
Creating fix-points towards stakeholders and market drivers will ensure long term success in an environment where the big consolidation is about to begin.
Connected Car Security Issues:
4 main components-
1- ECU (Electronic Control Unit)
2- CAN Bus (Control Area Network Bus)
3- OBD (Onboard Diagnostics)
4- Infotainment
AI model efficiency is crucial for making AI ubiquitous, leading to smarter devices and enhanced lives. Besides the performance benefit, quantized neural networks also increase power efficiency for two reasons: reduced memory access costs and increased compute efficiency.
The quantization work done by the Qualcomm AI Research team is crucial in implementing machine learning algorithms on low-power edge devices. In network quantization, we focus on both pushing the state-of-the-art (SOTA) in compression and making quantized inference as easy to access as possible. For example, our SOTA work on oscillations in quantization-aware training that push the boundaries of what is possible with INT4 quantization. Furthermore, for ease of deployment, the integer formats such as INT16 and INT8 give comparable performance to floating point, i.e., FP16 and FP8, but have significantly better performance-per-watt performance. Researchers and developers can make use of this quantization research to successfully optimize and deploy their models across devices with open-sourced tools like AI Model Efficiency Toolkit (AIMET).
Presenters: Tijmen Blankevoort and Chirag Patel
This session walks you through how our interns took some video from a drone and turned it into an Android App to count cars in a parking lot. This is a practical introduction to drone SDKs, Tensorflow and how to combine the two to do object detection on your Android phone from a drone.
For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2020/12/driver-monitoring-systems-present-and-future-a-presentation-from-xperi/
For more information about edge AI and computer vision, please visit:
https://www.edge-ai-vision.com
Petronel Bigioi, CTO for Imaging at XPERI, presents the “Driver Monitoring Systems: Present and Future” tutorial at the September 2020 Embedded Vision Summit.
Monitoring drivers and passengers inside of vehicles is an increasingly critical capability. For example, driver monitoring is required in order for cars to obtain a top safety rating from NCAP. This presentation introduces XPERI’s driver and in-cabin monitoring solutions and examines real-world use-cases in which these solutions are being deployed.
Bigioi illustrates the evolution of these technologies as they have been used in conventional cars, as they are increasingly being used in cars with partial self-driving capability, and how they are likely to be used in fully automated vehicles. This goes well beyond driver monitoring to include new types of safety features as well as non-safety uses such as entertainment, personalization, human-machine interfaces and even monitoring occupant health.
Falcon Shield: Countering the drone threatLeonardo
Leonardo Sales & Marketing Manager, Andy Roberts, presented this at DSEI 2019, highlighting the threats posed by accidental, malicious and targeted Class 1 drone activity in both the civil and defence sectors.
We pioneered accelerated computing to tackle challenges no one else can solve. Now, the AI moment has arrived. Discover how our work in AI and the metaverse is profoundly impacting society and transforming the world’s largest industries.
The Future of the Drone Industry and the Role of Market Research: CeBIT, Hann...Kay Wackwitz
This presentation shows the importance of market research in a new and extremely fast growing market.
Creating fix-points towards stakeholders and market drivers will ensure long term success in an environment where the big consolidation is about to begin.
Connected Car Security Issues:
4 main components-
1- ECU (Electronic Control Unit)
2- CAN Bus (Control Area Network Bus)
3- OBD (Onboard Diagnostics)
4- Infotainment
AI model efficiency is crucial for making AI ubiquitous, leading to smarter devices and enhanced lives. Besides the performance benefit, quantized neural networks also increase power efficiency for two reasons: reduced memory access costs and increased compute efficiency.
The quantization work done by the Qualcomm AI Research team is crucial in implementing machine learning algorithms on low-power edge devices. In network quantization, we focus on both pushing the state-of-the-art (SOTA) in compression and making quantized inference as easy to access as possible. For example, our SOTA work on oscillations in quantization-aware training that push the boundaries of what is possible with INT4 quantization. Furthermore, for ease of deployment, the integer formats such as INT16 and INT8 give comparable performance to floating point, i.e., FP16 and FP8, but have significantly better performance-per-watt performance. Researchers and developers can make use of this quantization research to successfully optimize and deploy their models across devices with open-sourced tools like AI Model Efficiency Toolkit (AIMET).
Presenters: Tijmen Blankevoort and Chirag Patel
This session walks you through how our interns took some video from a drone and turned it into an Android App to count cars in a parking lot. This is a practical introduction to drone SDKs, Tensorflow and how to combine the two to do object detection on your Android phone from a drone.
For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2020/12/driver-monitoring-systems-present-and-future-a-presentation-from-xperi/
For more information about edge AI and computer vision, please visit:
https://www.edge-ai-vision.com
Petronel Bigioi, CTO for Imaging at XPERI, presents the “Driver Monitoring Systems: Present and Future” tutorial at the September 2020 Embedded Vision Summit.
Monitoring drivers and passengers inside of vehicles is an increasingly critical capability. For example, driver monitoring is required in order for cars to obtain a top safety rating from NCAP. This presentation introduces XPERI’s driver and in-cabin monitoring solutions and examines real-world use-cases in which these solutions are being deployed.
Bigioi illustrates the evolution of these technologies as they have been used in conventional cars, as they are increasingly being used in cars with partial self-driving capability, and how they are likely to be used in fully automated vehicles. This goes well beyond driver monitoring to include new types of safety features as well as non-safety uses such as entertainment, personalization, human-machine interfaces and even monitoring occupant health.
Falcon Shield: Countering the drone threatLeonardo
Leonardo Sales & Marketing Manager, Andy Roberts, presented this at DSEI 2019, highlighting the threats posed by accidental, malicious and targeted Class 1 drone activity in both the civil and defence sectors.
We pioneered accelerated computing to tackle challenges no one else can solve. Now, the AI moment has arrived. Discover how our work in AI and the metaverse is profoundly impacting society and transforming the world’s largest industries.
Virtual simulations can handle more and more areas in vehicle development with better quality resulting in an strongly increasing demand for virtual simulation to complement or replace costly and time consuming physical simulations. The need for high performance computing (HPC) cycles necessary to perform these simulations grows accordingly resulting in requirements in computing power, electricity, cooling and floor space that have to be met. This talk will give an overview about our approaches to handle these demands in terms of architecture, co-location and cloud solutions.
FIA16: Leonardo Aircraft Division: M-346 programme - the dual role conceptLeonardo
During 2016 edition of the Farnborough Airshow, Leonardo Aircraft Division presented the M-346FT (Fighter Trainer), the latest variant of the platform, ideal to train next generation of fighter pilots
The evolution of machine learning and IoT have made it possible for manufacturers to build more effective applications for predictive maintenance than ever before. Despite the huge potential that machine learning offers for predictive maintenance, it's challenging to build solutions that can handle the speed of IoT data streams and the massively large datasets required to train models that can forecast rare events like mechanical failures. Solving these challenges requires knowledge about state-of-the-art dataware, such as MapR, and cluster computing frameworks, such as Spark, which give developers foundational APIs for consuming and transforming data into feature tables useful for machine learning.
LiDARs for Automotive and Industrial Applications 2018 Report by Yole Develop...Yole Developpement
Will automotive change the LiDAR market?
More information on that report at https://www.i-micronews.com/report/product/lidars-for-automotive-and-industrial-applications-2018.html
A presentation by John Kenney of Toyota InfoTechnology Center on Apr 9 2019 to the Silicon Valley Automotive Open Source Group: https://www.meetup.com/Silicon-Valley-Automotive-Open-Source/events/259384384/
Connected & Autonomous vehicles: cybersecurity on a grand scale v1Bill Harpley
A presentation which was given at 'How the Internet of Things is Changing Cyber Security - an event organised by Optimise Hub (Portsmouth University) on January 26th 2017 at Havant.
- This talk describes the issues relating to cybersecurity of Connected Cars and Autonomous Vehicles. It begins with an introduction to technology and standards. It then looks at the key security challenges and asks how prepared we are to deal with the future risks.
- It is a perfect case study in the challenge of achieving cybersecurity on a massive scale.
Verification of IVI Over-The-Air using UML/OCLSeungjoo Kim
Verification of IVI Over-The-Air using UML/OCL @ ICCC 2019 (International Common Criteria Conference), which is a major conference for the community of experts involved in security evaluation
We already trust artificial intelligence to drive our car, but we still configure thresholds and thrift through logs manually. In this talk, Ronny Lehmann, Loom CTO will discuss how he spent months analyzing modern-ops work, until he finally was able to extract the common-basis practices; and how we used this understanding to build a machine that complements ops teams, automating much of the work which is more suitable for machines - leaving for "humans" just the parts which require humans. What we built saves you time spent on parsers, on configuring and tuning rules and alerts, on conducting root-cause analysis and triage - and finally - on figuring out what to do.
Advanced driver assistance systems are designed to increase car safety more generally road safety.
Basically Advanced driver assists(ADS) systems helps the driver in the driving process and enables safe, relaxed driving. It makes sense to get your new car with driver assist features if you find it at a reasonable price as it helps you drive easily and safely in everyday use.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/videantis/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Marco Jacobs, Vice President of Marketing at videantis, presents the "Computer Vision in Cars: Status, Challenges, and Trends" tutorial at the May 2016 Embedded Vision Summit.
Just as horse carriages were replaced by cars in the 1920s, human operators in our cars will be replaced by electronics in the 2020s. The benefits are tremendous: self-driving cars save lives, save time and save cost. For car manufacturers, this will be a gradual change. With each new model year, they’re adopting increasingly sophisticated advanced driver assistance systems (ADAS) that aid the driver, instead of taking full control. These systems use cameras and computer vision techniques to understand the vehicle’s surroundings. Besides detecting pedestrians, vehicles, lanes, signs, and obstacles, these systems must be aware of where these objects are, and where they’re going. In this talk, Jacobs provides an overview of the state of ADAS today and gives a glimpse into the future. He highlights technology trends, challenges, and lessons learned, with a focus on the crucial role that computer vision plays in these systems.
For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2020/03/market-analysis-on-socs-for-imaging-vision-and-deep-learning-in-automotive-and-mobile-markets-a-presentation-from-yole-developpement/
For more information about edge AI and vision, please visit:
http://www.edge-ai-vision.com
John Lorenz, Market and Technology Analyst for Computing and Software at Yole Développement, delivers the presentation “Market Analysis on SoCs for Imaging, Vision and Deep Learning in Automotive and Mobile Markets” at the Edge AI and Vision Alliance’s March 2020 Vision Industry and Technology Forum. Lorenz presents Yole Développement’s latest analysis on the evolution of SoCs for imaging, vision and deep learning.
Smart infrastructure for autonomous vehicles Jeffrey Funk
These slides use concepts from my (Jeff Funk) course entitled analyzing hi-tech opportunities to analyze how autonomous vehicles are becoming economic feasible. They are becoming economically feasible because the cost of lasers, ICs, MEMS, and other electronic components are falling at 25 to 40% per year. If the cost of autonomous vehicles fall 25% a year, the cost of the electronics associated with autonomous vehicles will fall 90% in 10 years. Dedicating roads to autonomous vehicles is necessary to achieve the most benefits from autonomous vehicles. While using autonomous vehicles in combination with conventional vehicles can free drivers for other activities, dedicating roads to autonomous vehicles can dramatically reduce congestion, increase speeds, and thus increase the number of cars per area of the road. They can also reduce accidents, insurance, and the number of traffic police. These slide discuss the use of wireless technologies for the control and coordination of autonomous vehicles. Improvements in bandwidth, speed, and latency (delays) along with improvements in computer processing are occurring and these improvements are making dedicated roads for autonomous vehicles economically feasible.
Virtual simulations can handle more and more areas in vehicle development with better quality resulting in an strongly increasing demand for virtual simulation to complement or replace costly and time consuming physical simulations. The need for high performance computing (HPC) cycles necessary to perform these simulations grows accordingly resulting in requirements in computing power, electricity, cooling and floor space that have to be met. This talk will give an overview about our approaches to handle these demands in terms of architecture, co-location and cloud solutions.
FIA16: Leonardo Aircraft Division: M-346 programme - the dual role conceptLeonardo
During 2016 edition of the Farnborough Airshow, Leonardo Aircraft Division presented the M-346FT (Fighter Trainer), the latest variant of the platform, ideal to train next generation of fighter pilots
The evolution of machine learning and IoT have made it possible for manufacturers to build more effective applications for predictive maintenance than ever before. Despite the huge potential that machine learning offers for predictive maintenance, it's challenging to build solutions that can handle the speed of IoT data streams and the massively large datasets required to train models that can forecast rare events like mechanical failures. Solving these challenges requires knowledge about state-of-the-art dataware, such as MapR, and cluster computing frameworks, such as Spark, which give developers foundational APIs for consuming and transforming data into feature tables useful for machine learning.
LiDARs for Automotive and Industrial Applications 2018 Report by Yole Develop...Yole Developpement
Will automotive change the LiDAR market?
More information on that report at https://www.i-micronews.com/report/product/lidars-for-automotive-and-industrial-applications-2018.html
A presentation by John Kenney of Toyota InfoTechnology Center on Apr 9 2019 to the Silicon Valley Automotive Open Source Group: https://www.meetup.com/Silicon-Valley-Automotive-Open-Source/events/259384384/
Connected & Autonomous vehicles: cybersecurity on a grand scale v1Bill Harpley
A presentation which was given at 'How the Internet of Things is Changing Cyber Security - an event organised by Optimise Hub (Portsmouth University) on January 26th 2017 at Havant.
- This talk describes the issues relating to cybersecurity of Connected Cars and Autonomous Vehicles. It begins with an introduction to technology and standards. It then looks at the key security challenges and asks how prepared we are to deal with the future risks.
- It is a perfect case study in the challenge of achieving cybersecurity on a massive scale.
Verification of IVI Over-The-Air using UML/OCLSeungjoo Kim
Verification of IVI Over-The-Air using UML/OCL @ ICCC 2019 (International Common Criteria Conference), which is a major conference for the community of experts involved in security evaluation
We already trust artificial intelligence to drive our car, but we still configure thresholds and thrift through logs manually. In this talk, Ronny Lehmann, Loom CTO will discuss how he spent months analyzing modern-ops work, until he finally was able to extract the common-basis practices; and how we used this understanding to build a machine that complements ops teams, automating much of the work which is more suitable for machines - leaving for "humans" just the parts which require humans. What we built saves you time spent on parsers, on configuring and tuning rules and alerts, on conducting root-cause analysis and triage - and finally - on figuring out what to do.
Advanced driver assistance systems are designed to increase car safety more generally road safety.
Basically Advanced driver assists(ADS) systems helps the driver in the driving process and enables safe, relaxed driving. It makes sense to get your new car with driver assist features if you find it at a reasonable price as it helps you drive easily and safely in everyday use.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/videantis/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Marco Jacobs, Vice President of Marketing at videantis, presents the "Computer Vision in Cars: Status, Challenges, and Trends" tutorial at the May 2016 Embedded Vision Summit.
Just as horse carriages were replaced by cars in the 1920s, human operators in our cars will be replaced by electronics in the 2020s. The benefits are tremendous: self-driving cars save lives, save time and save cost. For car manufacturers, this will be a gradual change. With each new model year, they’re adopting increasingly sophisticated advanced driver assistance systems (ADAS) that aid the driver, instead of taking full control. These systems use cameras and computer vision techniques to understand the vehicle’s surroundings. Besides detecting pedestrians, vehicles, lanes, signs, and obstacles, these systems must be aware of where these objects are, and where they’re going. In this talk, Jacobs provides an overview of the state of ADAS today and gives a glimpse into the future. He highlights technology trends, challenges, and lessons learned, with a focus on the crucial role that computer vision plays in these systems.
For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2020/03/market-analysis-on-socs-for-imaging-vision-and-deep-learning-in-automotive-and-mobile-markets-a-presentation-from-yole-developpement/
For more information about edge AI and vision, please visit:
http://www.edge-ai-vision.com
John Lorenz, Market and Technology Analyst for Computing and Software at Yole Développement, delivers the presentation “Market Analysis on SoCs for Imaging, Vision and Deep Learning in Automotive and Mobile Markets” at the Edge AI and Vision Alliance’s March 2020 Vision Industry and Technology Forum. Lorenz presents Yole Développement’s latest analysis on the evolution of SoCs for imaging, vision and deep learning.
Smart infrastructure for autonomous vehicles Jeffrey Funk
These slides use concepts from my (Jeff Funk) course entitled analyzing hi-tech opportunities to analyze how autonomous vehicles are becoming economic feasible. They are becoming economically feasible because the cost of lasers, ICs, MEMS, and other electronic components are falling at 25 to 40% per year. If the cost of autonomous vehicles fall 25% a year, the cost of the electronics associated with autonomous vehicles will fall 90% in 10 years. Dedicating roads to autonomous vehicles is necessary to achieve the most benefits from autonomous vehicles. While using autonomous vehicles in combination with conventional vehicles can free drivers for other activities, dedicating roads to autonomous vehicles can dramatically reduce congestion, increase speeds, and thus increase the number of cars per area of the road. They can also reduce accidents, insurance, and the number of traffic police. These slide discuss the use of wireless technologies for the control and coordination of autonomous vehicles. Improvements in bandwidth, speed, and latency (delays) along with improvements in computer processing are occurring and these improvements are making dedicated roads for autonomous vehicles economically feasible.
Fullstop.ai is a level 2 autonomous hardware and software solution by Synergy Robotics and UMA Robotics, with Nvidia Hardware, with Provable ML, using a provable algorithm for a leader follower algorithm based , autonomous navigation system, incorporating Nvidia Jetson SDK, Drive OS, and smart Cities SDK. Similar to Comma.ai
Design of Image Segmentation Algorithm for Autonomous Vehicle Navigationusing...IJEEE
In the past few years Autonomous vehicles have gained importance due to its widespread applications in the field of civilian and military applications. On-board camera on autonomous vehicles captures the images which need to be processed in real time using the image segmentation algorithm. On board processing of video(frames)in real time is a big challenging task as it involves extracting the information and performing the required operations for navigation.This paper proposes an approach for vision based autonomous vehicle navigation in indoor environment using the designed image segmentation algorithm. The vision based navigation is applied to autonomous vehicle and it is implemented using the Raspberry Pi camera module on Raspberry Pi Model-B+ with the designed image segmentation algorithm. The image segmentation algorithm has been built using smoothing,thresholding, morpho- logical operations, and edge detection. The reference images of directions in the path are detected by the vehicle and accordingly it moves in right or left directions or stops at destination. The vehicle finds the path from source to destination using reference directions. It first captures the video,segments the video(frame by frame), finds the edges in the segmented frame and moves accordingly. The Raspberry Pi also transmits the capture video and segmented results using the Wi-Fi to the remote system for monitoring. The autonomous vehicle is also capable of finding obstacle in its path and the detection is done using the ultrasonic sensors.
This paper proposes smart monitoring of automobiles using IoT, which has the same functionality of conventional scanner-automobile diagnostic device. It consists of a Raspberry pi, Arduino Uno board, Web page for the service centre and also various sensors. The sensors attached in the car are connected with the Arduino board and the output is given to the raspberry pi and the Ethernet field uploads these readings to the server. If any variation in the readings, the server will send SMS to the users mobile to inform about the particular condition. And also it is possible to check the current status of the vehicle and there is special facility called emergency request that is requested by the user to inform about the accident or sudden breakdown to the service centre. It also has an obstacle sensor to sense any obstacles within a particular distance. Dust sensor fixed inside the car monitors the dust content, which can cause health problems to passengers. If there occurs any such scenarios, an SMS will be sent to the user. The vehicle will not get started if the seat belt is not worn by the driver. Detection of fire or water can result to automatic unlocking of the seat belts.
Gates are operated manually by gate keepers. Lots of energy is required in order to push or pull the gate.
Nowadays , no. of public as well as private vehicles are increasing rapidly, thereby increasing the no. of problems faced while parking them.
Suppose a vehicle needs to be parked and enters a parking area without any prior knowledge of availability of vacant space for parking.
If no vacancy is available; time ,fuel and money is lost abruptly and in return creates a lot of chaos inside the parking area.
This project is designed so as to automatically open or close the gate when the vehicle arrives and to facilitate the vehicle parking without human intervention.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/industry-analysis/video-interviews-demos/2d-and-3d-sensing-markets-applications-and-technologies-pre
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Guillaume Girardin, Photonics, Sensing and Display Division Director at Yole Développement, delivers the presentation "2D and 3D Sensing: Markets, Applications, and Technologies" at the Embedded Vision Alliance's September 2019 Vision Industry and Technology Forum. Girardin details the optical depth sensor market and application trends.
This presentation is focused on Automotive and 5G, the drivers, the current status and the challenges including network slicing and management and orchestration
Similar to Xpeng Motors' P7's self-driving roadmap and system design (20)
Why Is Your BMW X3 Hood Not Responding To Release CommandsDart Auto
Experiencing difficulty opening your BMW X3's hood? This guide explores potential issues like mechanical obstruction, hood release mechanism failure, electrical problems, and emergency release malfunctions. Troubleshooting tips include basic checks, clearing obstructions, applying pressure, and using the emergency release.
What Exactly Is The Common Rail Direct Injection System & How Does It WorkMotor Cars International
Learn about Common Rail Direct Injection (CRDi) - the revolutionary technology that has made diesel engines more efficient. Explore its workings, advantages like enhanced fuel efficiency and increased power output, along with drawbacks such as complexity and higher initial cost. Compare CRDi with traditional diesel engines and discover why it's the preferred choice for modern engines.
Things to remember while upgrading the brakes of your carjennifermiller8137
Upgrading the brakes of your car? Keep these things in mind before doing so. Additionally, start using an OBD 2 GPS tracker so that you never miss a vehicle maintenance appointment. On top of this, a car GPS tracker will also let you master good driving habits that will let you increase the operational life of your car’s brakes.
5 Warning Signs Your BMW's Intelligent Battery Sensor Needs AttentionBertini's German Motors
IBS monitors and manages your BMW’s battery performance. If it malfunctions, you will have to deal with an array of electrical issues in your vehicle. Recognize warning signs like dimming headlights, frequent battery replacements, and electrical malfunctions to address potential IBS issues promptly.
Symptoms like intermittent starting and key recognition errors signal potential problems with your Mercedes’ EIS. Use diagnostic steps like error code checks and spare key tests. Professional diagnosis and solutions like EIS replacement ensure safe driving. Consult a qualified technician for accurate diagnosis and repair.
"Trans Failsafe Prog" on your BMW X5 indicates potential transmission issues requiring immediate action. This safety feature activates in response to abnormalities like low fluid levels, leaks, faulty sensors, electrical or mechanical failures, and overheating.
Core technology of Hyundai Motor Group's EV platform 'E-GMP'Hyundai Motor Group
What’s the force behind Hyundai Motor Group's EV performance and quality?
Maximized driving performance and quick charging time through high-density battery pack and fast charging technology and applicable to various vehicle types!
Discover more about Hyundai Motor Group’s EV platform ‘E-GMP’!
𝘼𝙣𝙩𝙞𝙦𝙪𝙚 𝙋𝙡𝙖𝙨𝙩𝙞𝙘 𝙏𝙧𝙖𝙙𝙚𝙧𝙨 𝙞𝙨 𝙫𝙚𝙧𝙮 𝙛𝙖𝙢𝙤𝙪𝙨 𝙛𝙤𝙧 𝙢𝙖𝙣𝙪𝙛𝙖𝙘𝙩𝙪𝙧𝙞𝙣𝙜 𝙩𝙝𝙚𝙞𝙧 𝙥𝙧𝙤𝙙𝙪𝙘𝙩𝙨. 𝙒𝙚 𝙝𝙖𝙫𝙚 𝙖𝙡𝙡 𝙩𝙝𝙚 𝙥𝙡𝙖𝙨𝙩𝙞𝙘 𝙜𝙧𝙖𝙣𝙪𝙡𝙚𝙨 𝙪𝙨𝙚𝙙 𝙞𝙣 𝙖𝙪𝙩𝙤𝙢𝙤𝙩𝙞𝙫𝙚 𝙖𝙣𝙙 𝙖𝙪𝙩𝙤 𝙥𝙖𝙧𝙩𝙨 𝙖𝙣𝙙 𝙖𝙡𝙡 𝙩𝙝𝙚 𝙛𝙖𝙢𝙤𝙪𝙨 𝙘𝙤𝙢𝙥𝙖𝙣𝙞𝙚𝙨 𝙗𝙪𝙮 𝙩𝙝𝙚 𝙜𝙧𝙖𝙣𝙪𝙡𝙚𝙨 𝙛𝙧𝙤𝙢 𝙪𝙨.
Over the 10 years, we have gained a strong foothold in the market due to our range's high quality, competitive prices, and time-lined delivery schedules.
What Does the PARKTRONIC Inoperative, See Owner's Manual Message Mean for You...Autohaus Service and Sales
Learn what "PARKTRONIC Inoperative, See Owner's Manual" means for your Mercedes-Benz. This message indicates a malfunction in the parking assistance system, potentially due to sensor issues or electrical faults. Prompt attention is crucial to ensure safety and functionality. Follow steps outlined for diagnosis and repair in the owner's manual.
What Does the Active Steering Malfunction Warning Mean for Your BMWTanner Motors
Discover the reasons why your BMW’s Active Steering malfunction warning might come on. From electrical glitches to mechanical failures and software anomalies, addressing these promptly with professional inspection and maintenance ensures continued safety and performance on the road, maintaining the integrity of your driving experience.
Comprehensive program for Agricultural Finance, the Automotive Sector, and Empowerment . We will define the full scope and provide a detailed two-week plan for identifying strategic partners in each area within Limpopo, including target areas.:
1. Agricultural : Supporting Primary and Secondary Agriculture
• Scope: Provide support solutions to enhance agricultural productivity and sustainability.
• Target Areas: Polokwane, Tzaneen, Thohoyandou, Makhado, and Giyani.
2. Automotive Sector: Partnerships with Mechanics and Panel Beater Shops
• Scope: Develop collaborations with automotive service providers to improve service quality and business operations.
• Target Areas: Polokwane, Lephalale, Mokopane, Phalaborwa, and Bela-Bela.
3. Empowerment : Focusing on Women Empowerment
• Scope: Provide business support support and training to women-owned businesses, promoting economic inclusion.
• Target Areas: Polokwane, Thohoyandou, Musina, Burgersfort, and Louis Trichardt.
We will also prioritize Industrial Economic Zone areas and their priorities.
Sign up on https://profilesmes.online/welcome/
To be eligible:
1. You must have a registered business and operate in Limpopo
2. Generate revenue
3. Sectors : Agriculture ( primary and secondary) and Automative
Women and Youth are encouraged to apply even if you don't fall in those sectors.
In this presentation, we have discussed a very important feature of BMW X5 cars… the Comfort Access. Things that can significantly limit its functionality. And things that you can try to restore the functionality of such a convenient feature of your vehicle.
Why Isn't Your BMW X5's Comfort Access Functioning Properly Find Out Here
Xpeng Motors' P7's self-driving roadmap and system design
1. 0
Developing Autonomous Driving EVs for the
China Market XPENG Motors’ Approach
Junli Gu
VP of Autonomous Driving, XPENG
motors
March 18, 2019
2. 1
Agenda
1. XPENG Motors Introduction and Background
2. Roadmap for XPENG Motors’ Autonomous Driving Solution
3. System Architecture Design Powered by Xavier
3. 2
Who is XPENG?
We develop FUN, CONNECTED and INTELLIGENT EVs tailored for
the young and tech-savvy Chinese Millennials
2
• Aimed at young Internet users in China, with autonomous driving and
intelligent connection as the core differences
• 2014: Founded in Guangzhou, China
• Dec 2018: Mass production and official launch of G3 (electrical SUV)
• Q1 2019: Mass production of E28 (electrical sedan)
4. 3
Strong R&D capabilities and investments
Shanghai
Intelligent Connected
Vehicle
Navigation R&D
Silicon Valley &
San Diego
Machine Learning
Autonomous Driving
R&D
Guangzhou
Vehicle and VCU
R&D
V2X Testing
Trial and Production
Lead-in
Beijing
Artificial Intelligence
R&D
R&D footprint
Our R&D headcount accounts for over 70% of our total number of employees.
5. 4
Your Smart Driving Assistant
Connectivity
Xmart OS
X-pilot
Artificial
Intelligence
7. 6
Agenda
1. XPENG Motors Introduction and Background
2. Roadmap for XPENG Motors’ Autonomous Driving Solution
3. System Architecture Design Powered by Xavier
8. 7
L3 Products: Highly-Autonomous Highway Features
L4 Products: Fully-Autonomous
Urban & Highway Features
- Driverless Robo Taxi
- Driverless Robo Bus
- Human Driver vehicles
L2+ Products: Semi-Autonomous Highway/Urban Features
- Human Driver vehicles
Self-Driving Two Separate Branches…
9. Comfort Driving with safety guarantees
Where are we heading…
• Key differentiation through XPENG’s intelligent EV strategy
• Focus on in-house software solutions running on leading
computer hardware platforms
• Focus on enhancing driver assistance features towards L3
capabilities in 2020
• Focus on feature optimization for Chinese market and
Chinese consumers
8
10. 9
Roadmap for XPENG Motors’ Autonomous Driving Solution XPilot
2018-2019 2020 2021-2022 2024-2025
CarModel
Autonomous
Driving
Achievement
&Goal
• Xpilot 2.0:
Full scenario auto
parking + LCC + ACC
• Xpilot 3.0:
Super Memory Parking
+ Highway Autopilot
• Xpilot 4.0:
AVP + Highway/Urban
Autopilot
• Xpilot x.0:
Full Automation in
limited scenarios
(highway, parking, etc.)
• First generation
solution for
commercialization
with partial self
developed IPs
• Fully self developed
end-to-end SW IP
• Next gen HW
platform with
optimized sensor cost
• First level-4 solution
in consumer vehicle
A Class SUV (G3) B Class Sedan (E28) B Class SUV
11. 10
XPENG G3
By AI,
irregular lots
By memory
Roadmap for XPENG Motors’ Autonomous Driving Solution-XPilot
parking functions
XPENG E28
Alleviate people’s parking anxiety in parallel, vertical, perpendicular, irregular lots…
parking functions
By voice
By Vision
By Ultrasonic
17. 16
Challenge: Perception & Creating a Representative 3D Environmental Model
Compute (MP/s)
Quality raw sensor input with cost
constraints
2
1
Preponderance of training data
(especially corner cases)
3
18. 17
Challenge: Perception & Creating a Representative 3D Environmental Model
Real stream taken from E28 camera sets; ISP developed in house;
19. 18
Challenge: Extending to Day/Night, All Weather, All locations
1) Time (Location of Sun: Day/Night/NotDawn/NotDusk)
2) Select Weather Conditions
3) Availability of GNSS & RTK
4) Place (GeoFenced)
5) Select Speed Range
6) Road/Traffic Conditions
Sensing/Perception challenges (due
to insufficient quality of raw data
and/or compute power)
Mapping challenges
Driving policy
challenges
20. Ultrasonic Sensors
(6 in Front)
Tri-focal Cameras
(2M pixels, FOV 28,
52, 100, 60/15fps)
Surround-view
Camera (1 at Back)
Rear-view Camera
(2M pixels,FOV 52,
30fps)
In-Car Intelligent
Camera
Radars
(5 in Total)
Surround-view Camera
(1 in Front)
Ultrasonic Sensors
(6 at Back)
Surround-view
Camera (2 on Sides)
Cut-In Prevention
Camera
1M pixels, 60fps)Rear-view Camera
(1M pixels, 30fps)
Sensor System for E28 (Mass production in 2020)
19
Note: We use first vehicle G3’s picture as E28’s design is not revealed yet.
21. 20
XPilot Camera Coverage and Functions for E28
360 coverage; Designed to cover traffic scenarios in China
HFOV 100
HFOV 52
23. 22
1828x948@15fps
(for Highway Driving)
457x237@60fps
(for Urban Driving)
Long Range CNN
(Perception at > 200m)
Close Proximity CNN
(Responds x4 faster)
Cameras
Variable fps Network for China Specific Drive Conditions
(Close Vehicle Proximity and Abrupt Cut-ins)
1
24. 23
HighwayUrban Canyon
START POINT /
END POINT
55 Km route (Approx. 2.5hr)
2.5hrs x 3600 x 1Hz = 9,000 samples
GuangzhouRoute8
Absolute
Localization
Reference
Antenna +
GNSS/INS
2 GNSS / INS
20cm absolute-localization-accuracy at 95% (2 σ)
20cm absolute-localization-accuracy for at 95% (2 σ) of Highway route in white
25. 24
Front Radars
Right Front
Corner Radar
Left Front
Corner Radar
Left Rear
Corner Radar
Right Rear
Corner Radar
3 RADAR
Five Radars of High Angular Resolution: 2x improvement
5th Generation of Radar Technology
26. 25
Industry Leading Computing Platform
XPilot Unit (XPU) powered by NVIDIA Xavier
NVIDIA Xavier
Safety MCU
Camera Des
Camera Des
Camera Des
Memory
EMMC
Storage
CAN
Transceiver
Ethernet
Switch
Power
Management
CAN Ethernet
4
28. 27
XPU Software Stack
NVIDIA Xavier SoC Aurix MCU
Hypervisor
NVIDIA
Foundations
QNX OS and BSP/Drivers
NVIDIA System Software NvMeida/CUDA/CuDNN/TensorRT …
NVIDIA Drive Works
XPilot Frameworks
(Project Eagle)
NVIDIA
Tier-1
AUTOSAR
OTA Data
Camera
Service
CAN
Service
(Radar,
IMU/GNSS,
Vehicle IO)
XPilot
Autonomous
Driving
Applications
Perception,
Localization
Prediction, Path
Planning
Control, …
XPU HW NVIDIA/Tier- SW XPU Platform SW XPilot SW
Visualization Launcher
Monitor
Diagnostic
Service
Xpilot
Safety
App
29. 28
Driving hierarchy w/ safety intervention
AEB
Driver: Human Driver: XPilot
Collision
Warnings
5 SAFETY
Independent AEB System
30. 29
Summary
• XPENG Motors develop FUN, CONNECTED and INTELLIGENT EVs tailored for the
young and tech-savvy Chinese millennials
• Roadmap for XPENG Motors’ Autonomous Driving Solution
• System architecture design powered by Xavier