Ground breaking innovations like Advanced Driver Assistance System (ADAS) makes driving easier and safer on congested roads. The whitepaper details how FPGA technology emerges as a complete solution for ADAS.
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.
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.
Adaptive cruise control (ACC) provides assistance to the driver in the task of longitudinal control of their vehicle during motorway driving within limited acceleration ranges. The system controls the accelerator, engine powertrain and vehicle brakes to maintain a desired time-gap to the vehicle ahead.
Today, a typical automobile on the road has computer controlled electronic systems, and the most commonly used embedded systems in a vehicle include Airbags, anti-lock braking system, black box, adaptive cruise control, drive by wire, satellite radio, telematics, emission control, traction control, automatic parking, in-vehicle entertainment systems, night vision, heads up display, back up collision sensors, navigational systems, tyre pressure monitor, climate control, etc
Autonomous Vehicles: Technologies, Economics, and OpportunitiesJeffrey Funk
These slides use concepts from my (Jeff Funk) course entitled analyzing hi-tech opportunities to show how the cost and performance of autonomous vehicles are improving rapidly. LIDAR, other sensors, ICs, and wireless are experiencing rapid improvements that are enabling the overall cost of AVs to fall. For example, the latency of wireless systems is improving rapidly thus enabling vehicles to be controlled with wireless systems. This is also creating many new opportunities in the vehicle industry in the Internet of Things, data analytics, and logistics. The slides include a detailed discussion of AVs in Singapore, a likely early adopter.
An autonomous car is an autonomous vehicle capable of fulfilling the human transportation capabilities of a traditional car. As an autonomous vehicle, it is capable of sensing its environment and navigating without human input.
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.
CAS is a system designed to help prevent rear‐end collisions with vehicles which are stationary or travelling in the same direction.
It uses visual and audio warnings to prompt the driver to take preventative action.
It also initiates braking if the driver fails to respond to the warnings.
There are generally two kinds of safety systems in automobiles:-
Passive safety – seatbelts, airbag system
Active safety – impact sensors, radar detection
CAS is a system designed to help prevent rear‐end collisions with vehicles which are stationary or travelling in the same direction. Several studies have shown that driver distraction or inattentiveness is a factor in the great majority of rear end accidents. The system is aimed at alerting the driver to an imminent rear end collision both at low speeds, typical of urban driving, and at higher speeds typical of rural roads and highways.
Abstract—Collision warning and collision avoidance systems are emerging automotive safety technologies that assist drivers in avoiding rear-end collisions. Their function is to allow the driver enough time to avoid the crash and yet avoid annoying the driver with alerts perceived as occurring too early or unnecessary. The purpose of this paper is to review various mechanisms under development or developed rear end collision avoidance of automobiles. Some of the reviewed work include an automatic braking system that safely stops an automobile while approaching an obstruction to avoid collision. Another separate but related system is to have a detection device, which alerts the driver in case the automobile veers off the road by crossing either the centre or side painted lines. The braking system senses an obstacle, calculates the relative distance and applies the variable brakes automatically to maintain a safe distance. Warning devices and sensor mechanisms used in obstacle avoidance systems are also reviewed. With the expansion in road network, motorization and urbanization in the country, the number of road accidents have surged. Road traffic injuries (RTIs) and fatalities have emerged as a major public health concern, with RTIs having become one of the leading causes of deaths, disabilities and hospitalizations which impose severe socio-economic costs across the world. Motor vehicle population has grown at a compound annual growth rate (CAGR) of 10 per cent 2000-2009, during fuelled by a rising tide of motorization. Concomitantly, traffic risk and exposure have grown. During the year 2010, there were around 5 lakh road accidents, which resulted in deaths of 134,513 people and injured more than 5 lakh persons in India. These numbers translate into 1 road accident every minute, and 1 road accident death every four minutes. The total number of accidents can be reduced through the safety systems installed in vehicles. However, it was found that many traditional safety measures are reducing their effectiveness.
The Internet of Cars - Towards the Future of the Connected CarJorgen Thelin
No doubt you have heard the phrase “Internet of Things” and the new buzzword “IoT” been used more and more these days, but what does that mean in practice? The Tesla Model S is probably the most well-connected car on the planet at the moment, and in this presentation we will use that vehicle as a case study of some practical usage of IoT concepts and technology that is already being applied to modern automobiles.How far away are we from a future “Internet of Cars” and what will be the social and privacy impacts of more connected-car scenarios?
Adaptive cruise control (ACC) provides assistance to the driver in the task of longitudinal control of their vehicle during motorway driving within limited acceleration ranges. The system controls the accelerator, engine powertrain and vehicle brakes to maintain a desired time-gap to the vehicle ahead.
Today, a typical automobile on the road has computer controlled electronic systems, and the most commonly used embedded systems in a vehicle include Airbags, anti-lock braking system, black box, adaptive cruise control, drive by wire, satellite radio, telematics, emission control, traction control, automatic parking, in-vehicle entertainment systems, night vision, heads up display, back up collision sensors, navigational systems, tyre pressure monitor, climate control, etc
Autonomous Vehicles: Technologies, Economics, and OpportunitiesJeffrey Funk
These slides use concepts from my (Jeff Funk) course entitled analyzing hi-tech opportunities to show how the cost and performance of autonomous vehicles are improving rapidly. LIDAR, other sensors, ICs, and wireless are experiencing rapid improvements that are enabling the overall cost of AVs to fall. For example, the latency of wireless systems is improving rapidly thus enabling vehicles to be controlled with wireless systems. This is also creating many new opportunities in the vehicle industry in the Internet of Things, data analytics, and logistics. The slides include a detailed discussion of AVs in Singapore, a likely early adopter.
An autonomous car is an autonomous vehicle capable of fulfilling the human transportation capabilities of a traditional car. As an autonomous vehicle, it is capable of sensing its environment and navigating without human input.
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.
CAS is a system designed to help prevent rear‐end collisions with vehicles which are stationary or travelling in the same direction.
It uses visual and audio warnings to prompt the driver to take preventative action.
It also initiates braking if the driver fails to respond to the warnings.
There are generally two kinds of safety systems in automobiles:-
Passive safety – seatbelts, airbag system
Active safety – impact sensors, radar detection
CAS is a system designed to help prevent rear‐end collisions with vehicles which are stationary or travelling in the same direction. Several studies have shown that driver distraction or inattentiveness is a factor in the great majority of rear end accidents. The system is aimed at alerting the driver to an imminent rear end collision both at low speeds, typical of urban driving, and at higher speeds typical of rural roads and highways.
Abstract—Collision warning and collision avoidance systems are emerging automotive safety technologies that assist drivers in avoiding rear-end collisions. Their function is to allow the driver enough time to avoid the crash and yet avoid annoying the driver with alerts perceived as occurring too early or unnecessary. The purpose of this paper is to review various mechanisms under development or developed rear end collision avoidance of automobiles. Some of the reviewed work include an automatic braking system that safely stops an automobile while approaching an obstruction to avoid collision. Another separate but related system is to have a detection device, which alerts the driver in case the automobile veers off the road by crossing either the centre or side painted lines. The braking system senses an obstacle, calculates the relative distance and applies the variable brakes automatically to maintain a safe distance. Warning devices and sensor mechanisms used in obstacle avoidance systems are also reviewed. With the expansion in road network, motorization and urbanization in the country, the number of road accidents have surged. Road traffic injuries (RTIs) and fatalities have emerged as a major public health concern, with RTIs having become one of the leading causes of deaths, disabilities and hospitalizations which impose severe socio-economic costs across the world. Motor vehicle population has grown at a compound annual growth rate (CAGR) of 10 per cent 2000-2009, during fuelled by a rising tide of motorization. Concomitantly, traffic risk and exposure have grown. During the year 2010, there were around 5 lakh road accidents, which resulted in deaths of 134,513 people and injured more than 5 lakh persons in India. These numbers translate into 1 road accident every minute, and 1 road accident death every four minutes. The total number of accidents can be reduced through the safety systems installed in vehicles. However, it was found that many traditional safety measures are reducing their effectiveness.
The Internet of Cars - Towards the Future of the Connected CarJorgen Thelin
No doubt you have heard the phrase “Internet of Things” and the new buzzword “IoT” been used more and more these days, but what does that mean in practice? The Tesla Model S is probably the most well-connected car on the planet at the moment, and in this presentation we will use that vehicle as a case study of some practical usage of IoT concepts and technology that is already being applied to modern automobiles.How far away are we from a future “Internet of Cars” and what will be the social and privacy impacts of more connected-car scenarios?
Configuring the communication on FlexRay: the case of the static segmentNicolas Navet
N. Navet, M. Grenier, L. Havet, "Configuring the communication on FlexRay: the case of the static segment", Proc. of the 4th European Congress Embedded Real Time Software (ERTS 2008), Toulouse, France, January 29 - February 1, 2008.
Altera is now shipping our Cyclone® IV FPGAs, the market's lowest cost, lowest power FPGAs, with an integrated 3.125-Gbps transceiver variant. Learn how to meet increasing bandwidth requirements while lowering costs in high-volume applications in this presentation. http://www.altera.com/b/cyclone-iv-fpga-shipping.html
This presentation is the result of my team in the course "Embedded Systems" at the University of Massachusetts, Amherst. It presents the findings of the paper "Timing analysis of the FlexRay communication protocol", a communication network with automotive uses.
20 Inspiring Quotes From William Zinsser's "On Writing Well"Glenn Leibowitz
If you're looking for inspiration and ideas that will help you become a better writer, read these 20 inspiring quotes from William Zinsser's "On Writing Well", the classic guide to writing nonfiction.
Compiled by Glenn Leibowitz, visit http://www.glennleibowitz.com
The Best Startup Investor Pitch Deck & How to Present to Angels & Venture Cap...J. Skyler Fernandes
Take the online video course on Udemy:
https://www.udemy.com/course/the-best-startup-investor-pitch-deck/?referralCode=A5ED0FBD65120A93A16E
3.5+hrs of video content, walking step by step each part of the pitch, with personal VC stories, examples, and advice.
The "Best" Startup Investor Pitch Deck is an aggregation of some of the best pitch decks and wisdom from some of the top angels, VCs, and entrepreneurs including my own person insight/experience. The slide deck includes a template for entrepreneurs to use to present to investors, with details on what should be addressed on each slide. There are also additional slides on how best to pitch to investors effectively, how to design and format slides, and what to do before the pitch.
End to End Machine Learning Open Source Solution Presented in Cisco Developer...Manish Harsh
The RAPIDS suite of open source software libraries and APIs gives you the ability to execute end-to-end data science and analytics pipelines entirely on GPUs. Licensed under Apache 2.0, RAPIDS is incubated by NVIDIA® based on extensive hardware and data science science experience. RAPIDS utilizes NVIDIA CUDA® primitives for low-level compute optimization, and exposes GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces.
Rosella reference design architecture v 0.1Tarik Hammadou
I am pleased to release the first version of the Rosella Reference Design Architecture and Applications document outlining requirements necessary to address the deployment of Rosella edge computing smart infrastructure platform with focus on the Parking Guidance Application (PGA)
Solutions for ADAS and AI data engineering using OpenPOWER/POWER systemsGanesan Narayanasamy
The ultimate goal of ADAS feature development is to make our roads safer and better suited for fully autonomous vehicles in the long run. Still, manufacturers and buyers shouldn’t underestimate the importance of ADAS for meeting current automotive challenges. The most significant impact of advanced driver assistance systems is in providing drivers with essential information and automating difficult and repetitive tasks. This increases safety for everyone on the road
This presentation talks about Software Defined Vehicles, Automotive Standards including Cyber Security and Safety, Agile Methods like SAFe/Less , Continuous Delivery best practices.
The rush to the edge and new applications around AI are causing a shift in design strategies toward the highest performance per watt, rather than the highest performance or lowest power.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2022/06/autonomous-driving-ai-workloads-technology-trends-and-optimization-strategies-a-presentation-from-qualcomm/
Ahmed Sadek, Senior Director of Engineering at Qualcomm, presents the “Autonomous Driving AI Workloads: Technology Trends and Optimization Strategies” tutorial at the May 2022 Embedded Vision Summit.
Enabling safe, comfortable and affordable autonomous driving requires solving some of the most demanding and challenging technological problems. From centimeter-level localization to multimodal sensor perception, sensor fusion, behavior prediction, maneuver planning and trajectory planning and control, each one of these functions introduces its own unique challenges that must be solved, verified, tested and deployed on the road.
In this talk, Sadek reviews recent trends in AI workloads for autonomous driving as well as promising future directions. He covers AI workloads in camera, radar and lidar perception, AI workloads in environmental modeling, behavior prediction and drive policy. To enable optimized network performance at the edge, quantization and neural architecture optimization are typically performed either during training or post-training. Sadek also covers the importance of hardware-aware quantization and network architecture optimization, and introduces the innovation done by Qualcomm in these areas.
The choice of technology within the autonomous vehicle ecosystem drives the business model. The article presents and highlights a few choices and their implications
Automotive Challenges Addressed by Standard and Non-Standard Based IPCAST, Inc.
IP cores from CAST for automotive bus controllers and video applications: CAN FD, LIN, SENT, Ethernet, HDR/WDR, and more. Visit http://www.cast-inc.com for more info.
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The complexity of Medical image reconstruction requires tens to hundreds of billions of computations per second. Until few years ago, special purpose processors designed especially for such applications were used. Such processors require significant design effort and are thus difficult to change as new algorithms in reconstructions evolve and have limited parallelism. Hence the demand for flexibility in medical applications motivated the use of stream processors with massively parallel architecture. Stream processing architectures offers data parallel kind of parallelism.
As data processing requirements increased with new applications, new processing technologies like Stream computing and parallel execution came into being. This write‐up briefly compares two competing performance architectures for data parallelism – Cell Broadband Engine (Cell BE in short) and the GPU (Graphics Processing Unit). The Cell BE Processor architecture was developed in collaboration between IBM, Sony and Toshiba. Development started in 2001 and first set of products based on this architecture started appearing in 2005.
A Set-top-Box (STB) is a very common name heard in the consumer electronics market. It is a device that is attached to a Television for enhancing its functions or the quality of its functions. On the other side, the STB is connected to an external source of signal, like satellite, cable, terrestrial or internet. The STB processes the signal it receives, turns it into content, which is then displayed on the television screen or other display device. There are different types of STBs based on what kind of signals it can receive and what kind of processing it can do. The most widely used STBs are DVB STBs, which receive DVB (Digital Video Broadcast) transmission.
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In today’s competitive software development scenario, the customer demands a testing coverage which not only ensures the stated requirements but also the implied ones. This situation calls for an exhaustive testing which may not be always possible due to various reasons. Testing, due to its last position in SDLC, often gets crunched due to the cumulative schedule slippages. Hence Tester is faced with a challenge to make testing as efficient as possible within a short time span due to cost constraints. With selective testing an only option, test leads usually go for the age-old approach of Random Testing. Random testing does not ensure coverage in a scientific manner.
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In this paper we present a recently developed tool named BrainAssist, which can be used for the study and analysis of brain abnormalities like Focal Cortical Dysplasia (FCD), Heterotopia and Multiple Sclerosis (MS). For the analysis of FCD and Heterotopia we used T1 weighted MR images and for the analysis of Multiple Sclerosis we used Proton Density (PD) images. 52 patients were studied. Out of 52 cases 36 were affected with FCDs, 6 with MS lesions and 10 normal cases. Preoperative MR images were acquired on a 1.5-T scanner (Siemens Medical Systems, Germany).
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Discover more about Hyundai Motor Group’s EV platform ‘E-GMP’!
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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.
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
Advanced Driver Assistance System using FPGA
1. March 2014
White Paper
Advanced Driver Assistance System (ADAS) is the front runner of innovations to make driving experience easier and safer on our more congested roads. According to the research firm, Strategy Analytics, ADAS deployment will grow around 10% within next couple of years. The challenges involved in the design of an ADAS processing platforms are power reduction, transportation of video data over high-speed serial interfaces, parallel/serial process partitioning, meeting platform scalability requirement, meeting external memory bandwidth requirement, architectural flexibility and need for on-chip memory resources. This white paper discusses how the processing power of Field Programmable Gate Arrays (FPGAs) and Programmable SoCs can be used to keep pace with consumer innovations. Nithin M.R, Raisa Basheer and Sreela Mohan
Advanced Driver Assistance System using FPGA
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www.nestsoftware.com
NeST Controlled
Page 2 of 9
Advanced Driver Assistance System Using FPGA
Introduction
Automotive industry can't treat safety as an afterthought. Innovations like the airbag, anti-lock
braking systems (ABS) and electronic stability programs (ESP) have helped to reduce
the number of traffic fatalities and severity of accidents. But increase in the number of
vehicles on the road, more than these technologies are needed to address a further
reduction of accidents and fatalities. In the last few years Advanced Driver Assistance
System (ADAS) features like radar- or camera-based systems have been introduced to make
driving safer. ADAS constantly keep an eye on the road and makes sure to alert the driver in
real-time of an impending danger. The increased use of complex automotive electronics
systems requires that they should be designed for ultra-reliability because the failure of an
automotive system could place the vehicle's passengers in a life-threatening situation.
Rear Camera
Line Keeping System
Diver Alert System
Adaptive
Cruise
Control
Active Park
Pull Drift Compensation Assist
Blind Spot Indicator
System with Cross
Traffic Alert
Figure 1: ADAS features
In this paper we will look how FPGA technology emerges as a complete solution for ADAS.
FPGA provide a faster time to market, lower risk and cost of ownership than ASIC and ASSP
based solutions.
How is the market evolving?
Government legislation and strong consumer interest in safety features is one of the driving
factors contributing to the ADAS market growth. Increased safety awareness and the desire
for more driving comfort on the consumer side targets market to grow at a CAGR of
22.59(1) percent over the period 2012-2016.
Innovations in remote sensors and associated processing algorithms that extract and
interpret critical information also fuel an increase in DA system deployment.
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Figure 2: Market Analysis Data(1)
In recent years, the Global ADAS market has also been witnessing the increasing deployment of ADAS in low-cost cars. So the market is on the threshold of enormous growth. In the race to develop reliable and cost-effective ADAS, designers are presented with challenges to integrate functionality, develop scalable platforms and design systems that are robust enough to work in various operating conditions.
In order to process multiple algorithms simultaneously, develop a scalable architecture, and get to market on time, ADAS system designers are increasingly turning to FPGAs and PSoCs to solve their challenging problems. The architecture of PSoCs or FPGAs is ideally suited for vision processing applications that require both fine grained parallelism and high-level processing. Automakers and suppliers benefit from IP (intellectual property) and other development aids available to help accelerate time-to-market and reprogram products to meet changing requirements and specifications. What are the challenges and opportunities?
ADAS are expensive and this could pose a challenge to the growth of this market(5). Suppliers failed to offer extensions to the mandated technology that the consumer will continue to pay extra for. Suppliers need to offer a scalable platform that allows cost- effective deployment with the time to market and low risk in mind. Intellectual Properties used must be certified to the appropriate automotive safety integrity level. To comply with ISO 26262(3), an ADAS supplier must establish procedures associated with safety standards. The industry lacks interoperability specifications for radar, laser, and video data in the car network. Also lacks standards for embedded vision-processing algorithms. ADAS cannot add to driver distraction.
Power dissipation(3) is a crucial parameter since systems are either located behind the windshield in front of the rear-view mirror with direct exposure to sunlight or in the bumper
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in front of the radiator hence cannot dissipate much heat. Data transactions on external
DDR memory especially can consume a substantial amount of power.
Performance and power requirements can be a challenge when using general-purpose CPU
architectures with often many cores running at high frequency. In addition, the algorithms
used to process video and radar data combined with other data sources makes it difficult
for automotive suppliers to determine fixed high-performance architecture.
In order to handle the increased performance requirement, either the image resolution
needs to be decreased, or the frame rate reduced or multiple devices need to be used.
Therefore ability to add new algorithms to offer more features is also limited by a fixed
computing architecture. Automotive suppliers face significant challenges to develop a base
computing platform that can be quickly modified and scaled to meet the cost and
performance targets in entry level and high-end luxury vehicles around the world.
What are the current trends in ADAS design?
Traditionally for each ADAS functions there is an electronic control unit (ECUs)(6) which is
not scalable and simple microcontrollers (MCUs) do not have the processing power to
process the various sensor inputs from multiple radars, cameras, laser scanners, and ultra
sonic sensors.
Vision Processor ECU
Radar Processor ECU
Laser Processor ECU
Ultrasonic Processor ECU
Decision
Making
MCU
Camera
Radar
Laser
Ultrasonic
Braking
Throttle
Steering
Driver Alert
Figure 3: ADAS using ECUs and MCU
In order to develop a base computing platform that can be quickly modified and scaled to
meet the cost and performance targets, traditionally an ASSP (Application specific standard
product) is selected which has fixed input and output. Using ASSP, if suppliers want to
support a wide range of vehicle models with single hardware architecture, they will have to
design for the full set of ADAS features and scale back the feature offerings on the low end
vehicles. ASSP has a fixed computing architecture. Often, the entire ASSP is consumed
performing one specific algorithm, but in applications requiring multiple algorithms the
processing functions need to be run in parallel.
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In ASSP in order to handle the increased performance requirement, either the image resolution needs to be decreased or the frame rate reduced or multiple devices need to be used. Therefore ability to add new algorithms to offer more features is also limited by ASSP.
FPGAs present an intriguing alternative to ADAS system design compared to fixed-function devices. FPGAs allow designers to customize the functionality and quickly change the I/O structures and hardware and data pipeline to be optimized for a particular algorithm. How FPGA can benefit from these challenges and opportunities? For the development of ADAS Systems, car makers require a common vehicle platform which can be reconfigured according to market needs since it saves the time-to-market and reduces cost of implementation while enhancing flexibility during manufacturing. FPGAs provide a suitable platform for developing the rapidly evolving ADAS Systems in automobiles. Most important requirements of ADAS Includes
Higher levels bandwidth and performance for processing video streams from multiple cameras
Complex, real-time processing required to combine different sensor inputs
Transmit, receive, and translate between multiple communication standards such as CAN, MOST, Ethernet, LVDS.
Meeting ADAS requirements FPGAs provide an ideal platform for developing low-power, low-cost, high-performance, ADAS systems with the most favorable level of integration and flexibility. FPGAs are reprogrammable. If there is any change in the processing architecture, it is possible to reprogram the hardware blocks in FPGA. Using FPGA, any changes can incorporate late in the design cycle. Using reprogrammable nature of FPGA, ADAS can support mutually exclusive functions using same FPGA. FPGAs are well suited to meet the various processing requirements of an ADAS. Two or more distinctly different processes can be run in parallel on a single FPGA. The features like Rear View Camera , Rear cross path etc can be implemented through video processing, manipulation and graphics rendering while the feature effective Pedestrian Detection is performed through image processing analytics .
Another feature of FPGAs is device scalability. To add a new functionality to a serial DSP or an ASSP based system, it requires a complete re-architecture of the software design, even after moving to a more powerful device in the family. But in the case of an FPGA-based
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implementation, a new functional block can be added, utilizing previously unused FPGA logic and keeping the existing blocks as it is.
Figure 4 shows how the camera signal is split between the video- and image processing functions(2). The raw processing power needed to perform these functions can quickly exceed that is available in a serial digital signal processor (DSP). Parallel processing along with hardware acceleration is a viable solution.
Figure 4: Camera based ADAS using FPGA Camera-based ADAS applications require significant external memory access bandwidth especially in multi-camera systems. The data rate needed to store and access the images in external memory is usually high. Camera-based DA applications are memory bandwidth- intensive. These systems also commonly require memory controllers. FPGAs offer flexibility to add memory controllers in a cost effective manner. High end FPGAs offer memory controller blocks (MCBs) that designer can configure for 4, 8 or 16-bit DDR, DDR2, DDR3, or LPDDR memory interfaces. For processing streaming video or analyzing blocks of image data in camera-based DA systems, on-chip memory resources (block RAM, FIFO) that serve as line buffers are available in FPGA. Bayer transform, lens distortion correction, and optical-flow motion-analysis are examples of functions that require video line buffering. Limitation of camera based ADAS System is the operating range of camera sensor is fairly limited compared to the radar- and sonar-based systems. So we can go for sensor fusion techniques. Limitations of camera sensors can be overcome by sensor fusion. Operating range of sensors like radar is more compared to camera sensors. The advantages of different types of sensors can be made useful in the case of sensor fusion.
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Figure 5 shows the block diagram of the implementation of a sensor fusion DA System on PSoC(6). PSoC (Programmable SoC) is a combination of a hard processor system (HPS), and a programmable logic (FPGA logic). The combination of HPS and FPGA logic in PSoC dramatically increases performance for real-time ADAS applications. It also enables greater system integration for bundling multiple applications.
Figure 5: Sensor Fusion ADAS using PSoc In order to process multiple algorithms simultaneously ADAS system designers are increasingly turning to FPGAs and PSoC to solve their challenging problems. Some low level sensor data processing benefits from parallel processing while some other high-level processing functions like system monitoring and control, decision making, warning generation etc are serial decision processes. FPGAs support both types of processing. Benefits of FPGA based DA Systems compared to previous systems
Power: The efficient implementation of data processing algorithm in FPGA reduces the power consumption compared to general-purpose computer architecture even though FPGAs consume considerable power generally.
Performance(2) :
Parallel processing of different functionalities can be easily achieved with FPGAs. It is difficult to run different processes simultaneously with an ASSP based design. But it is possible on a single FPGA.
Functional partitioning of parallel and serial DA processes are possible. Functions that benefit from parallel processing are implemented in FPGA logic, while those more suited for serial processes are implemented in software. In FPGAs serial processes can be implemented either through Soft processors like Micro blaze (Xilinx) or through hard processors like ARM based Cortex –A9 processor.
Reprogrammable nature is a major advantage of FPGA systems over the other systems. Reprogram ability is not possible with other alternatives.
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Device scalability: FPGAs are scalable and flexible to support a wide range of design requirements for ADAS applications. Designers can use a device that is priced and sized appropriately for the specified feature set.
FPGAs meet external bandwidth requirements. FPGA memory controllers provide customized external memory interface design options to meet DA bandwidth needs and optimize all aspects of the cost equation.
Availability of on chip memory resources like block RAMs.
High-speed serial interfaces: Several FPGAs offer differential I/O that can operate at high speeds for the serial transport of data from external interfaces to the processing modules. It is possible to leverage these high-speed I/O capabilities along with the FPGA logic to implement emerging LVDS SerDes signaling protocols within the FPGA device itself, eliminating external components and reducing system cost.
Functional safety: ADAS need to meet specific functional safety requirements. ISO26262 Quality certified FPGA devices, IP, Development tools, and FPGA design flow ensures functional safety of the DA System.
Better time to market(4): IP cores are readily available for various sensor processing applications especially for video and image processing. Because of the readily available quality certified IP Cores and FPGA device scalability, time to market for FPGA based DA systems are less compared to other alternatives.
Less cost of implementation: Cost of implementation for FPGA based DA systems are less compared to others because of features like IP reuse, reprogram ability, device scalability, better integration or bundling of different features etc.
Product obsolescence: While designing DA Systems, designers must consider life span of hardware components used. FPGA life cycles span up to 15 years which is longer than application-specific integrated circuits (ASICs) and ASSPs.
Issues that can impact FPGA selection
Firm-error immunity (7): FPGAs depends on SRAM (static RAM) for configuration memory which makes them prone to neutron-induced errors which can cause thousands of failures in time .Moreover, these errors rise exponentially with fluctuations in temperature and altitude. But, Nonvolatile flash memory solutions do not suffer from neutron-induced errors and are therefore firm-error immune.
Electromagnetic interference (EMI): EMI is a major concern in the case of FPGA selection also. But, in reprogrammable FPGAs, EMI can be quickly eliminated.
Speed: ADAS applications require lightning-fast response times. FPGA response times are usually very low, may be several orders of magnitude faster than even a high-performance microcontroller. These fast response times help to reduce both EMI and power consumption.
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Conclusion Automatic driver assistance system (ADAS) is one of the fastest growing segments in automobile industry. In ADAS, sensors and algorithms are combined to understand the vehicle environment so that the driver can receive assistance or be warned of potential hazards. The processing platform requirements for an efficient ADAS system are architectural flexibility, platform scalability, external memory bandwidth, on-chip memory resources, high-speed serial interfaces, and parallel/serial process partitioning, functional safety. FPGA technology provides a suitable platform for such DA systems and is a viable alternative to standard ASSP and ASIC approaches. References
1. Ian Riches (2012), Automotive Advanced Driver Assistance Systems. http://on-demand.gputechconf.com/gtc/2013/presentations/S3413-Advanced- Driver-Assistance-Systems-ADAS.pdf
2. Paul Zoratti (2011, August 30), Automotive Driver Assistance Systems: Using the processing Power of FPGAs(White Paper). http://www.xilinx.com/support/documentation/white_papers/wp399_Auto_DA_Systems.pdf
3. Altera, A Safety Methodology for ADAS Designs in FPGAs(White Paper). http://www.altera.com/literature/wp/wp-01204-automotive-functional-safety.pdf
4. Altera (2013), Driving Innovative Automotive Solutions(Brochure).
http://www.altera.com/literature/br/br-automotive_broch-1005.pdf
5. Tina Jeffrey (2013, November 7), The challenges of developing advanced driver assistance systems.
http://www.newelectronics.co.uk/electronics-blogs/the-challenges-of-developing- advanced-driver-assistance-systems/57515/
6. Bob Siller (2013, December 3), Complex Trends and Challenges in Designing ADAS Systems.
http://johndayautomotivelectronics.com/complex-trends-and-challenges-in- designing-adas-systems/
7. Martin Mason (2007, December 12), Know the issues: Applying FPGAs in system- critical automotive electronics.
http://www.eetimes.com/document.asp?doc_id=1272854