Why the Road to Dependable, High-Quality Cars Lies in a Holistic Design Methodology Highly integrated ADAS systems optimized for performance, power, safety, and reliability
System-focused design strategy optimizes automotive electronics for performance, safety, and reliability
CONTENTS Introduction.....................................................................................4 Cadence System Design Enablement.............................................6 Holistic Design Approach................................................................7 ADAS: A Smarter, Safer Driving Experience..................................9 ADAS Subsystems..........................................................................10 Enabling ADAS Algorithms...........................................................11 CNNs in ADAS Applications..........................................................12 Data Processing.............................................................................13 Optimizing ADAS Design..............................................................14 Design and Verification................................................................15 ISO 26262 and Functional Safety..................................................16 Ensuring Reliability.......................................................................17 Complying with Automotive Interface Standards......................18 Meeting Functional Safety Requirements...................................18 Summary........................................................................................19
Cars now contain more computing power than planes do. Every part of a car is interrelated and must be designed, optimized, and verified simultaneously while the internal systems make split-second decisions about conditions with literally life-or-death outcomes. Developing automotive systems that can handle this level of processing requires taking a holistic approach, taking all parts of the car in consideration, from the chip to the board to the entire vehicle. All components must work together to meet stringent safety and reliability requirements. Focusing on the end product and on optimizing the design at the system level results in dependable, reliable vehicles that take the road of the future. Cadence is here to lead the way.
INTRODUCTION Electronic components are taking a front seat in vehicle design. As the automotive industry continues to develop more autonomous driving features and even self-driving cars, future vehicles will boast more sensor clusters, computer power, vehicle-to-object (V2X) communication technology, high-bandwidth Ethernet networks, and high-definition (HD) displays. Consider the Ford GT: this supercar incorporates 10 million lines of code—about 8 million more than Lockheed’s F-22 Raptor fighter jet and at least 3 million more than the Boeing 787 Dreamliner. With 50 onboard sensors and 28 microprocessors, the Ford GT is designed to assist drivers in handling corners, curves, and different driving conditions.
AUTONOMOUS DRI Intelligent Vehicle • ADAS applications
• Real-time vehicle information and • Adaptive and predictive vehicle
These electronic components aren’t just for revving up the drive. Government regulations are calling for automotive manufacturers to integrate redundant sensing and control systems with more cameras, radar, and other advanced driver-assistance features into vehicles for increased safety and reliability. These vehicles must operate reliably and consistently in a variety of road and environmental conditions; to do this, design and verification tools, IP, new algorithms, and runtime software must be optimized for the entire automotive system. Each new subsystem within the vehicle one must work within the ecosystem of existing subsystems in a complex organization, as well as taking into account hardware and software functionality, component tolerances, temperature variations, stress-induced failure mechanisms (such as electromigration and electrostatic discharge), and expected wear and tear. Simulations, fault analysis, and yield and reliability analyses are critical. The advanced driver assistance system (ADAS) segment—essential for enhancing the driver experience and overall safety—is one of the fastest growing of the automotive semiconductor space.
V2X COMMUNICAT Smart Transportation • V2V–vehicle-to-vehicle • V2C–vehicle-to-cloud • V2I–vehicle-to-infrastructure • V2P–vehicle-to-pedestrian • V2D–vehicle-to-device • V2G–vehicle-to-grid 4
Transformation of Transportation
INFOTAINMENT Connected Passenger • Seamless connectivity • Security • Bring your own device • Personalized connected infotainment • Voice and gesture control
CADENCE SYSTEM DESIGN ENABLEMENT Cadence has built its foundation on a broad EDA portfolio of sophisticated SoC, packaging, and board design tools. Over the years, we have extended our expertise and portfolio into the system design space, delivering IP, hardware/software convergence platforms, software content, and services along with the foundational EDA tools. Taking a holistic design approach from an end-product viewpoint forms the basis of our System Design Enablement strategy. In the automotive realm, Cadence has been amassing a depth of knowledge and experience through years of working closely with customers to meet their challenges of designing and verifying automotive components, subsystems, and the entire system. We work not just with automotive semiconductor suppliers, but also with Tier 1 vendors and OEMs to deepen our understanding of their requirements, obstacles, and opportunities. We strive to ensure that our solutions are relevant for each level of the supply chain. Our technologies and methodologies, including offerings from our ecosystem partners, make Cadence ideally suited to enable automotive designers to succeed with system integration, package, board, and chip design and verification challenges.
HOLISTIC DESIGN APPROACH Clearly, a vehicle’s electronic components are all interrelated. At the same time, the non-electronic parts of the car must be able to interact with the vehicle’s operating environment. To that end, a holistic design approach ensures that the vehicle meets automotive quality and safety standards early in the design cycle. This approach is designing from the top down, accounting for all aspects of the design, using simulation, convolutional neural networks (CNNs), and other tools to test the design before design errors become too costly to fix. This approach leads Cadence to deliver more than just the chip—we also provide layers of the software stack.
Tensilica® Vision DSP, design IP, and verification IP
Supports real-time data processing for sensors and cameras to enable sensor fusion for safety-critical systems. Enables automated parking, lane departure, and communications.
Automotive Ethernet MAC design and verification IP, Palladium® acceleration and emulation environment, Sigrity™ technologies
Enables high-speed communication link between cameras, ADAS systems, and other electronic control units (ECUs) for high-performance in-vehicle networking (IVN) applications, system-level verification, and channel simulation.
Tensilica DSPs, Cadence design IP, and verification IP (VIP)
Enables audio/voice processing, voice recognition, audio high-fidelity playback and sound enhancement, noise vibration harshness, USB, Wi-Fi, Bluetooth, LTE radio, V2X connectivity.
ECU Module Design
Allegro®, OrCAD®, Sigrity, OrbitIO™, and Virtuoso® design tools. Spectre® and Incisive® verification tools
Enables mixed-signal subsystem development and integration, PCB and package design, EMI/EMC analysis and optimization.
Incisive verification, Incisive vManager™ solution, Incisive Functional Safety Simulator
Enables ISO 26262 safety compliance, requirement traceability, automated fault injection, fault simulation, fault tracking, documentation.
Advanced Driver Assistance Systems Surround View Blind Spot
Traffic Sign Recognition
Pedestrian Detection Collision Avoidance
Park Assistance/ Rear
Lane Departure Warning
Surround View Long-Range Radar Lidar Camera Short/Medium Range Radar Ultrasound
Passive Vision (Camera)
Active Vision (Lidar)
• Rear-View Camera
• Adaptive Cruise Control
• Radar, Lidar, and Image Correlation
• Vision Enhancement
• Collision Avoidance
• System Functional Safety
• Auto-Dimming Headlights
• Blind Spot Detection
• System Data Control
• Parking Assist
• Lane Detection and Following
Sound and Ultrasound
• Rear Object Detection
• Front Collision Avoidance Braking
• Parking Assist/Auto Park
• Adaptive Cruise Control
• Voice Recognition
• 360° Hazard Awareness
• Cabin Noise Reduction
• Rear Collision Detection
• Blind Spot Detection • 360° Parking Assist and Lane Detection
• Sign and Traffic Signal Recognition • Rain, Snow, and Fog Removal • Pedestrian Tracking/Avoidance • Eye Focus Detection and Driver Monitoring • Vehicle Detection/Collision Avoidance
• Emergency Recognition
ADAS: A SMARTER, SAFER DRIVING EXPERIENCE ADAS technology enables vehicles to become “aware” of their surroundings. Cars currently in production can include adaptive cruise control, driver monitoring systems, automatic parking, collision avoidance, and lane departure warning systems; future systems will include all of these and more, eventually leading to the full autonomous driving experience. Data is at the heart of these functions—various in-vehicle and V2X sensors collect huge amounts of data in real time, which then must be processed nearly as instantly to make driving decisions with literal life-or-death outcomes. While key technologies for vision, radar, ultrasound, real-time networking, and embedded control can be adapted for other applications, the special requirements of ADAS limit the off-the-shelf chip choices for designers. These unique design specifications include: • High compute performance—At >1000GMAC/sec, ADAS technology must support a DSP architecture tuned to process compute-intensive algorithms, all while delivering an optimal SoC power, performance, and area (PPA) ratio. • High network/memory bandwidth—ADAS technology must support up to 1GB for video/image resolution, rapid frame rates, video streams, and images, with the storage required to access intermediate results generated by highly complex algorithms. Increased integration needs will also drive changes throughout the design chain. OEMs may begin to develop the ECU for SoC architectures. Tier 1 integrators that supply ECUs may establish new ADAS SoC design centers. Consumer businesses and semiconductor companies may establish automotive business units to support this space. Born from the need for greater integration and to meet reliability and thermal requirements, advanced process technologies that are “automotive-ready”—such as 16nm FinFETs, 22nm FD-SOI, and 28nm CMOS—have already emerged.
ADAS SUBSYSTEMS ADAS functions require a mix of sensors and communication, both within and without the vehicle. These subsystems often use specialized IP building blocks to execute key algorithms for sensor processing, including computer vision, voice recognition, radar analysis, and reliable communications. Essentially, ADAS connects a variety of subsystems within a vehicle.
Imaging and Video Assistance Imaging and video assistance include emergency braking, lane and vehicle tracking, traffic sign recognition, parking assistance, driver alertness monitoring, and low-distraction human-machine interfaces (HMIs). These applications must process large volumes of data accurately and in real time, and use this information to make decisions with life-or-death outcomes. They must be fast, reliable, predictable, and without error.
Voice Control and Gesture Recognition Providing the driver with hands-free control of internal functions—from the car radio to environment control to navigation—voice control and gesture recognition can enhance safety and improve the driving experience.
Vehicular Communications Systems V2X communication systems will allow vehicles and roadside units to exchange information, such as traffic and safety-relevant data. In addition, vehicle-to-vehicle (V2V) communication further enhances safety by “looking around the corner.” All of this data can be shared with other cars via the cloud, adding the need for a stable and robust communications network.
Automotive Ethernet Delivering high-speed in-vehicle communication, automotive Ethernet is the key enabler for ADAS applications. This is the data highway that allows, for example, video streams from the side- and rear-view cameras to be processed and transferred to the dashboard display with the high bandwidth and low latency required. In addition, this automotive Ethernet can also be used as the data backbone that directly connects all domain controllers in a car.
ENABLING ADAS ALGORITHMS Our configurable DSPs, along with off-the-shelf software from our partner ecosystem, support new algorithms for communication, audio, imaging, computer vision, and CNN functions that are integral to ADAS. • Cars are being equipped with more cameras, lidar units, and radar sensors, collecting data from the environment around the vehicle. Our portfolio includes high-throughput DSPs that support heavy data communications for applications such as adaptive cruise control, emergency braking, sensor fusion, and V2V communications. • Dedicated DSPs for audio, voice, and speech support always-on wake capabilities for voice triggering and automotive sound systems, including active noise control equipment. • Vision and imaging DSPs process video data from a vehicle’s many cameras, filling visual displays with meaningful information for the driver. The newest offering in this line was designed to provide the MAC performance that’s critical in CNN applications, along with low-power consumption and on-the-fly data compression.
CNNS IN ADAS APPLICATIONS Underlying many of these functions are deep learning technologies, such as Convolutional neural networks (CNNs). CNNs are systems of interconnected “neurons” that exchange related information. One or more convolutional layers, often with a subsampling layer, is followed by one or more fully connected layers. Multiple layers of featuredetecting neurons, each layer itself with neurons, respond to different combinations of inputs from the previous layers. As with neurons in a brain that make a connection between concepts and reinforcement of that connection allows a brain to “know” something very well, CNNs have numeric “weights” of importance that are fine-tuned during a training process. A properly trained network responds correctly when it is presented with an image or pattern that it “recognizes”. So, for example, when the CNN recognizes a stop sign, it “knows” to stop the car. Compared with traditional pattern-detection methods, CNNs are more accurate, require less memory, and are faster to interpret “noisy” data correctly. Tapping into the German Traffic Sign Recognition Benchmark (GTSRB) and using a proprietary hierarchical CNN methodology, Cadence has developed traffic sign recognition algorithms that have yielded a better correct detection rate (99.80%) versus a previously established baseline. Future CNNs will be trained for more complex tasks, such as judgment and strategy.
DATA PROCESSING Processing the data from the ADAS can be distributed or centralized. Each method has different requirements. Regardless of method, every piece of data must be verified to ensure that they will work reliably in the vehicle. Distributed data processing. This takes place in close proximity to each respective sensor or camera, and requires high-speed interface IP and DSPs, with automotive Ethernet IP enabling in-vehicle communication. Sensor fusion DSPs can integrate the output of multiple sensors, thus reducing data traffic to the central head unit. Centralized data processing. This requires an automotive head unit be connected to each of the subsystems (via automotive Ethernet IP, for instance). Interface IP, DSPs, and memory subsystems are essential to ensure a low-latency response of the system.
Image Pre-Processing Video Codec
Vision Subsystem Vision DSP
CPU CNN DSPs
Radar + Ultrasound + Fusion Subsystem Radar DSP
Ultrasound Fusion DSP DSP
Interconnect System Interconnect
On-Chip SRAM DDR4/LPDDR4 Controller
PCle 2.0 RC
USB 2/3 Host
PCle 2.0 PHY
Auto Ethenet SD MAC SDIO eMMC AutoE D-PHY PHY MIPI DSI
32b Peripheral APB LIN
Generic ADAS SoC Integrated Architecture
OPTIMIZING ADAS DESIGN Driven by the need to integrate more functionality on a chip as well as greater data-processing capabilities, automakers are turning to advanced semiconductor processes while tapping into dedicated design IP and packaging technologies. As a result, a new class is emerging of automotive SoCs and systems in packages (SiPs), as well as new challenges that our System Design Enablement strategy and specialized technologies address. Cadence tools support the creation of unique automotive electronic components, subsystems, and systems that meet power and performance targets, safety and reliability standards, and potentially harsh environmental and operating conditions. Our IP can bring the sophisticated, differentiated capabilities that are making vehicles smarter. With our methodologies and services, you can streamline your design cycle to meet your time-to-market goals.
SYSTEM INTEGRATION System analysis | Hardware/software verification | Software applications PACKAGE AND BOARD PCB design | Package design | PCB and package analysis CHIP (Core EDA) Design and implementation | IP/SoC verification | Software drivers
Partnerships with Ecosystem Leaders
Cadenceâ€™s System Design Enablement Strategy
DESIGN AND VERIFICATION Because software is available well before silicon, hardware/software co-verification is essential. The Cadence System Development Suite covers the entire design cycle, from early pre-silicon software development to silicon and system validation. The suiteâ€™s connected platforms accelerate system design, IP and SoC verification, and bring-up, significantly reducing system integration time. Tier 1 suppliers can use these tools to prototype and test a complete system, evaluating a variety of real functions before hardware availability. OEMs can debug specific traffic situations to test and optimize their algorithms. For example, consider a camera system that sits behind the rearview mirror. Inside this system is a CNN that runs on an ADAS SoC for object detection and tracking. Before silicon becomes available, the designer must develop, verify, and optimize the hardware platform running the complex CNN algorithms. The Cadence System Development Suite supports this flow, enabling verification of the SoC to ensure that it is working as intended and to engage in the early development of software drivers and firmware. To test the complete ADAS, a Tier 1 supplier can stream in video sequences of real traffic scenarios. At the OEM level, a software engineer can use the tools to validate, optimize, and debug a specific algorithm or traffic scenario.
ISO 26262 AND FUNCTIONAL SAFETY Errors in the electrical components of a car can lead to minor inconveniences, product recalls, or even loss of life. To be truly safe, a system must contain redundancies, limiting the risk that any single error can upset the entire system; it must also be able to monitor all subsystems and trigger error responses and recovery features. In the automotive world, ISO 26262 is the standard for functional safety of electronic systems in vehicles. The standard outlines the requirements for automotive safety lifecycle phases, functional safety across the development process, and acceptable levels of safety. Compliance with this standard includes: • Detecting and correcting hardware errors • Detecting and resolving systematic faults • Preventing software tasks from affecting each other • Reducing the use of variable-latency system components • Processing speed • Documentation (including guides to safety features), tool qualification support, and verification reports The biggest challenge of compliance is collecting and analyzing the massive amount of data required to achieve the accepted safety integrity level. Until now, this has been a manual, time-consuming process. Now with the Cadence Incisive Functional Safety solution, this task can be significantly accelerated.
ENSURING RELIABILITY Automotive SoCs must demonstrate functional safety, including resilience to failure and fail-safe modes, but they must also provide reliability across their lifetime of operation. For this, Cadence also works very closely with silicon foundries, so aging effects, such as hot carrier injection, bias temperature instability, time-dependent dielectric breakdown, electromigration, and high automotive temperatures, are all accounted for in our Mixed-Signal Solution. You can then design reliability into your automotive SoCs. • Custom IC tools boast a native reliability flow, spanning analog and digital cell characterization with respect to aging, electrically aware interconnect design to combat electromigration, and electrothermal simulation to account for heating and self-heating effects • Digital design solution addresses electromigration issues, performs electrical rules checks, and analyzes substrate noise • Packaging thermal analysis tools provide chip-package-PCB co-simulation and analysis to support faster power signoff • Functional safety simulations model and asses both stress- and environmentally-induced failure mechanisms
COMPLYING WITH AUTOMOTIVE INTERFACE STANDARDS Cadence offers a wide range of system, interface, and memory IP that facilitates ADAS application design, including: • Industry-leading IP for DDR4/LPDDR4 controller and PHY • Automotive Ethernet MAC controller including TSN support (ASIL-B ready) • IP for MIPI® camera/display controller/PHY • IP for PCI Express® (PCIe®) controller and PHY Additionally, our verification IP (VIP) can validate compliance with standard interface specifications, such as CAN, LIN, Ethernet, DDR4, Flash, USB, and dozens more.
MEETING FUNCTIONAL SAFETY REQUIREMENTS Cadence has been developing fault simulation technologies for more than 25 years, and now offers tools that automate the process of meeting automotive functional safety requirements. From staying up-to-date on the latest standards to managing all of the associated data, complying with functional safety requirements has traditionally been a time-consuming, manual effort. Cadence is transforming this process by automating fault injection and result analysis for IP, SoC, and system designs. Built on the Cadence Incisive verification platform, our end-to-end functional safety solution is fully compatible with our Incisive functional verification flow to significantly reduce the automotive ISO 26262 compliance effort. The solution is available as part of the Cadence System Development Suite.
SUMMARY The field of automotive automation is the driver—so to speak—of the next leap of innovation in the field of transportation. Ford Motor Company is set to invest a billion dollars over the next five years in developing a fleet of new driverless cars. Self-driving Volvos are already on the roads in Sweden, and the company is looking for volunteers in London to take part in a self-driving car trial. Uber is now testing a fleet of self-driving cars in Tempe, Arizona and Pittsburgh, Pennsylvania. Maybe the recent increase of development in this field has to do with the ongoing drop in the cost of radar, infrared imagers, sonar, GPS, and other sensors. More likely, it is the dramatic improvement in the processing power of embedded systems. The day when entire cities operate fleets of self-driving vehicles, decreasing the number of accidents, reducing traffic, and even mitigating parking hassles, is quickly coming to fruition. Because lives are at stake, ensuring the safety and reliability of automotive systems is critical. This calls for a holistic design approach that accounts for the system as a whole, including every component inside, ensuring that every individual part functions as intended with the whole. With our System Design Enablement strategy in conjunction with our many years of working with automotive semiconductor designers and integrating with the automotive supply chain, Cadence is well equipped to help deliver automotive-grade devices and systems that support a safer, more enjoyable ride.
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