What Are Autonomous Systems?Autonomous systems, such as self-driving cars and some robots, operate without human intervention. In this section, you’ll learn what defines autonomous systems and the various levels of autonomy. You will also find examples of autonomous systems in the world today. Show
DefinitionAn autonomous system is one that can achieve a given set of goals in a changing environment—gathering information about the environment and working for an extended period of time without human control or intervention. Driverless cars and autonomous mobile robots (AMRs) used in warehouses are two common examples. Autonomy requires that the system be able to do the following:
An autonomous system can sense, perceive, plan and act without intervention.The vast majority of current systems known as autonomous are semi-autonomous rather than fully autonomous. Cars with driver support systems such as lane keep assist and advanced braking systems are semi-autonomous, as are robotic surgery systems, robot vacuums and most unmanned aerial vehicles (UAVs and drones). Most fully autonomous systems, such as driverless cars, remain too costly, data-intensive, power-consuming or unsafe for widespread public use. Significant progress is being made. Electric vehicles, autonomous vehicle perception systems and connected car platforms have passed Gartner’s "peak of inflated expectations" and through the "trough of disillusionment." These systems have reached the "slope of enlightenment" in the Connected Vehicle and Smart Mobility Hype Cycle. Examples of Autonomous SystemsAutonomous vehicles, autonomous robots, autonomous warehouse and factory systems and autonomous drones are some examples of autonomous systems. Autonomous VehiclesBoth passenger and commercial vehicles include autonomous capabilities, which exist on a continuum, as identified by the six levels of driving automation defined by SAE J3016:
Many passenger vehicles in widespread use meet SAE J3016 Level 0, 1 or 2. To deliver the types of autonomy described in SAE J3016, passenger vehicles have transformed into semi-autonomous, connected mobile devices on wheels. Cars of the future will provide even more autonomous features and eventually become fully autonomous. In many cities, autonomous cars and shuttles, such as an all-electric shuttle without manual controls in San Francisco, are common sights. As for autonomous commercial vehicles, while many fewer trucks are built annually than cars, autonomous trucks will radically change cargo transport and the use of public highways. One autonomous cargo transport technique is known as truck platooning. In truck platooning, a human driver in a tractor-trailer truck leads a convoy of autonomous tractor-trailer trucks, enabling a single driver to move much more cargo. Automated driver support systems allow each autonomous truck to follow the truck in front of it at a set distance. The human driver can drop off the follower trucks and pick up new ones at predetermined locations along a highway. Autonomous vehicles also include those that use rail. Autonomous freight trains will move cargo with a human acting as an observer. Autonomous RobotsAutonomous robots vary from simple robot floor cleaners to complex autonomous helicopters. Otto, the first autonomous snowplow in North America, keeps runways clear at an airport in Manitoba. In agriculture, the idea of fully autonomous tractors has engaged generations of farmers, but currently autonomous tractors require a supervising operator. Other autonomous systems used on farms include automatic milking machines and strawberry-picking robots. In the medical field, robots assist surgeons in performing high-precision procedures, such as coronary artery bypass and cancer removal. High-mobility autonomous systems, such as four-legged walking robots, can navigate obstacles, access difficult-to-reach locations and perform tasks hazardous to humans. Examples include industrial inspection robots and rescue mission robots. Autonomous Warehouse and Factory SystemsFrom mail sorting systems to material conveyors to assembly robots, a diverse array of autonomous systems performs routine and repetitive tasks, enabling better use of human labor. One type of warehouse autonomous system is a robot forklift that moves products around an ecommerce giant’s automated distribution center. On assembly lines, autonomous factory robot arms perform many heavy and precision tasks—such as arc welding, painting, finishing and packaging. Autonomous DronesUnmanned aerial vehicles, known as UAVs or drones, are small self-piloting autonomous aircraft. Drones have long been used for reconnaissance, surveying, asset inspection and environmental studies. Two common uses for drones are agriculture and oil well inspection. Autonomous UAV technology has its basis in the autopilot technology used by passenger airplane captains in commercial aircraft. Fully autonomous (pilotless) passenger aviation remains a distant goal. Similarly, un-crewed UAVs are usually piloted remotely rather than directing their own flight paths. In UAVs, two tasks commonly performed by fully autonomous systems are airborne refueling and ground-based battery switching. Sensors and Sensor FusionSensors and sensor fusion play a vital role in autonomous systems. They enable such systems to gather data from sources in the environment and make use of the data to plan and take action. In this section, you’ll learn about the diverse types of sensors used in autonomous systems and how sensor fusion helps an autonomous system acquire and develop a more accurate assessment of its environment. Sensors Used in Autonomous SystemsSensors help an autonomous system determine its location, identify informational signs, and avoid obstacles and other hazards. The following describes common types of sensors and their purposes and explains how the use of multiple sensors can overcome a weakness of one type of sensor by pairing it with another one with different strengths and weaknesses.
Unlike image sensors and LiDAR, radar sensors are unaffected by weather conditions.Radar sensors are often paired with cameras to achieve image quality that is closer to the high-resolution images provided by LiDAR. How Radar and LiDAR Compare:
Wireless Vehicle CommunicationsIn addition to sensors on an autonomous system, machines in the environment can also provide information to the system. Autonomous vehicles will pass information to nearby systems and vice versa. Vehicle-to-everything (V2X or V2E) communication between a vehicle and its environment improves safety by enabling communication with the following types of systems:
Such communication is achieved with one of two technologies: 5G or dedicated short-range communication (DSRC) using the IEEE Wireless Access in Vehicular Environments (WAVE) 802.11p standard. Current LTE cellular technology does not allow for peer-to-peer communication which is necessary for V2V or V2P. In the future, 5G vehicle-to-everything communication (C-V2X) will make cars smarter and driving safer. Sensor FusionEach type of sensor and source of environmental information has advantages and disadvantages. Sensor fusion produces more detailed and more accurate information about the environment than could be achieved with a single source. As a branch of machine learning and signal processing that focuses on perception, sensor fusion combines data from multiple sensors and databases to produce higher-quality information so that an autonomous system can make better, safer decisions. Sensor fusion is also known as data fusion, filtering or target tracking. How does sensor fusion work? Sensor fusion systems typically take data from cameras, LiDAR, radar, sonar and other sensors and fuse it together, essentially augmenting data from one type of sensor with data from another type of sensor. Highly efficient, high-throughput software and special purpose hardware called accelerators handle the massive quantity of sensor data that needs to be processed for quick decision making by an autonomous system. Sensor fusion combines data from multiple types of sensors to produce a more accurate picture of the environment.To perceive and understand the sensor data, the system must filter disparate data sources, localize data assets, interpret those assets and classify data. Sensor fusion algorithms—such as the Kalman filter, Bayesian networks and convolutional neural networks—help the autonomous system ensure that it is working to extract the maximum possible information from the sensor data.
Software for Autonomous SystemsBuilding safe, secure and reliable autonomous systems begins with the architecture, then the design, and then the software foundation. In this section, you’ll learn about autonomous systems architecture, functional safety systems, the future of autonomous system software, a safe software foundation and the many security considerations for autonomous systems. The growth of autonomous systems will involve a transition from hardware-driven equipment to software-driven electronics, regardless of whether the autonomous system is a snowplow or a surgical system. The software requirements for real-time control, safety, security and reliability are similar across industries. At BlackBerry QNX, we provide the operating system or software foundation for developers facing the myriad challenges of building safe, secure and reliable software for use in a wide variety of autonomous systems. Autonomous System Software ArchitectureThe four software components for autonomous systems are sensing, perceiving and understanding, making decisions and taking action.
Functional Safety SystemsUnsafe autonomous systems are a grave concern of consumers, governments and industry watchers. It may not be fair, but autonomous systems are held to a higher standard of safe behavior than humans. That is, they must prove a better safety record than humans or they will not be accepted by the public. In passenger vehicles, safety features such as lane-departure warnings and collision detection, and active-control features such as automatic braking and lane-keep assist, must always work. In comparison, the public is willing to accept mistakes from human drivers. People are willing to accept that humans make mistakes, but autonomous systems are held to a higher standard.To address this challenge, developers of embedded software for autonomous systems recommend that all software be safety-certified in safety-critical systems like autonomous vehicles. BlackBerry QNX has pre-certified the QNX® Neutrino® RTOS and QNX® Hypervisor to functional safety standards including IEC 61508 (electronic systems) and ISO 26262 (automobiles). BlackBerry QNX also provides expert consulting services to help our customers achieve the safety certifications they need. AbstractionAutonomous systems today are propriety networks of systems from multiple suppliers integrated by a system developer, which makes it difficult for developers to scale software and limits the availability of third-party after-market applications. In the future, developers will interact with autonomous systems via a software platform that abstracts the hardware, abstracts the sensors and pushes the interface to a higher-level set of software services via an application programming interface (API). This will free developers from having to interact with a specific type of LiDAR, radar or camera in use—and enable them to simply request information via high-level services provisioned with APIs. Connectivity will be similarly abstracted, so the communications within the car, with other vehicles and with the cloud will be simpler for a developer to implement without requiring a deep understanding of a specific communication technology. In the future, a developer will call an API to get information from a car, without needing to understand the underlying hardware.Software Foundation for Safe SystemsAt the core of any safety-critical autonomous system is a safe, reliable and secure software foundation or operating system. The following components provide the building blocks for safe autonomous systems.
BlackBerry and AUTOSAR are working closely on open-system architecture standards for autonomous vehicles and to pave the way for innovative electronic systems that further improve performance, safety and security. How BlackBerry QNX Can Help YouBuilding software for autonomous systems is time-intensive, costly and high risk. BlackBerry QNX reduces the burden for developers through a safe, reliable and secure real-time operating system designed specifically for safety-critical systems. We also offer engineering, security and safety certification services and have extensive experience with autonomous system development. In this section, you’ll learn more about our software solutions, professional services and industry leadership. BlackBerry QNX SoftwareFrom surgical robots and cars to trains and traffic lights, BlackBerry® QNX® software provides the foundation for safe, reliable and secure systems:
The QNX Neutrino RTOS is used in hundreds of millions of systems, including driverless vehicles and autonomous robots.BlackBerry QNX Professional ServicesDeveloping safe, reliable and secure software for mission-critical and safety-critical applications of all kinds is a core competency at BlackBerry QNX. We offer training, consulting, custom development, root cause analysis and troubleshooting, system-level optimization and onsite services for developers of a variety of embedded systems in automotive, medical, robotics, industrial automation, defense and aerospace, among other industries. Learn more about our professional services, including safety services and security services. Industry LeadershipThe BlackBerry QNX Autonomous Vehicle Innovation Centre (AVIC) helps developers of software for connected and self-driving vehicles through production-ready software developed independently and in collaboration with partners in the private and public sectors. Additionally, as part of a program with L-SPARK, Canada’s largest software-as-a-service accelerator, BlackBerry QNX helps companies research and develop product prototypes in areas such as robotics, device security, sensor fusion (e.g. LiDAR, radar, cameras and GPS), functional safety, analytics, medical devices and autonomous vehicles.
Check Out Our Other Ultimate GuidesReal-time Operating Systems Provides embedded RTOS basics and considerations when choosing between an open source or commercial OS options READ THE GUIDE Embedded Systems Security Covers topics such as embedded systems protection, security exploits and mitigation, and best practices READ THE GUIDE Offers key concepts and information on standards for safe system design READ THE GUIDE WP.29 Cybersecurity Vehicle Regulation Compliance Information about the UNECE WP.29 regulations, the countries where they apply and how they aim to mitigate the cybersecurity risks posed to passenger vehicles. Read the Guide Click here to download the Ultimate Guide to Autonomous Systems. Our team of experts are here to answer your
questions. What is the diffrence between seeing the driving environment and perceiving that same environment?Terms in this set (6)
What is the difference between seeing the driving environment and perceiving that same environment? When you perceive something, you give value and meaning to it. Seeing something is just looking at it.
How much does a driver use his or her vision to identify the driving environment?About 90% of what a driver identifies in a driving environment is through their sense of vision. While standing stationary your field of vision is 180 degrees or more, but as your speed increases your field of vision decreases. Move your eyes from side to side to detect possible dangers while driving.
What is selective seeing in driving?When we drive, our brains filter visual stimuli to focus our attention on things we need to notice to operate our vehicle safely. Is the vehicle in front of us slowing down? Is the light going to turn yellow? This is called selective attention.
What three major elements should you always look for in any driving environment?Regardless of the driving environment, you should always look for other roadway users, roadway features, changing conditions, and traffic controls that may affect your intended path of travel.
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