<h2 dir="ltr" id="isPasted">Enhancing the Motor Selection Process</h2>At any stage throughout your DC motor selection process, you can benefit from collaborating with an application engineer to ensure your provided with the optimal dc motor solution. Early engagement with an applications engineer has been proven to save design engineers valuable time throughout the entire motor selection process. When your application requires a DC motor or gear motor, contact an applications engineer as early in the design process as possible for maximum benefit.Your timeline and expectations are very important. The first step an application engineer will take is to learn about your project’s timeline ensuring all items are delivered in a timely manner. On average, engineers save over 10 hours of research time during their motor selection process by speaking with an ISL Products applications engineer.<img alt="Graph showing added value of early engagement dc motors" src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjI2ODk5OTE2NTMxLVdlYnNpdGUgQXBwIEVuZy4gQmVuZWZpdHMgLSBNb3RvcnMucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" class="fr-fic fr-dii"><h2 dir="ltr">Start the Discussion with an Applications Engineer</h2>An application engineer will ask some preliminary questions to learn more about your application and motor requirements in order to provide the optimal motor solution. Some common questions they may ask you early in the design process are:<ul><li dir="ltr">What<a href="https://islproducts.com/dc-motors-and-dc-gear-motors/" target="_blank">&nbsp;</a>type of motor are you interested in: brushed, brushless (BLDC), stepper, etc.?</li><li dir="ltr">Are you considering a<a href="https://islproducts.com/design-note/planetary-gear-motors-vs-spur-gear-motors/" target="_blank">&nbsp;gear motor</a> for additional torque output?</li><li dir="ltr">Do you have any preliminary application data that may benefit us in the motor selection process?</li><li dir="ltr">What are some of the more critical motor parameters that we should be aware of?</li></ul>Once these questions are answered, the applications engineer will analyze your requirements and provide a preliminary motor solution. For an even faster process, submit the information through ISL's <a href="https://islproducts.com/motors-selection-guide-specification-upload/" target="_blank">Motor Selection Guide</a> so our applications engineers can look over the data before the first call or email.&nbsp;<h2 dir="ltr">Preliminary Design Specifications</h2>Preliminary design specifications will include an overall dimensional drawing and motor performance curves. Our proprietary motor simulation software allows us to provide projected performance data very early on in the motor selection process, even before a sample is made.A motor / gear motor design database helps an application engineer streamline the selection process even further. They have the ability to cross-reference your requirements to pre-existing designs, making the design process much quicker. If slight alterations are needed to meet your specific requirements they will make those adjustments.<h2 dir="ltr">Parameters to Consider During Motor Selection</h2><h3 dir="ltr">Torque &amp; Speed</h3>The two most important parameters when selecting a motor are the torque and speed. More specifically, the torque and speed you would like the motor to operate at under the anticipated load. The option of adding a gear head to the motor will significantly increase the torque available but reduce the speed.<h3 dir="ltr">Voltage &amp; Current Draw</h3>When dealing with any DC powered device, understanding the available voltage is important. The voltage will dictate a lot about a motor’s internal design characteristics. Once the voltage is determined, another parameter to consider is the current draw. Current draw becomes a more important factor if the device is battery powered. If you’re using a constant power source, the current draw may not be as critical. Understanding these electrical parameters helps the applications engineer get a feel for the overall power available.<h3 dir="ltr">Understanding the Data</h3>It’s very important that you understand the data that is provided to you as well as your application’s requirements. All of these are crucial in the design and performance of your application or device. An apps engineers will help to educate you and answer any questions throughout the entire process.<h2 dir="ltr">Application Requirements &amp; Design Considerations</h2>Providing application duty cycle information to an apps engineer will give ample insight on how the motor will be expected to perform. When discussing duty cycle, you should mention if the motor will be running continuously or intermittently. If a duty cycle is intermittent, how long will it operate (ON time) and what is the rest period in between (OFF time)? Will the motor be changing rotational direction? If so, make sure there is enough dwell time in between changes in direction.With the use of in-house motor test equipment dc motor manufacturers are able to accurately simulate your expected duty cycle and provide useful insight on how a specific motor will perform. This equipment also allows manufacturers to generate performance curves illustrating the speed, torque, current draw and power of a motor from no-load to stall. All of these figures can be signed off on before moving onto mass production, ensuring you get exactly what you need.<h2 dir="ltr">Dedicated Service After The Selection Process</h2>Even after the motor selection process is complete, our dedicated team of application engineers are still working to provide you with the most optimal components. Our post-production quality testing ensures our motors meet or exceed your expectations before the motors arrive at your facility.Our goal is to make the overall motor selection process quick and exciting for you and your team. We are able to accomplish this by providing valuable insight from many years of experience and by serving as an extension of your engineering team. Get started, <a href="https://islproducts.com/contact/" target="_blank">reach out to an Applications Engineer today</a>!

Early Engagement Benefits with an Applications Engineer

Save valuable time by discussing your dc motor requirements early in the design process with an applications engineer.


Benefits of Early Engagement With an Applications Engineer: DC Motors and Gear Motors

<h2 dir="ltr" id="isPasted">What is a DC Motor?</h2>A Direct Current (DC) motor is a rotating electrical device that converts direct current electrical energy into mechanical energy. An Inductor (coil) inside the DC motor produces a magnetic field that creates rotary motion as voltage is applied to its terminal. Inside the motor is an iron shaft, wrapped in a coil of wire. This shaft contains two fixed magnets, North and South, on each side which causes both a repulsive and attractive force, producing torque. <img alt="Inside the DC Motor" src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1625081828033-Fig+1+-+2.png" class="fr-fic fr-dii" style="width: 778px; height: 346.978px;" width="624"><h2 dir="ltr">What is a DC Gear Motor?</h2>A gear motor is an all-in-one combination of a motor and gearbox. The addition of a gear head to a motor reduces the speed while increasing the torque output. The most important parameters in regards to gear motors are speed (rpm), torque (lb-in), and efficiency (%). In order to select the most suitable gear motor for your application you must first compute the load, speed and torque requirements for your application. Not all gear motors are the same. There are <a href="https://islproducts.com/component/spur-gear-motors/" target="_blank">Spur Gear Motors</a>,<a href="https://islproducts.com/component/planetary-gear-motors/" target="_blank">&nbsp;Planetary Gear Motors</a> and<a href="https://islproducts.com/component/worm-gear-motors/" target="_blank">&nbsp;Worm Gear Motors</a>, each one excelling at a different task. Read our article, <a href="https://www.wevolver.com/article/the-motors-inside-autonomous-robots" target="_blank">The Motors Inside Autonomous Robots</a>, to get a better understanding of these different types of gear motors.&nbsp; <div class="fr-img-space-wrap"><img alt="DC Gear Motor Construction" src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1625082292903-Wevolver+Body+DC+Motor+Basics.png" class="fr-fic fr-dii" style="width: 513px;"></div>&nbsp;<h2 dir="ltr">The Motor Selection Process</h2>The motor selection process, at the conceptual design phase, can be challenging. The following key points can help you determine and select the most appropriate motor or gear motor for our application.<ol><li dir="ltr">Design Requirements&nbsp;–&nbsp;A design assessment phase where the product development requirements, design parameters, device functionality, and product optimization are studied.</li><li dir="ltr">Design Calculations&nbsp;–&nbsp;Calculations used to determine which motor would be the best solution for your application. Design calculations determine gear ratio, torque, rotating mass, service factor, overhung load, and testing analysis.</li><li dir="ltr">Types of DC Motors/Gear motors – The most common electrical motors convert electrical energy to mechanical energy. These types of motors are powered by direct current (DC).<ul><li dir="ltr"><a href="https://islproducts.com/component/brushed-dc-motors/" target="_blank">Brushed</a></li><li dir="ltr"><a href="https://islproducts.com/component/brushless-dc-motors/" target="_blank">Brushless</a> (BLDC)</li><li dir="ltr"><a href="https://islproducts.com/component/planetary-gear-motors/" target="_blank">Planetary Gear Motors</a></li><li dir="ltr"><a href="https://islproducts.com/component/spur-gear-motors/" target="_blank">Spur Gear Motors</a></li><li dir="ltr"><a href="https://islproducts.com/component/stepper-motors/" target="_blank">Stepper</a></li><li dir="ltr"><a href="https://islproducts.com/component/coreless-brushed-dc-motors/" target="_blank">Coreless</a> &amp; <a href="https://islproducts.com/component/coreless-brushless-dc-motors/" target="_blank">Coreless Brushless</a></li><li dir="ltr"><a href="https://islproducts.com/component/dc-servo-motors/" target="_blank">Servo</a></li></ul></li></ol> <ol start="4"><li dir="ltr">Motor Specifications&nbsp;– Once the design calculations are performed, and the application parameters are defined, you can use this data to determine which motor or gear motor will best fit your application. Some of the most common specs to consider when selecting a motor or gear motor would be:<ul><li dir="ltr">Voltage</li><li dir="ltr">Current</li><li dir="ltr">Power</li><li dir="ltr">Torque</li><li dir="ltr">RPM</li><li dir="ltr">Life Expectancy / Duty Cycle</li><li dir="ltr">Rotation (CW or CCW)&nbsp;</li><li dir="ltr">Change in Rotation / Dwell Time</li><li dir="ltr">Shaft Diameter and Length</li><li dir="ltr">Enclosure Restrictions</li></ul></li></ol><h2 dir="ltr">Gear Motor Performance Curves</h2>A motor's performance and gearbox performance are combined into one graph by displaying three specific parameters. These three parameters are speed, torque and efficiency. These performance curves are essential when selecting a gear motor for your application.<img alt="Gear Motor Performance Curves" src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1625082139276-1.png" class="fr-fic fr-dii">&nbsp;<ul><li dir="ltr">Speed/Revolutions&nbsp;(N) – (unit: rpm)&nbsp;indicated as a straight line that shows the relationship between the gear motors torque and speed. This line will shift laterally depending on voltage increase or decrease.</li><li dir="ltr">Efficiency&nbsp;(η) – (unit: %)&nbsp;is calculated by the input and output values, represented by the dashed line. To maximize the gear motors potential it should be used near its peak efficiency.</li><li dir="ltr">Torque&nbsp;(T) – (unit: gf-cm)&nbsp;this is the load borne by the motor shaft, represented on the X-axis.</li><li dir="ltr">Current&nbsp;(I) – (unit: A)&nbsp;indicated by a straight line, from no load to full motor lock. This shows the relationship between amperage and torque.</li><li dir="ltr">Output&nbsp;(P) –&nbsp;(unit: W)&nbsp;is the amount of mechanical energy the gear motor puts out.</li></ul>For example, let’s consider the performance curve below&nbsp;(figure 5)&nbsp;for a DC gear motor.<ul><li dir="ltr">Maximum operating efficiency (70%) for this motor would occur at 3.75 lb-in / 2,100 rpm.</li><li dir="ltr">As torque increases the speed and efficiency decrease. The result of increased torque is poor output performance and the device will eventually fail to function once the motor reaches its stall torque (18 lb-in).</li></ul>&nbsp;<div class="fr-img-space-wrap"><img alt="DC Gear Motor Torque Performance Curves" src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1625082178768-2.png" class="fr-fic fr-dii" style="width: 548px;"></div>&nbsp;Gear motor performance curves are a helpful tool when selecting a motor for your application. To get the most out of the performance curves it’s important to thoroughly understand the application's requirements. You can use your load and speed requirements to help determine the required torque. Most DC motor and gear motor manufacturers provide performance curves upon request.

Get up to speed on what makes DC motors spin!

DC Motor & DC Gear Motor Basics

<h2>Prepare For The Robot Revolution</h2>Autonomous Robots are becoming the new normal as they get integrated into industrial settings as well as our everyday lives. It&rsquo;s not all robot arms and sci-fi security bots though, a lot of current autonomous robots resemble normal warehouse objects like conveyor belts and palette jacks. Manufacturing and distribution facilities are incorporating Autonomous Robots into their workflow more and more. Delivery services like Amazon, UPS and food delivery services are beginning to use drones and other AGV (automated guided vehicles) to deliver items to your front door.As these automated devices rise in popularity, the demand for them to carry out different tasks increases. One of the most critical components within any autonomous device is the DC motor or gear motor. There are many different types of motors, each of them excelling at specific tasks. To better explain how and why certain motors are selected when designing autonomous robotics, let&rsquo;s look at what differentiates them and how they are used.<a href="https://islproducts.com/component/brushed-dc-motors/" target="_blank">Brushed Motors</a>: The most common type of DC motor and has been around the longest. They&rsquo;re great for a variety of tasks and are easy to operate due to their simplicity. Their low cost relative to other types of motors makes them a popular choice. To increase the controllability of a brushed motor while keeping the costs down, you can choose to have an encoder added, though this usually increases the cost.Brushed motors are typically used for tasks where speed is the main factor, like drive motors to move AGVs around or to spin the cleaning brush on a floor scrubbing robot. Other simplistic low-torque tasks are where brushed motors are optimal. For example, the door release motor on delivery bots.<a href="https://islproducts.com/component/brushless-dc-motors/" target="_blank">Brushless Motors</a>: These are a good option for applications and tasks that require more precision and control. Brushless motors use an external controller to regulate speed. You do have to make room for the motor controller elsewhere within the application though. Due to the absence of brushes BLDC motors have a much longer usage life than a standard brushed motor, though there is an increase in cost. They are often picked over Brushed motors due to their quiet nature and longer service life. The versatility of BLDCs means that they&rsquo;re a solid choice for most applications.Brushless motors are the perfect choice for applications that need high performance in a small package. They work great as enhanced precision drive motors and as joints on robotic arms. They also serve well for higher speed requirements for carrying out tasks like drilling. Outrunner types of BLDC motors are used mostly in drones as the propeller motor. More companies are starting to use them in other unique ways to accommodate different autonomous functions.&nbsp;<a href="https://islproducts.com/component/stepper-motors/" target="_blank">Stepper Motors</a>: A type of BLDC motor, Stepper motors operates in small and precise &ldquo;steps&rdquo; that allow for incredibly high precision. Stepper motors are open-loop positioning, meaning they don&rsquo;t rely on sensors or monitors, saving on size, weight, and complexity.Stepper motors are great for tasks that require deliberate and precise movement as well as actions that require a hold and pause. This makes them an ideal choice for any type of placement or movement device, whether that is a robotic arm or a Cartesian grid system like on a 3D printer. Stepper motors are also well suited for applications and devices that hold and dispense items, like vending machines. Captive and Non-Captive stepper motors are great for linear movements like sophisticated locking systems or controlling the throttle on gas powered autonomous agricultural equipment.<h2 dir="ltr">Need More Torque? Use A Gear Motor&nbsp;</h2>A common way to increase the torque output of a DC motor is to couple it with a gearbox. The three most common types of these are Planetary, Spur, and Worm gear motors. Each gear motor has its own unique characteristics and purpose within the autonomous world.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjIyMTI1ODk2MTk3LVRoZSBNb3RvcnMgSW5zaWRlIEluZC4gQXV0b25vbW91cyBSb2JvdHMucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 700px;" class="fr-fic fr-dib"><a href="https://islproducts.com/component/spur-gear-motors/" target="_blank">Spur Gear Motors</a>: The most cost efficient gear motor solution, using straight toothed large and small gears stacked on parallel shafts. Due to their compact construction, they are the best choice for size constricted situations. They are a great option for light work loads like automated rollers or for use at lower torque values like in an autonomous auger system.&nbsp;<a href="https://islproducts.com/component/planetary-gear-motors/" target="_blank">Planetary Gear Motors</a>: This type of gear motor is designed with several satellite gears revolving around one central sun gear. Since several planetary gears are touching the sun gear at once the load is distributed, allowing planetary gear motors to sustain higher torque values. This makes them ideal for higher load and speed applications. Planetary gear motors are most commonly used within robotics where a joint or claw needs to operate varying loads, intermittently. They can be found in forklifts and warehouse robots. They are used in all types of industrial conveying and printing machines.<a href="https://islproducts.com/component/worm-gear-motors/" target="_blank">Worm Gear Motors</a>: These use a &ldquo;worm&rdquo; gear to maximize the motor&rsquo;s torque. The configuration of a worm gearbox turns the output shaft 90 degrees, allowing for a smaller mounting footprint. In addition, worm gear drives will only turn when power is applied, this means that they are self locking in the event of a power failure or a component breakage. This makes them desirable for situations where heavy loads need to be lifted. They can be found powering pulley and track systems for autonomous off-road vehicles as well.Recommended reading:&nbsp;<a href="https://www.wevolver.com/article/servo-motors-vs-stepper-motors" rel="noopener noreferrer" target="_blank">Servo Motors vs. Stepper Motors</a>As you can gather, in the growing world of autonomous robots and vehicles, motors and gear motors are what literally drives them forward. Using a slew of different motors allows an AGV to maneuver fast, light heavy objects, and maximize power efficiency. The recent expansion in the AGV market is built entirely on these motors, so make sure you use the right motor for the job.

Autonomous Robots use a variety of unique dc motors and gear motors to carry out their multitude of operations. ISL Products explains how and where these dc motors are used.

The Motors Inside Autonomous Robots

The guide to understanding the state of the art in hardware & software for self-driving vehicles

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References

Introduction

Sensing

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Acting

User Experience

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Use Case: Autonomous Racing

Summary

2020 Autonomous Vehicle Technology Report

This article is part of a series about ADAS and Autonomous Vehicles, sponsored by <a href="https://www.nexperia.com/" rel="noopener noreferrer" target="_blank">Nexperia</a>. We'll start the series by unpacking the concept of ADAS and exploring its impact on the world of semiconductors. The article is written by Ahmed Faizan Sheikh and co-authored by Ian Kennedy and Wayne Lawson. &nbsp;The second article will dive into new semiconductor products that can increase reliability and performance in electrical automotive systems. Find it&nbsp;<a href="https://www.wevolver.com/article/putting.highperformance.computing.into.cars.automotive.discrete.semiconductors.for.autonomous.driving" rel="noopener noreferrer" target="_blank">here</a>.&nbsp;<hr>Advanced Driver-Assistance Systems, also known as ADAS, are electronic systems that help with monitoring, warning, braking, and steering tasks in a vehicle. These technologies exist at different levels. For example, infotainment systems, rear-view cameras, blind spot, and lane departure warnings are applications of this technology which empower the driver with crucial information but also let them exercise control over the vehicle at all times.&nbsp;Next are semi-autonomous systems (SAS), like lane-keep assistance, which enable the vehicle to control itself for a brief period but allow the driver to override the automatic control when needed.&nbsp;Lastly, highly autonomous systems are the ones that take full control of the vehicle at times, like during automatic parking.All these subsystems come together to realize automated and semi-autonomous systems. From electronic stability control systems which help drivers regain control of their vehicles as needed, adaptive headlights which adjust their direction and intensity as per the road conditions, a rearview video system which allows the driver to see the area behind the rear bumper, adaptive cruise control which determines the speed of the vehicle based on the position of the driver’s vehicle with respect to the vehicle in front, and so on.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNTczNTcwMzEyOTExLUFEQVMgb3ZlcnZpZXcgMDMuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==">Examples of ADAS systems (blue) and Sensors (black)<h1>Components of ADAS</h1>Quite predictably, ADAS has played an important role in the development of autonomous cars and will play an even critical role in the years to come. But before we delve deeper into this, let’s understand how ADAS works and what makes up an ADAS system.<h2>Sensors</h2>Sensors capture real-time actionable data from the environment that provide input for the various Advanced Driver-Assistance Systems in a vehicle. Commonly used ADAS sensors include cameras, ultrasonic, radar, and Lidar sensors. They’re often located in the rear and front bumpers of the car and side-view mirrors.&nbsp;<h2>Software &amp; Data</h2>Most automotive companies are employing advanced software to process the incoming sensor data, learn and make decisions, and actuate the hardware for a specific response. Machine learning and artificial intelligence are ruling the industry and feeding the algorithms to decide how to behave in varied situations.&nbsp;The mapping functions of ADAS are used to collect and store geographical and infrastructure data related to vehicle sensors.<h2>Processors</h2>Electronic Control Units (ECUs) and Microcontroller Units (MCUs) are the hardware components (the electronic circuitry) that the software runs on. They are often dedicated to a single or narrow range of tasks, so with increasing ADAS applications, the number of processors is likely to increase as well. However, increasingly vehicle manufacturers are changing their approach from embedded software that is running on ADAS-specific ECUs to higher-level software platforms running on centralized ECUs or MCUs.Recommended reading: <a href="https://www.wevolver.com/article/putting-high-performance-computing-into-cars-automotive-discrete-semiconductors-for-autonomous-driving" rel="noopener noreferrer" target="_blank">Putting high-performance computing into cars: automotive discrete semiconductors for autonomous driving</a>ActuatorsActuators execute the decisions made by the system. They come in many forms, depending on the ADAS system. For example, displays that provide information, or actuators that control the engine and steering for adaptive cruise control or lane-keep assistance. <img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNTczMjMwMzE4MzE3LUFEQVMgS2V5IENvbXBvbmVudHMgMDIuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==">Four control points in Advanced Driver Assitance Systems are key for autonomous driving and product differentiation. &nbsp; | &nbsp; Image courtesy McKinsey&amp;Company<h1>Centralized vs. Decentralized ADAS System Architecture</h1>As you can sense, with increasing capabilities and a larger number of sub-systems comes increasing complexity. One of the key questions on how to achieve highly effective sensing &amp; processing evolves around the concept of sensor fusion and the question of implementing a centralized versus decentralized architecture for fusion.Centralized ADAS System ArchitecturesIn a centralized architecture, all the Remote Control Units (RCUs) are directly connected to a central control unit. For instance, Lidar and ultrasonic sensors will be located in two different locations of a vehicle and will perform two different functions. These sensors will gather input and send it to a central control unit which processes the data.&nbsp;Decentralized ADAS System&nbsp; ArchitecturesA decentralized fusion system consists of a network of sensing units, each with an ability to process its raw data and communicate with the adjacent nodes.&nbsp;Which architecture is the right one?It is tough to determine as to which architecture is the right way to design a self driving car. Centralized architecture could sound like a better option as the measurements from different sensors are independent quantities and not influenced by other nodes; there are two drawbacks. There should be enough communication bandwidth to transport the raw data to the centralized node. This essentially means high-power processing, and this could prove to be costly.&nbsp;On the other hand, decentralized architecture is complex. Although the demand related to bandwidth and centralized processing is reduced greatly in such an architecture, it introduces latency between actuation and sensing phases and increases the challenges related to the sharing of misinformation.<h1>Engineering Challenges in Designing ADAS Systems&nbsp;</h1>ADAS technology development affects many parts of vehicle engineering. Vital requirements for future developments are:&nbsp;<ol><li>Increasing redundancy.</li><li>Reducing weight and size of components (such as electronics, sensors and cameras).</li><li>Assimilating exclusive functions into more comprehensive systems. Additionally, accomplishing more multifaceted ADAS functions involve not only input from more cameras and sensors but also the fusion of data from those sensor elements.&nbsp;</li></ol>RedundancyIncreasing automation and (semi-)autonomy in vehicles increases the importance of the reliability of automotive electronics both at the system- and component level. Therefore the concept of dual redundancy of key systems has been introduced to improve reliability and safety. For instance, in the event of failure of part of a vehicle’s ADAS system you still need to be able to control the steering and brakes; a so-called limp home mode. Examples of systems that need redundancy are: drive by wire, steering, and braking systems. &nbsp;To achieve hardware redundancy extra components are included, which allow the continuing operation of a system in the event of a partial failure, thus increasing the availability and reliability of the system. Take for example a traditional brushless motor with three phases; if one of these phases is lost, then the motor will fail to turn. &nbsp;However, if the motor is designed to have another 3-phase set of windings, then if one phase fails, the motor will still operate. &nbsp;The requirements for high levels of system availability are driven by standards such as ISO26262 for critical safety functions where Automotive Safety Integrity Level (ASIL) C or D is required. Modern mission-critical automotive systems now feature redundancy and high-reliability automotive power MOSFETs that adhere to AEC Q101 qualifications from the Automotive Electronics Council. &nbsp;Increased safety and reliability are great. However, dual redundancy has the potential to increase the size, weight, and complexity of electronic subsystems, which already have become bigger, heavier, and more complex with an increasing amount of ADAS systems.Semiconductor manufacturers are innovating to overcome these challenges around the weight, size, and reliability of their components. Examples of solutions are MOSFETS with two independent channels inside a compact footprint, enabling both space and weight savings for designers.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNTczNTA3Nzc5ODI5LVJTMTA3N19uZXhwZXJpYV9hYWEtMDE2MDA5LmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=">Dual LFPAK56D MOSFETS which include 2 independent channels inside a compact footprint. | Image courtesy NexperiaA future article in this series will particularly address reducing the size of electronic components by the use of automotive qualified highly reliable small size Discrete Flat No Leads (DFN) packages.InterferenceAlong the same lines, another important concern is related to interference and shortcuts. The automotive software industry must meet the strict safety requirements and follow the proper certifications to ensure that everything is going as intended. Freedom from interference is an important requirement. The electronic currents passing through a component of an electronic system should not impact a nearby component through interference.Besides adhering to standards and qualifications, something called Failure Mode and Effects Analysis (FMEA) can play an imperative role in discovering potential failures and studying their impact. FMEA can be an extremely powerful tool to lessen the error rate in an automotive system and to recognize the underlying complications in any situation of failure.<h1>Conclusion</h1>ADAS systems have tremendous potential to increase the safety, comfort, and effectiveness of our vehicles and transportation systems. By many ADAS is seen as a stepping stone to fully autonomous vehicles.&nbsp;As we’ve seen, more systems and more advanced systems, increase weight, seize, and complexity both on a systems level as well as on the overall vehicle architecture level. Semiconductor companies are responding to above mentioned challenges by innovating their components. The technological expertise of semiconductor companies is more impactful than ever in the future development of vehicle autonomy.&nbsp;<hr>This article is written by Ahmed Faizan Sheikh and co-authored by Ian Kennedy and Wayne Lawson.This article is part of a series about ADAS and Autonomous Vehicles, sponsored by <a href="https://www.nexperia.com/" rel="noopener noreferrer" target="_blank">Nexperia</a>. In the next articles we will dive more deeply into the new semiconductor technologies that reliably enable you to bring high-performance computing, 5G connectivity, and sensing into cars. The second article will dive into how new semiconductor products can increase reliability and performance in electrical automotive systems. It's called&nbsp;“<a href="https://www.wevolver.com/article/putting.highperformance.computing.into.cars.automotive.discrete.semiconductors.for.autonomous.driving" rel="noopener noreferrer" target="_blank">Putting high-performance computing into cars – automotive highly reliable miniaturized Discretes for autonomous driving</a>” and written by Jan Birger Preibisch.More articles on autonomous vehicle technology can be found&nbsp;<a href="https://www.wevolver.com/?articles=true&category=autonomous%20vehicles" rel="noopener noreferrer" target="_blank">here</a>. To read more about how the electrification of cars' powertrains impact semiconductors; read this article by Ian Kennedy. References<a href="https://www.mckinsey.com/industries/semiconductors/our-insights/advanced-driver-assistance-systems-challenges-and-opportunities-ahead" rel="noopener noreferrer" target="_blank">• &nbsp; Advanced driver-assistance systems: Challenges and opportunities ahead &nbsp; - &nbsp; Mckinsey &amp; Company</a><a href="https://www.sciencedirect.com/science/article/pii/B9780128037294000040" rel="noopener noreferrer" target="_blank">• &nbsp; Motion Planning for Intelligent Transportation Systems, Chapter 4 Advanced Driver Assistance Systems - Rahul KalaRobotics and Artificial Intelligence Laboratory, Indian Institute of Information Technology.</a><a href="https://ieeexplore.ieee.org/document/6681152" rel="noopener noreferrer" target="_blank">• &nbsp; S. Sommer et al., "RACE: A Centralized Platform Computer Based Architecture for Automotive Applications," 2013 IEEE International Electric Vehicle Conference (IEVC)</a><a href="https://www.nexperia.com/applications/automotive/adas-radar-sensor-module.html" rel="noopener noreferrer" target="_blank">• &nbsp; ADAS radar sensor module design &nbsp; - &nbsp; Nexperia</a>

Vehicles increasingly contain electronic systems that assist drivers with monitoring, warning, braking, and steering tasks. Semiconductor companies are innovating to increase safety, while reducing weight, size, and complexity.

How Advanced Driver-Assistance Systems (ADAS) Impact Automotive Semiconductors

Autonomous driving is no longer sci-fi, it&rsquo;s become a reality and soon to be hitting our streets. Every week, Autotech companies are announcing their plan for self-driving tech. But, no two autonomous driving technologies are exactly alike.<blockquote class="lk ll lm">&ldquo;What we actually mean when we say a vehicle is self-driving, fully automated, and so on?Do we mean that the vehicle can drive itself anywhere at anytime, with no-assistance inside it?Or, that the vehicle always needs someone inside ready to take over just in case?Or, that the vehicle can drive itself, as long as it is within certain constraints, such as good weather and in a defined area of operations?&rdquo;</blockquote>To bring clarity to such situations, the Society for Automotive Engineers (SAE) outlined 6 levels of automation for automakers, suppliers, and policymakers to use to classify a system&rsquo;s sophistication via their standard titled&nbsp;<a class="de bv lo lp lq lr" href="https://www.sae.org/misc/pdfs/automated_driving.pdf" rel="noopener" target="_blank">J3016</a>.<h1 class="ls lt cj aq ap cb lu lv lw lx ly lz ma mb mc md me" data-selectable-paragraph="" id="173a">SAE&rsquo;s Six Levels of Autonomy</h1><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1570500234379-1_tVu-Og0xM0bL3IuVk7QP1Q.png" style="width: 766px;" class="fr-fic fr-dib">The driver assistance systems of level 1 are very common today. Some cars even offer steering and lane-keeping assistance, as well as remote-controlled parking &mdash; all systems defined as level 2 &ldquo;Partly Automated Driving (PAD)&rdquo;. A good example is Tesla&rsquo;s &ldquo;Autopilot&rdquo;, an industry-leading driver assistance system.A crucial shift occurs between Levels 3 and 4 when the driver releases responsibility for monitoring the driving environment to the system. Level 3 &ldquo;Highly Automated Driving&rdquo;, level 4 &ldquo;Fully Automated Driving&rdquo; and level 5 &ldquo;Full Automation&rdquo; are still in the testing phase.<h1 class="ls lt cj aq ap cb lu lv lw lx ly lz ma mb mc md me" data-selectable-paragraph="" id="3184">Level 0: No Automation</h1>This is where the human driver controls the car completely without any support from a driver assistance system.<h1 class="ls lt cj aq ap cb lu lv lw lx ly lz ma mb mc md me" data-selectable-paragraph="" id="2ffb">Level 1: Driver Assistance</h1>SAE&rsquo;s Level 1 is an automated system on the vehicle that can sometimes assist the human driver to conduct some parts of the driving task. In fact, many top-of-the-range car models offer level one automation. You&rsquo;re still the driver with full-control on driving however, you may call upon technology like adaptive cruise control for active safety.At Level 1, a computer can control either steering or acceleration/braking, but it is not programmed to do both at the same time. To sum it up, you still have full responsibility to monitor road situations and assume all driving functions if the assistance system cannot do so for any reason.<h1 class="ls lt cj aq ap cb lu lv lw lx ly lz ma mb mc md me" data-selectable-paragraph="" id="c93c">Level 2: Partly Automated Driving</h1>Functions that make partial automation possible are already a reality and in practice. Semi-autonomous driving assistance systems, such as the Steering and Lane Control Assistant including Traffic Jam Assistant, make daily driving much easier. They can brake automatically, accelerate and, unlike level 1, take over steering.With the remote-controlled parking function, it&rsquo;s possible to pull into tight spots without a driver for the first time. In level 2, the driver continues to remain in control of the car and must always pay attention to traffic.Here&rsquo;s the list of some driving assistance systems,<ol><li class="kw kx cj aq ky b kz la lb lc ld le lf lg lh li lj nm nn no" data-selectable-paragraph="" id="594c">Adaptive Cruise Control automatically adapts speed to maintain a safe distance from vehicles in front.</li><li class="kw kx cj aq ky b kz nq lb nr ld ns lf nt lh nu lj nm nn no" data-selectable-paragraph="" id="ae0d">Autonomous Emergency Breaking detects an obstacle, warn the driver or automatically brake to avoid or mitigate a crash.</li><li class="kw kx cj aq ky b kz nq lb nr ld ns lf nt lh nu lj nm nn no" data-selectable-paragraph="" id="fb01">Lane Detection using a forward camera to detect lane markings on the road.</li><li class="kw kx cj aq ky b kz nq lb nr ld ns lf nt lh nu lj nm nn no" data-selectable-paragraph="" id="4273">Lane Keeping Assist combines a forward-facing camera to detect lane markings with an electric steering system, keeping the vehicle in the center of the lane.</li><li class="kw kx cj aq ky b kz nq lb nr ld ns lf nt lh nu lj nm nn no" data-selectable-paragraph="" id="7855">Parking Assistance systems are designed to help a driver park. Some perform the entire job automatically, while others simply provide advice so that the driver knows when to turn the steering wheel and when to stop.</li><li class="kw kx cj aq ky b kz nq lb nr ld ns lf nt lh nu lj nm nn no" data-selectable-paragraph="" id="cfa5">Parking Line Detection system that detects markers on the road surface in order to determine the exact location of parking lots.</li></ol><h1 class="ls lt cj aq ap cb lu lv lw lx ly lz ma mb mc md me" data-selectable-paragraph="" id="1767">Level 3: Highly Automated Driving</h1>In the third development stage, drivers gain more freedom to completely turn their attention away from the road under certain conditions. In other words, they will be able to hand over complete control to the car. The driver, however, must be able to take over control within a few seconds, such as at&nbsp;<a class="de bv lo lp lq lr" href="https://www.wired.com/2017/02/self-driving-cars-cant-even-construction-zones/" rel="noopener" target="_blank">road construction sites</a>.<h1 class="ls lt cj aq ap cb lu lv lw lx ly lz ma mb mc md me" data-selectable-paragraph="" id="ad46">Level 4: Fully Automated Driving</h1>Level 4 is considered to be fully autonomous driving, although a human driver can still request control, and the car still has a cockpit. In level 4, the car can handle the majority of driving situations independently. The technology in level 4 is developed to the point that a car can handle highly complex urban driving situations, such as the sudden appearance of construction sites, without any driver intervention.The driver, however, must remain fit to drive and capable of taking over control if needed, yet the driver would be able to sleep temporarily. If the driver ignores a warning alarm, the car has the authority to move into safe conditions, for example by pulling over. While level 4 still requires the presence of a driver, cars won&rsquo;t need drivers at all in the next, final level of autonomous driving. However, their operations will be constrained to certain situations,<ul><li class="kw kx cj aq ky b kz la lb lc ld le lf lg lh li lj nv nn no" data-selectable-paragraph="" id="7d84">Limited to a geo-fenced area, such as paved streets in a defined area of town.</li><li class="kw kx cj aq ky b kz nq lb nr ld ns lf nt lh nu lj nv nn no" data-selectable-paragraph="" id="5e30">Limited by adverse weather, such as falling snow, snow-packed roads, intense rain, thick fog, etc.</li><li class="kw kx cj aq ky b kz nq lb nr ld ns lf nt lh nu lj nv nn no" data-selectable-paragraph="" id="dff8">Limited to a maximum speed, e.g., vehicles limited to 35 mph may be able to travel on most streets, but not on roads posted at 40 mph and above.</li></ul><h1 class="ls lt cj aq ap cb lu lv lw lx ly lz ma mb mc md me" data-selectable-paragraph="" id="f8b9">Level 5: Full Automation (Driverless)</h1>Unlike levels 3 and 4, the &ldquo;Full Automation&rdquo; of level 5 is where true autonomous driving becomes a reality.Here drivers don&rsquo;t really even need to have a license. and everyone in the car is a passenger. Cars at this level will clearly need to meet stringent safety demands, and will only drive at relatively low speeds within populated areas. They are also able to drive on highways but initially, they will only be used in defined areas of city centres.

Autonomous driving is no longer sci-fi, it’s become a reality and soon to be hitting our streets. Every week, Autotech companies are announcing their plan for self-driving tech. But, no two autonomous driving technologies are exactly alike.

Autonomous Driving Levels 0-5 Explained

Even though it has the right of way, the connected and automated Lincoln MKZ stops at an intersection because another vehicle is running the light. Vehicle-to-vehicle communication enabled this safety feature. Photo by Michigan Photography

Mcity demonstrates the powerful pairing of connectivity and automation.

How self-driving cars can be safer with connected technology

<div class="textimage basecomponent"><div class="textimage ">The future of mobility is measured in milestones: this February, Google subsidiary Waymo announced that its fleet of self-driving cars had covered over 8 million kilometres on public roads. This came shortly after Uber&rsquo;s announcement that it had completed 3 million kilometres of autonomous driving. If industry has its way, then we will soon be sharing all our streets with vehicles controlled by algorithms instead of drivers. But is that a realistic scenario? Or simply a rose-tinted vision of a tech-driven future?We asked one of the leading experts in this field, Italian researcher Emilio Frazzoli, Professor of Dynamic Systems and Control at ETH Zurich since October 2016. &ldquo;It all depends what level of autonomous mobility you have in mind,&rdquo; he replies. &ldquo;I would say it will be at least another 15 years before you can buy a self-driving car from a dealer. But if you mean a limit- ed kind of car sharing, then it&rsquo;s already happening.&rdquo; In fact, this latter concept is a core part of Frazzoli&rsquo;s own research. In mid-2018, the ride sharing company Lyft launched a service on the Las Vegas Strip that allows anyone to book one of a fleet of 30 BMWs through its app. The driverless cars are controlled by algorithms developed by vehicle technology company Aptiv, which acquired NuTonomy &ndash; the start-up founded by Frazzoli &ndash; in October 2017.<h2>Rethinking urban mobility</h2>Before joining ETH, Frazzoli spent ten years as a professor at the prestig- ious MIT in Boston. Autonomous systems &ndash; initially aircraft and drones &ndash; were the focus of his work right from the start. &ldquo;The technical side of that was generally pretty cool, but it wasn&rsquo;t really doing much to help solve the challenges society is facing.&rdquo; In 2009, he found himself pondering a fundamental question: &ldquo;Back then, the main argument for conducting research into self-driving cars was the idea that they would make road traffic safer.&rdquo; While acknowledging the truth of that statement, at least in the long term, Frazzoli realised there was potentially a much larger, medium-term benefit to be gained from completely rethinking the issue of individual mobility for city dwellers.&ldquo;The goal of my research group is a form of mobility that combines the convenience of a private car with the sustainability of public transport.&rdquo; In other words, a kind of Uber, but driverless and therefore much more economical and available. Plus &ndash; thanks to electrification and better capacity utilisation &ndash; a solution that offers significantly lower energy consumption and CO2 emissions. Right now, people use private cars, on average, just 5 percent of the time, which means the cars spend the remaining 95 percent of the time standing idle in car parks and garages or on the street. This makes no sense in terms of sustainability, urban development or resource efficiency.Frazzoli&rsquo;s start-up NuTonomy, which develops control software for autonomous vehicles, began drawing up plans to test self-driving cars in Singapore back in 2014. At around the same time, the professor published an article in which he investigated how replacing all the private vehicles in the 719-square-kilometre city-state with shared, self-driving vehicles would affect traffic volumes. His results showed that the mobility needs of Singapore&rsquo;s entire population could be met with some 40 percent of the vehicles (350,000 instead of 800,000).One year later, Prime Minister Lee Hsien Loong unveiled his vision of a &ldquo;car-lite future&rdquo; based on autonomous vehicles, the expansion of public transport and the fostering of slow traffic such as walking and cycling. With 5.5 million inhabitants and a population density of 7,697 people per square kilometre &ndash; compared with Switzerland&rsquo;s figure of 203 &ndash; Singapore is more dependent on efficient transport than any other major metropolitan area.That is why Singapore has spent years trying to crack down on demand for private cars by imposing high taxes and charging up to 70,000 dollars for the certificates of entitlement required to own a vehicle. More than ten companies are current- ly testing their systems in a 2-hectare test facility at Nanyang Technological University in the western part of Singapore Island. And plans are already in place to operate the first self- driving buses outside rush hours in three of the city&rsquo;s suburbs starting in 2022.</div><h2>Simulating transformation</h2>Pieter Fourie&rsquo;s &ldquo;laboratory&rdquo; is located in the western part of Singapore. He works in a sunlit office on the sixth floor of the CREATE Tower, a building encased in vertical foliage at the National University of Singapore (NUS). Here, he conducts research into the cities of the future on behalf of ETH Zurich&rsquo;s Future Cities Laboratory. Fourie heads up the Engaging Mobility project, which brought together government authorities and universities at a preliminary workshop in July 2017. The goal was to define the basic conditions required to implement city-wide, on-demand mobility using autonomous cars and buses.The researchers used the results of the workshop to formulate key research questions such as: What do we do with the current supply of parking spaces if the majority of vehicles are constantly on the road? Do we need to redefine the layout of our roads? And what effect will auto- mated, electrified transport have on existing public transport, energy requirements and safety?Fourie explores these and similar issues using the MATSim simulation platform developed by a group led by Professor Kay Axhausen at ETH Zurich&rsquo;s Institute for Transport Planning and Systems. MATSim is agent-based, which means the simulation is driven by the behaviour of individual agents rather than by overarching rules. &ldquo;On the basis of Singapore&rsquo;s most recent demographics, we are modelling a synthetic population that is as close as possible to the real one,&rdquo; Fourie says.Within this population, each individual agent exhibits a certain mobility behaviour and has a specific destination based on real-life traffic data. Fourie is now at the stage of tinkering with the underlying conditions, including the number of vehicles employed, their size, the maximum permissible waiting times for passengers, the availability of parking spaces and a variety of different traffic flows. He then lets the synthetic population loose on the simulation for 24 hours. The system automatically evaluates how efficiently the individual agents were able to reach their destinations in each scenario.Right now, Fourie&rsquo;s team is programming these kinds of simulations for the waterfront area of Tanjong &shy;Pagar, a district of some 2 square kilometres in the western part of Singapore. This site is currently being converted from a container terminal into a residential and commercial area. Fourie has already simulated more than 200,000 trips involving 60,000 individual agents. This included calculating how big the fleet of autonomous vehicles would need to be and how many kilometres the vehicles would have to cover to achieve an equivalent level of service in three different street typologies.The researchers also simulated four different parking strategies for a fleet of 4-, 10- and 20-seater vehicles. Preliminary results suggest that the transport system is at its most efficient if the shared vehicles are allowed to park in the street when they stop receiving requests for pick-ups. That holds true even if it means temporarily reducing the roadway capacity by one lane. The researchers&rsquo; findings also suggest that having fewer, but correspondingly larger, pick-up and drop-off stations has a favourable impact on traffic flow by reducing the detours cars have to take to collect passengers. The stations also need to be big enough to accommodate different vehicle sizes. Fourie is hoping to have these kinds of simulations up and running for the entire island as early as next year.<h2>Decision-making dilemmas</h2>Despite these rapid developments in Singapore and the fledgling services coming online in Las Vegas, Emilio Frazzoli still sees plenty of challenges ahead, especially when it comes to dealing with chaotic environments. &ldquo;We still don&rsquo;t know exactly how autonomous vehicles should behave in traffic,&rdquo; he says, explaining that this involves dozens of decision-making dilemmas that are an integral part of everyday traffic situations. For example, should a self-driving car cross a double line in order to avoid a potential collision? And what if an innocent road user is injured as a result of a manoeuvre designed to save a culpable driver from a fatal crash? These are the kinds of decisions that have to be defined when programming control algorithms. One key focus of Frazzoli&rsquo;s current research is therefore the &ldquo;rulebooks&rdquo; that should be used to prioritise these various decision- making criteria in control algorithms. At the top of the hierarchy are rules designed to ensure road users&rsquo; safety. At the bottom are rules designed to enhance passenger comfort.In a recent article, Frazzoli and his team estimated that it would take 200 rules in 12 hierarchy groups to prepare vehicles for every possible scenario, including low-priority rules such as not frightening animals on the edge of the road. Frazzoli feels the time has come for a broader public &shy;debate on autonomous driving: &ldquo;The coding of safety and liability rules is not something we should simply leave in the hands of engineers working for private companies&rdquo;. Ultimately, he argues, it is in everyone&rsquo;s interest to incorporate our new, virtual drivers into urban traffic as smoothly as possible &ndash; much like we do with new human drivers, but with the greater levels of safety, predictability and efficiency that autonomous vehicles offer.&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</div>

Emilio Frazzoli’s start-up NuTonomy develops control software for autonomous vehicles and uses Singapore as a test bed. (Photograph: NuTonomy)

Car sharing with autonomous vehicles could improve cities in many different ways. Singapore is taking a pioneering role, working with ETH researchers to explore the potential of personalised, electrified and automated public transport.

Algorithms take the wheel

Some call it a marvel of technology. Some call it a fad. Self-driving cars are constantly making the headlines. These vehicles, designed to carry passengers from point A to B without a human maneuver, are promised to bring greater mobility, reduce street congestion and fuel consumption, and create safer roads.Driverless vehicles are hardly a novel concept anymore, but what is really going on in the autonomous car industry? How do self-driving cars work? Who are making these cars? Why is it taking this long? This article will answer these questions.<h1 data-selectable-paragraph="">How do self-driving cars work</h1>To reach a destination, a driverless car needs to know the route, understand its surrounding, observe traffic rules, and make correct judgments when interacting with other vehicles and pedestrians on the road. To accomplish all this, it relies on the following key technologies:<ul><li data-selectable-paragraph="">Camera: to see things like lanes and traffic lights</li><li data-selectable-paragraph="">Radar: to sense objects, especially the big ones, and determine their distances</li><li data-selectable-paragraph="">Lidar: also to sense objects as Radar, but it’s much better in detecting small objects and mapping 3D objects. Unfortunately, <a href="https://www.wired.com/story/lidar-self-driving-cars-luminar-video/?source=post_page---------------------------" target="_blank">it is expensive and can still be a little unreliable at times.</a></li><li data-selectable-paragraph="">AI: the brain of the car. It combines the car’s sensors and camera visions to understand the path ahead and determine how the car should be maneuvered.</li></ul><h1 data-selectable-paragraph="">Leveling up</h1>The progression of driverless technology doesn’t go from no automation at all to full-on self-driving with no human intervention. In fact, SAE International, an automotive standardization organization classified autonomous cars to 5 levels:<ul><li data-selectable-paragraph="">Level 0 — No Automation:&nbsp;Human driver controls everything — steering, braking, and accelerating.</li><li data-selectable-paragraph="">Level 1 — Driver Assistance:&nbsp;The car provides some help with either steering OR accelerating. Cars with cruise controls fall into this category.</li><li data-selectable-paragraph="">Level 2 — Partial Automation: The car can control both steering and accelerating at the same time, with human drivers monitoring the environment and keeping their hands on the wheel. Tesla’s autopilot is an example of Level 2 automation.</li><li data-selectable-paragraph="">Level 3 — Conditional Automation: The car will control the car and monitor the environment, but may request human drivers to intervene in certain situations. Audi A8’s Traffic Jam Pilot was able to achieve level 3.</li><li data-selectable-paragraph="">Level 4 — High Automation: Compared to level 3, the autonomous car can handle more complex driving tasks. It may still ask for human intervene in rare situations such as extreme weather.</li><li data-selectable-paragraph="">Level 5 — Full Automation:&nbsp;A truly self-sufficient car. It will not ask for human intervene and can carry out all driving tasks. Google’s Waymo is an example of that.</li></ul><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1563614129520-self-driving_tech_levels.jpg" style="width: 766px;" class="fr-fic fr-dib"><h1 data-selectable-paragraph="">Key players in the market</h1>Many companies recognized that whether they like it or not, the disruption is inevitable. Hoping to get ahead of the competition, they have invested billions of dollars in the R&amp;D of key technologies behind self-driving cars.The transportation revolution attracted both big corporations and startups. <a href="https://blog.cometlabs.io/263-self-driving-car-startups-to-watch-8a9976dc62b0?source=post_page---------------------------" target="_blank">Over 260 startups</a> are ready to tackle every aspect of the ecosystem while forming strategic partnerships with others. Big corporations are also investing billions of dollars to aggressively establish and implement roadmaps. Some of the leading and high-profile companies include the following.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1563614178106-436da7b4-2493-11e9-8ce6-5db4543da632.webp" style="width: 766px;" class="fr-fic fr-dib"><h2 data-selectable-paragraph="">General Motors</h2>As one of the leading car manufacturer, GM has spent a lot of money to maintain its lead position in driverless cars. In 2016, it acquired self-driving tech company Cruise Automation for over $1billion. This unit received $2.25 billion investment from SoftBank and an additional $1.1 billion from GM itself in 2018. Furthermore, eager to dominate the market, GM bought its own LIDAR manufacturer so that it can rely less on partnerships. GM has been testing in San Francisco with a plan to expand to New York City. It plans to commercialize its self-driving car with ride-hailing services in 2019.<h2 data-selectable-paragraph="">Waymo</h2>Believe it or not, Waymo was established a decade ago. However, it is still considered to be the cool kid in the block. Valued at $175 billion, Waymo has accumulated over 8 million self-driving miles with a fleet of Chryslers, Hondas, and Jaguars. Just recently, Waymo announced its plan of purchasing 62,000 Fiat Chrysler vans for its ride-hailing service. Pledged to commercialize by the end of 2018, Waymo is leading the self-driving car race.<h2 data-selectable-paragraph="">Uber</h2>From the high-profile lawsuit against Waymo to the operation halt in Arizona and Pittsburgh, Uber has had a bumpy ride. However, Uber has not given up. With partners like Volvo and Daimler, Uber scored a $500 million investment from Toyota this year. Back on the streets of Pittsburg, Uber’s autonomous vehicle is driven manually to recalibrate its HD map of the city. It is also pumping money to its driverless car engineering hub in Toronto to continue its mission.<h2 data-selectable-paragraph="">Lyft</h2>Compared to Uber’s aggressive development and expansion strategy, Lyft’s approach is more controlled. Lyft partnered with Aptiv, a formerly bankrupted company that turned its tide by investing in driverless technology. Together they have completed over 5000 paid rides with 20 vehicles in Las Vegas, servicing popular destinations on the strip. When requesting Lyft rides, users can opt-in for driverless cars, and for now, there’s still a safety driver in the vehicle to monitor the ride.<h2 data-selectable-paragraph="">Tesla</h2>Tesla takes a completely different approach to driverless technologies. Instead of using LIDAR, Elon Musk believes the advancement of camera and image recognition technology are sufficient for automation. Although its current vehicles are equipped with auto-driving features, they still require human attention, and we have seen accidents reported due to the lack of human interventions. It’s yet to be seen how far Tesla can push its self-driving technology.<h2 data-selectable-paragraph="">Baidu</h2>Baidu leads the biggest driverless car effort in China since 2014. In 2017, it announced the Apollo, an <a href="https://github.com/ApolloAuto/apollo?source=post_page---------------------------" target="_blank">open source project</a> to facilitate the research and development of driverless cars. Baidu aimed to mass produce autonomous vehicles by 2019 to 2020, but their ability to successfully carry out this plan becomes doubtful when it lost multiple key AI talents and COO Lu Qi.<h1 data-selectable-paragraph="">What’s taking so long?</h1>Waymo was first established in 2009, and almost a decade later, its cars are finally getting ready to become commercialized. That’s quite a long time to release a product. Why does it take so long? Although eager to advance as quickly as possible, the self-driving car industry is facing key some challenges that they need to overcome in order to truly become common on streets. These issues include:LidarDriverless car experts agree that Lidar plays a key role in ensuring a safe trip. Similar to Radar, Lidar is also used to detect surrounding objects’ distance and shape. However, instead of using radio waves, Lidar sends infrared lights, which can better detect smaller objects (like rocks, or a cyclist and ) and objects in closer distance compared to Radar.So is Radar unnecessary for self-driving cars? Definitely not. Radar works better when detecting objects that are further away, and it’s much less sensitive to extreme weather than Lidar.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1563614240277-content_dam_lfw_print_articles_2018_11_1811lfw_jw_2.png" style="width: 766px;" class="fr-fic fr-dib"> Lidar measures distance to a target by illuminating the target with laser light and measuring the reflected light with a sensor. Image by LuminarAs you have probably figured, Radar and Lidar are a complementary pair and they can accomplish so much together for the driverless future.However, even though Lidar is not a new technology, it still needs further development. The bulky equipment comes with a hefty price tag of $75k per piece and is not ready for mass production. Driverless cars will also benefit greatly from higher resolutions and greater distance range than what the current Lidar technology can offer.Lidar’s room for improvement can be translated into a huge business opportunity. The trade secrets regarding Lidar technology was in the eye of the Waymo v. Uber storm in 2017. Now, over 50 companies are trying to improve Lidar and make it cheaper for mass production.AIDriverless cars rely on artificial intelligence to make judgments. AI identifies objects on the streets and determines how the car should behave in different situations. To train such intelligence, scientists use a huge amount of data so that the algorithm can learn objects on the road. For example, the algorithm can identify a bicyclist on the street because it has seen images of tens and thousands of bicyclists.We all have high expectations for what AI can accomplish, but it’s still far from perfect. For example, in the fatal accident caused by Uber’s self-driving car, the algorithm failed to recognize the victim, causing a delay in reactions. Furthermore, there are so many moving parts (literally) on the street, producing millions of possible scenarios. A tremendous amount of data is needed for the system to learn how to handle these scenarios, and we are just simply not there yet.MappingAnother race is happening in the mapping world. Driverless cars need more than the regular map we get on our phone. Although a self-driving car’s sensors and cameras can pick up objects on the street, it would be a lot safer to have an accurate 3D map of the route so that the car is familiar with all aspects of the street and can focus on detecting other elements like pedestrians. 3D maps also provide tremendous value during extreme weathers, when the data cameras and sensors provide are inadequate.Mapping is difficult because it requires a lot of data to produce an accurate representation of the world. Even Google map has low fidelity for rural areas. What’s more challenging is the constant need for continuously data update. Companies like Here, TomTom, DeepMap, and Google are all in the race to produce maps that can be an irreplaceable part of the ecosystem.InfrastructureJust as how new infrastructure was needed when automobile replaced horse carriages, self-driving cars also require updated infrastructure. Worn-off pavement markings and unclear street signages will all need to be upgraded for self-driving cars so that they can clearly see the road. This may sound easy, but the implementation calls for the creation of a uniformed standard, and collaboration between federal, state, and local agencies. We also need to build connected infrastructure as a way for driverless cars to communicate with nearby infrastructure. For example, in construction zones, rather than relying on worker’s hand gestures to direct traffic, devices should be installed so that signals can be transmitted to driverless vehicles.The infrastructure overhaul comes with a hefty price tag, but it is crucial to the safety of driverless cars. <a href="https://thehill.com/opinion/technology/353034-self-driving-cars-are-coming-but-us-roads-arent-ready-for-the-change?source=post_page---------------------------" target="_blank">States like Michigan</a> have begun testing new infrastructure with its modernization projects, and we will see more of them coming.Human CommunicationAutonomous vehicles may have programmed behaviors backed by AI to handle various scenarios on the street, but humans will also need to learn how to interact with autonomous vehicles.Frequently, drivers, pedestrians, bicyclists, and motorcyclists use gestures and eye contacts on streets to signal their intentions. But how will that work with driverless cars? One of the self-driving technology company Drive.ai <a href="https://medium.com/@andrewng/self-driving-cars-are-here-aea1752b1ad0?source=post_page---------------------------" target="_blank">tackled this problem by having these cars “talk to” pedestrians.</a> Embedded with LED screens on the front, rear and sides of the vehicle, these screens can display texts such as “waiting for you to cross”, providing a mean for the vehicle to demonstrates its intention.Human TrustWhile the industry has slowly got a grasp of human-vehicle communication, human trust is a more complex problem to solve, and it directly affects the adoption rate. In a <a href="https://www.reuters.com/article/us-autos-selfdriving-usa-poll/most-americans-wary-of-self-driving-cars-reuters-ipsos-poll-idUSKBN1FI034?source=post_page---------------------------" target="_blank">research conducted by the Reuters and Ipsos</a>, only 38% men and 17% women surveyed said they would feel comfortable riding a driverless car. <a href="https://www.researchgate.net/publication/324912188_Trust_in_driverless_cars_Investigating_key_factors_influencing_the_adoption_of_driverless_cars?source=post_page---------------------------" target="_blank">Another Research</a> shows that to gain people’s trust in autonomous vehicles, the industry needs to demonstrate the cars’ reliability, performance, privacy (e.g., location tracking), and security (e.g., hacking).The wariness is not surprising, given the novelty of the technology and the potential catastrophic consequence if things go wrong. These research results demonstrate that besides improving vehicle safety and performance, self-driving car manufacturers must establish trust with consumers by educating and promoting. Designing a compelling rider experience that addresses their needs and pain points is also important, as it highlights the benefits of riding self-driving cars.<h1 data-selectable-paragraph="">Buckle up for the future</h1>Human species have the <a href="http://www.slate.com/articles/health_and_science/science/2014/03/the_science_of_what_separates_us_from_other_animals_human_imagination_and.html?source=post_page---------------------------" target="_blank">exceptional talent of imagination</a>. What further sets us apart from other animals is the ability to build nested scenarios in our minds, share our fantasies with each other, and eventually work on a common goal that is based on imaginations. The rise of self-driving vehicles is precisely an outcome of collaborative imagination. We are witnessing an evolution based on rapid technology advancement, and sooner or later, human mobility may never be the same. We don’t know how many twists and turns there are ahead of us, but the journey to our destination sure is exciting.

Everything you should know before your next conversation about self-driving cars

A Beginners Guide to Self-Driving Cars

What sensors do we need for building a fully autonomous robot?Autonomous Robots are equipped with numerous sensors to perceive its surroundings as well as be aware of its own movements. The first step for achieving autonomy of robots i.e., robots moving from point A to point B on its own without colliding with anything, is awareness of the surrounding environment. Autonomous robots have a stack of sensors, among them, Wheel Odometers, IMU, GPS, Lidar, and Multiple Cameras being the most common. The current developments in the autonomous vehicles space also make use of sensors like Radar, Stereo Cameras in combination with the above stack.&nbsp;What is localization?<a href="http://www.cs.cmu.edu/~rasc/Download/AMRobots5.pdf" rel="noopener noreferrer" target="_blank">Localization</a> means to determine the current position and orientation of a body with respect to some coordinate system.How humans localize, is it a difficult task?Humans very naturally tend to determine their &nbsp;current position with respect to the different environmental landmarks/features around them. So, when we localize ourselves we tend to understand we are at some given distance and at certain angle from some house/tree/lamp post or any other landmarks. Given an empty featureless space even humans cannot localize. Thus, features are important for this localization task and thus we need a map filled with features/landmark to localize ourselves in that map, else it is an impossible task to perform.Then how do robots do it?The SLAM algorithm has two parts; the first is mapping and the second is localization. Autonomous ground robots have visual sensors like Lidar and Camera which can pretty well map its environment around. Then with 3D reconstruction from their data, robots generate something called a HD map. HD maps differ from normal maps, the former has a lot more features than the later. Once this map is ready, the robot starts localizing itself in this map. <a href="http://robots.stanford.edu/papers/thrun.pf-in-robotics-uai02.pdf" rel="noopener noreferrer" target="_blank">Particle Filter</a>, <a href="https://www-users.cs.umn.edu/~isler/pub/tase10.pdf" rel="noopener noreferrer" target="_blank">Triangulation</a>, <a href="http://www.cs.toronto.edu/~urtasun/courses/CSC2541/03_odometry.pdf" rel="noopener noreferrer" target="_blank">Visual Odometry</a> are some methods used for this purpose.&nbsp;Another widely used method for localization is <a href="https://www.cs.cmu.edu/~motionplanning/lecture/Chap8-Kalman-Mapping_howie.pdf" rel="noopener noreferrer" target="_blank">Extended Kalman Filter</a>. An EKF is a non-linear version of the linear Kalman Filter. It's a state-space estimator, what that means is that it can help in estimating the current state given input of the previous state. It's is used as a data fusion filter for localization tasks in robotics. It takes inputs from the IMU, Wheel Odometers and GPS and performs its computation based on a CTRV (Constant Turn Rate Velocity) model for a wheeled ground vehicle, to estimate the current position and orientation of the vehicle. Often this localization information is fused with visual odometry to achieve an accuracy of 100mm in the localization task.Once the robots know where they are in a map they can now start planning their path for the destination point B. Thus, invoking another interesting field of research called Path Planning. &nbsp; More resources on SLAM :1. <a href="https://blog.cometlabs.io/teaching-robots-presence-what-you-need-to-know-about-slam-9bf0ca037553" rel="noopener noreferrer" target="_blank">Teaching robots presense</a>2. <a href="https://en.wikipedia.org/wiki/Simultaneous_localization_and_mapping" rel="noopener noreferrer" target="_blank">SLAM</a>3. <a href="https://ieeexplore.ieee.org/abstract/document/1638022" rel="noopener noreferrer" target="_blank">Simultaneous Localization and Mapping</a>&nbsp;

Image: Highway image using LIDAR - Oregon State University (CC BY-SA 2.0)

A brief introduction to localization and mapping, and how these two functions are performed simultaneously during SLAM (Simultaneous Localization and Mapping).

How autonomous robots know where they are

This article is part of a series about the usage of robots in harsh environments, written by post-doctoral robotics researcher Matthew Nancekievill. Find the second article, on subsea environments,&nbsp;here.<hr>Lets face it, there are some jobs that we just don’t want to do, or CAN’T do that we will have to get robotic platforms to complete. This is especially true of harsh environments such as subsea, mining, space, arctic, often forgotten surgical robotics and nuclear decommissioning. In this article we are going to take a brief look at robotic platforms currently deployed within the nuclear industry, why they’re required and solutions that are still required for all you innovators out there. &nbsp;With decommissioning costing the UK £3billion/yr and estimated costs of £121 billion over the next 120 years, there is a requirement for increased efficiencies and decommissioning rates that robotics can provide.&nbsp;Hopefully this article acts as a summary of robotic solutions in nuclear decommissioning without being too much of an exhaustive list.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNTU5NjY4MDk3MDA3LUltYWdlIDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib"><h1>A look at the Nuclear Decommissioning Environment</h1>Decommissioning happens around us all the time, old buildings get torn down, coal power plants shutdown and vehicles get scrapped. The nuclear industry is no different with the reactors, storage facilities and processing elements all requiring decommissioning when they reach the end of their useful life.Hazardous substances can be found in all the above environments with asbestos, chemicals used during refinement, rare earth metals and oils that can’t be put into our main waste stream all examples of hazardous substances. The Nuclear industry faces all the same problems but adds one to the list, “nuclear waste”.I’ve always felt that nuclear gets a bad rap in the press, with all the pollutants and oil spills throughout the years created from coal power plants seemingly ignored when nuclear waste is mentioned. However, the effects of nuclear radiation on the body can be very unforgiving.To give you a flavour, researchers working with weak radioactive sources, such as myself, are allowed a total yearly dose of &lt;1 mSv attributed to radiation work, registered radiation workers in the UK &lt;20 mSv. This is a large safety factor to account for medically proven effects of radiation at radiation levels &gt;250 mSv with 1,000 mSv likely to kill you within a few days to a couple of weeks. (Average background radiation dose in the UK is approximately 2.7 mSv)Compare this to radiation doses in some of the most radioactive places on earth, such as the UK’s Sellafield Site or the Fukushima accident, where in the most extreme cases (no really, the most extreme cases, the majority is not like this) dose-rates of around 10,000 mSv.h-1 are possible (check-out <a href="http://irid.or.jp/en/research/20150420-2/" rel="noopener noreferrer" target="_blank">these survey results</a> from the IRID and the shape-changing robot mentioned later.This is before you add in the difficulties of the physically constrained and tight working spaces, high temperatures, contaminated water used for cooling and, in the case of nuclear accidents such as Fukushima, an unknown physical layout “behind the door” due to explosions within the reactor buildings.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNTU5NjcyODIxNzYyLUZ1a3UuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib"><h1>Current Practices</h1>In less radiologically extreme environments, much of the work is carried out by human workers in air-fed suits with multiple layers of gloves, some of which could be lead-lined (lead-lined gloves) worn to avoid contamination and puncturing of the suit on sharp edges. This often means that with all the getting ready, decontamination at the end of the shift and the physical exertion required to operate in these suits, an 8-hour work shift could result in anywhere between 15 minutes to 2 hours of actual decommissioning with power tools cumbersome to use and movement awkward. Workers have been known to empty their boots at the end of their shift of all their sweat that has built up… Workers are, at the root of it, tasked with dismantling the facility. This means cleaning, chopping and moving all sorts of materials into the correct waste stream and then moving on to the next object or structure.<h2>Robotics in Nuclear</h2>It is clear that some of these repetitive tasks or highly radioactive areas lend themselves to the use of robotic platforms. There has been a large body of work conducted on developing solutions for just that. Aquatic robotic platforms for use within submerged nuclear waste storage tanks, robotic manipulators for laser cutting of structures, drone-based devices for site surveys and ground-based robots for automated warehouse characterisation and unknown environments.Examples of these are:The Forth AVEXIS, developed jointly by Forth Engineering and the University of Manchester. A submersible ROV designed to be deployed within the Magnox Swarf Storage Silo and fit through a 6” access port. More information within the video.<iframe src="https://www.youtube.com/embed/OLvAQFz5wh8?&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" allowfullscreen="" class="fr-draggable" style="width: 766px; height: 443px;" frameborder="0" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-gtm-yt-inspected-7="true" id="626921597" title="Avexis ROV" data-gtm-yt-inspected-29="true" data-gtm-yt-inspected-37="true"></iframe>The LaserSnake2, which combines a multi-jointed “snake-arm” manipulator with a powerful laser-cutter. Developed by OCRobotics, The Welding Institute, National Nuclear Laboratory, Laser Optical Engineering Ltd. And ULO Optics. It is designed to cut and reduce the size of objects and structures to fit in dedicated waste containers.<iframe src="https://www.youtube.com/embed/hqOfRhJsaEQ?&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" allowfullscreen="" class="fr-draggable" style="width: 766px; height: 436px;" frameborder="0" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-gtm-yt-inspected-7="true" id="439090068" title="LaserSnake2 - Laser cutting for nuclear decommissioning at Sellafield - a world first." data-gtm-yt-inspected-29="true" data-gtm-yt-inspected-37="true"></iframe>Researchers from Bristol University have just recently flown a drone over the Chernobyl Red Forest highlighting the site survey capabilities of drones applicable to all nuclear sites.<iframe src="https://www.youtube.com/embed/_Eto98XTm-4?&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" allowfullscreen="" class="fr-draggable" style="width: 766px; height: 394px;" frameborder="0" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-gtm-yt-inspected-7="true" id="334628213" title="YouTube video player" data-gtm-yt-inspected-29="true" data-gtm-yt-inspected-37="true"></iframe>Hitachi-GE have also developed a “shape-changing robot” to characterise the internals of Fukushima. Designed to be passed through small gaps in a long cylindrical shape, it is then capable of morphing into a “U” shape for stability. Equipped with a radiation tolerant camera and dosimeter, multiple robots were deployed with valuable data returned.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNTU5NjY4MzQ5NTkyLVNoYXBlLWNoYW5naW5nIElSSUQtSGl0YWNoaSByb2JvdCAtIDQ1MC5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib">However, one of them got stuck, which leads me to my next point.<h1>The problem with Robots</h1>I love robots, and I believe that robotic systems HAVE to and WILL have a huge part to play in harsh environments, but there are still things that have so far left deployment of robotic systems on the fringes of use. These include, but are not limited to:<ul><li>Robots are dumb: When compared to a human assessing a situation. The Hitachi shape-changing robot fell foul of a common problem with robotic systems, it got caught in a hole in the grating it was driving on it wasn’t expecting and that could not be seen by the human operator with the robot not “smart” enough to avoid or raise a flag. Robots are only as smart as we make them!</li><li>Radiation effects: Robots readily survive longer than humans but there are still failures of the electronics in high dose areas.</li><li>Tether entanglement:&nbsp;Most robots (not including drones) are often required to be connected via tether. This is for safety, in-case the robot breaks, meaning it can be unceremoniously dragged out but causes issues with entanglement.</li><li>Robots require a skilled pilot: That skill-set is not common.</li><li>The industry isn’t ready: When things have been done a certain way for a long time, it is difficult to change that. Not to mention all the legal licensing issues and who takes responsibility when something goes wrong?! Media storms surrounding the ethics of robots taking jobs and becoming our future overlords do not help (thanks a lot Terminator).</li></ul><h1>In Conclusion</h1>There is a great body of work being completed within industry and research institutions developing bespoke solutions for specific problems and there have been many successful deployments and also many unsuccessful deployments, which is all part of innovation! Not included above but deserve a mention with regards to innovation and deployments to Brokk and Seabotix robotic systems that are often used daily.To really get consistent robotic platform deployments in nuclear decommissioning, further innovation improving the capabilities of robotic platforms is required as well as upskilling of the workforce and events showcasing the technology to industry. Communication is key and the continued development of systems by all the engineers out there.<hr>This article is part of a series about the usage of robots in harsh environments, written by post-doctoral robotics researcher Matthew Nancekievill. Find the second article, on subsea environments,&nbsp;here.

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