{"id":13393,"date":"2019-01-23T14:06:59","date_gmt":"2019-01-23T13:06:59","guid":{"rendered":"https:\/\/www.intellias.com\/?p=13393"},"modified":"2023-08-21T08:30:56","modified_gmt":"2023-08-21T06:30:56","slug":"how-to-build-adas-technology-for-autonomous-driving","status":"publish","type":"blog","link":"https:\/\/intellias.com\/how-to-build-adas-technology-for-autonomous-driving\/","title":{"rendered":"How to Build Advanced Driver Assistance Systems (ADAS) for Autonomous Vehicles"},"content":{"rendered":"
Innovation takes time. We won\u2019t see fully autonomous vehicles congesting the urban streets any time soon. But OEMs and Tier 1 providers are actively exploring certain core self-driving<\/a>\u00a0car technologies. ADAS technologies are the decisive piece of the puzzle. It’s critical for the safety, comfort, and ease of driving. And ADAS technology’s value will only continue to rise as autonomous cars approach the city streets.<\/p>\n Let\u2019s find out how ADAS technologies gets us closer to a fully automated future.<\/p>\n <\/p>\n So what is ADAS in automotive? The need to address safety issues on the road has crystallized into concrete government regulations. Official policies oblige OEMs and Tier 1 suppliers to use ADAS components like rearview cameras in all new vehicles under 10,000 pounds (4,500 kilograms) and include autonomous emergency braking (AEB) systems in buses and trucks. These and similar regulations have become the biggest motivators for automakers to pursue ADAS opportunities<\/a>.<\/p>\n Quick takeaways from global ADAS components market developments between 2018\u20132022<\/strong><\/p>\n <\/p>\n Source: Technavio\u2019s report on the Global Automotive Advanced Driver Assistance System Market<\/a><\/em><\/p>\n The combination of increasing computing power, improved sensor technologies, and better software solutions can help automotive companies beat off the intense competition. No wonder ADAS technology is the fastest-growing segment in the automotive ADAS market.<\/p>\n Consumers love the comfort and safety provided by parking assist, blind zone monitoring, and other advanced systems. And they love safety ratings, of course. Authorities around the world are fighting for safety improvements<\/a> and fewer road fatalities. The development of advanced driver assistance systems is governed by international safety standards including IEC-61508 and its derivative, ISO\u202f26262<\/a>.<\/p>\n Historical data suggests that ADAS safety systems reduce traffic fatalities.<\/p>\n <\/p>\n Source: EE Times, Automotive King Redefines Future<\/a><\/em><\/p>\n OEMs respond to market demand and regulatory requirements, working toward full driving automation. You can be sure that we\u2019ll soon see an increasing number of ADAS in\u00a0automotive that help with monitoring, warning, braking, and steering.<\/p>\n The ultimate goal of ADAS feature development is to make our roads safer and better suited for fully autonomous vehicles in the long run. Still, manufacturers and buyers shouldn\u2019t underestimate the importance of ADAS for meeting current automotive challenges. The most significant impact of advanced driver assistance systems is in providing drivers with essential information and automating difficult and repetitive tasks. This increases safety for everyone on the road.<\/p>\n Below, you\u2019ll find an infographic showing principal ADAS features and their uses. It also shows the critical components behind each solution.<\/p>\n Principal ADAS features<\/strong><\/p>\n <\/p>\n Source: Electronic Specifier, What is driving the automotive LiDAR and RADAR market?<\/a><\/em><\/p>\n The chart below shows the value of each component within the ADAS solutions market, which is broken down into the following categories:<\/p>\n The size of the ADAS market in the US by solution type, 2014\u20132025 (USD billion)<\/strong><\/p>\n <\/p>\n Source: Grand View Research, ADAS Market Size, Share & Trend Analysis Report by Solution<\/a><\/em><\/p>\n Find out how Intellias developed ADAS solution for electric vehicles<\/p>\n Applications related to\u00a0self driving car technology\u00a0include various state-of-the-art tools that depend on each other.<\/p>\n Pillars of ADAS in automotive that are key to autonomous driving and product differentiation<\/strong><\/p>\n <\/p>\n Source: McKinsey & Company, Advanced driver-assistance systems: Challenges and opportunities ahead<\/a><\/em><\/p>\n Speaking of what is ADAS in automotive as well as of ADAS feature development and ADAS system architecture, we\u2019d like to single out five components that are worth in-depth discussion: sensors, processors, software algorithms, mapping solutions, and actuators.<\/p>\n These elements can be roughly grouped into three subsystems responsible for:<\/p>\n System-level design for ADAS in automotive<\/strong><\/p>\n <\/p>\n Source: The Embedded Vision Alliance, Complex Trends and Challenges in Designing ADAS<\/a><\/em><\/p>\n ADAS vision systems and ADAS safety systems require lots of fused sensors to monitor the vehicle\u2019s surroundings and what\u2019s going on inside the car. The most commonly used ADAS sensors today are lidar, radar, and ultrasonic.<\/p>\n Software for self driving cars\u00a0featuring ultrasonic sensors usually consists of multiple sensors located in the front and rear bumpers and side-view mirrors. They transmit short sound waves and measure the time it takes for them to travel to a target object and return to the receiver.<\/p>\n Short-range and long-range applications of sensor technology<\/strong><\/p>\n <\/p>\n Source: Electronic Design, Radar and Ultrasonic Sensors Strengthen ADAS Object Detection<\/a><\/em><\/p>\n An ADAS safety system can rely on ultrasonic sensor technology for low-speed and short-range applications such as blind spot detection, self-parking, and parking assistance. Radar and lidar are both used by ADAS engineers for object detection, collision prevention, and interaction with traffic management systems.<\/p>\n Still, there are differences between these technologies. Lidar is the best solution for real-time detection, but it\u2019s unpleasantly expensive for mass deployment. Radar sensors, especially long-range ones, are reliable enough and cheaper but lack precision when detecting small objects.<\/p>\n Cameras pointed in all directions, radar and lidar sensors, and multiple displays gather and present information to drivers. Computing all of this data requires high-performance processors. And the need for processing power will grow with future advanced driver assistance systems software advancements.<\/p>\n The effectiveness of advanced driver assistance systems is measured by the car\u2019s ability to sense, perceive, and react. But without enough processing power, a computer can\u2019t decide how the car should behave in a particular real-time situation on the road. Traditional low-level programming technologies, which require lengthy development and are difficult to maintain, are inappropriate for most ADAS safety systems.<\/p>\n <\/p>\n Modern cars have more than 100 microprocessors and up to 100 million lines of code. So OEMs should choose their processors smartly. The task of seasoned engineers for self driving car technology\u00a0is to build a sophisticated system that will maintain high-speed transfers with increasing amounts of data to analyze the car’s surroundings and act accordingly. Moreover, engineering companies need to tackle the challenge of multicore architectures and high frequencies with low power consumption.<\/p>\n Autonomous Driving & ADAS Software Development<\/p>\n The ADAS market is growing rapidly, and so is ADAS system architecture algorithm development. A variety of algorithms are powering life-saving systems. Among them, vision and image processing algorithms are real game changers for ADAS feature development.<\/p>\n Visual sensors are the primary type used for driving, which is why computer vision will play a crucial role in autonomous cars. ADAS algorithms use input from cameras and sensors to incorporate environmental elements into self driving car technology. Then the output provided by these algorithms to the actuation system either warns the driver of potential hazards or gives directions to the ADAS in automated driving on how to act.<\/p>\n Lane departure warning and lane detection systems, adaptive cruise control, headlight control, autonomous emergency braking, collision warning, pedestrian protection \u2013 these are just some of the advanced driver assistance systems software\u00a0developed using vision and image processing.<\/p>\n Autonomous vehicle navigation in urban environments requires higher accuracy than GPS-based systems can offer. Besides, GPS may fail, causing what would be an ordinary situation in a car with a human driver to turn into a life-threatening situation in a self-driving vehicle. That\u2019s why advanced driver assistance systems should ensure greater precision, increased stability within environments with dynamic obstacles, and the ability to learn and improve maps over time.<\/p>\n <\/p>\n Tech startups, established tech providers, and manufacturers are competing and partnering with each other to work out sophisticated mapping algorithms that store and update geographical and infrastructure information. By incorporating these mapping solutions into ADAS vision and ADAS safety systems, location can be pinpointed to centimeters. OEMs can achieve real-time cloud navigation services, environment perception, planning, and decision-making.<\/p>\n Learn how Intellias helped equip German premium cars with the most advanced driver assistance functions on the market.<\/p>\n The actuation system terminates the chain of events controlled by advanced driver assistance systems. It facilitates interactions between a vehicle\u2019s components and takes prompt actions based on computed results.<\/p>\n Through programmed sequences, the actuation ADAS subsystem reacts to the object recognition results, which are processed into commands to control the vehicle. Automatic actuators allow a wide range of operations from visual, acoustic, or haptic warnings to electric power steering, autonomous acceleration, and braking.<\/p>\n Actuation system within ADAS vehicle architecture<\/strong><\/p>\n <\/p>\n Source: Hitachi Automotive Systems Americas, Inc., Advanced Driver Assistance System<\/a><\/em><\/p>\n Advanced driver assistance systems aren\u2019t only connected to autonomous vehicles architecture; they\u2019re also closely interconnected. Vision and camera systems, air conditioning systems, and networks of sensors can no longer be tested in isolation. Only testing of ADAS in automated driving technology in the framework of the entire vehicle will give precise results.<\/p>\n This isn\u2019t the end of the testing challenges, though. There\u2019s one more type of dependency to consider: smart and interconnected external networks such as vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) systems. The high interdependency of internal and external subsystems makes the testing scope enormous. Only experienced ADAS engineers can cope with it.<\/p>\n In recent years, the automotive industry has made huge steps toward autonomous driving. And advanced driver assistance systems lie at the core of these achievements. Although ADAS features haven\u2019t become mainstream yet, the goal of fully automated driving is no longer a fantasy.<\/p>\n OEMs and Tier 1 suppliers may have difficulties with ADAS feature development, considering current and evolving legislation and the necessity to integrate ADAS technology into existing and new vehicle architectures. These are just some of the issues that force automotive players to seek external partnerships.<\/p>\n At Intellias, we\u2019re working on several impressive autonomous driving projects. We\u2019re developing ADAS features and ADAS algorithms and know exactly how to test and implement ADAS in\u00a0automated driving.\u00a0<\/em>Contact us<\/a> to speak with one of our automotive experts.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":" Learn about ADAS technology that can give us the ultimate driving safety and comfort <\/p>\n","protected":false},"author":6,"featured_media":60653,"template":"","class_list":["post-13393","blog","type-blog","status-publish","has-post-thumbnail","hentry","blog-category-automotive-blog","blog-category-autonomous-driving"],"acf":[],"yoast_head":"\nOEMs and Tier 1 vendors should build ADAS technologies to beat the competition and meet safety requirements<\/h2>\n
Building ADAS in automotive has already saved lives, is improving safety today, and will do even more in the future<\/h2>\n
ADAS technology and its uses reflect trends in the automotive industry<\/h2>\n
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Five pillars of ADAS in automotive to ensure safety and connectivity<\/h2>\n
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Sensor technologies are at the forefront of ADAS technology<\/h3>\n
Processors are indispensable for driving automation at any level<\/h3>\n
ADAS algorithms to propel safe and smart driving<\/h3>\n
Mapping in ADAS system architecture sets new standards for in-car navigation<\/h3>\n
Actuators as major enablers of self driving car technology<\/h3>\n
Testing ADAS in automotive helps to ensure vehicle safety and convenience<\/h2>\n
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