In the automotive industry, from allowing autonomous vehicles to transforming research, design, and development processes, artificial intelligence is one of the latest keys to success.
Artificial intelligence has an enormous influence on various production and manufacturing sectors, along with aviation, manufacturing, technology, and others. Higher productivity is achieved because of the features of artificial intelligence such as machine learning and deep learning in the automotive sector.
Artificial intelligence (AI) in the automotive industry is expected to cause a profound disruption by streamlining production capabilities and augmenting business growth. The design and deployment of novel technologies, including autonomous mobility, automotive simulations, rapid prototyping, and AI-enabled car factories, creates an ambitious outlook for the autonomous technology industry.
In particular, research into the development of smart vehicle technology focuses on various issues regarding the environment, infrastructure, pedestrians, and other objects that could be some of the obstacles to smart vehicles.
Artificial intelligence (AI) has applications in the automotive life cycle, from the design and development process through to testing and manufacturing to marketing. Powerful information sources are the data produced by the many sensors now installed in cars, collected from production lines, and compiled from customer feedback. Their study and interpretation provide equally powerful levers for progress in design, testing as well as understanding consumer needs and expectations.
The most anticipated feature of artificial intelligence in the automotive industry is that of autonomous cars. In the automotive industry, manufacturers and their technology partners are working overtime to develop artificial intelligence-driven systems to enable self-driving cars. These systems incorporate a wide range of artificial intelligence-enabled technologies such as deep learning neural networks, natural language processing, and gesture-control features to provide brains for vehicles that can safely drive themselves, with or without a human driver on board. Some of the leading innovators in the field have been Google and Tesla, and companies such as Uber or Waymo are working on implementing self-driving cars.
For instance, in October 2018, Waymo subsidiary of Alphabet, which is a parent company of Google, launched an autonomous taxi service in Arizona, U.S. Waymo’s AI software crunches data from the vehicles’ Lidar, radar, high-resolution cameras, GPS, and cloud services to produce control signals that operate the vehicle. Powerful AI deep-learning algorithms can accurately predict what objects in the vehicle’s travel path are likely to do.
In October 2015, Tesla launched ‘Autopilot Driver Assistance System’ with autopilot capability for their model S car. In the electric car market, Tesla succeeded in becoming a well-known name. The company is continuously updating its software to improve the self-driving capability and the safety of the passengers. In addition, the company has also built in-house AI chips in order to boost the car's performance and safety. Eight cameras, an array of ultrasonic sensors, sonar, forward-facing radar, and GPS are almost similar to Waymo and Google's data, all of which are fed into an AI program that transforms sensory data into vehicle control data. The Autopilot program from Tesla goes beyond driving the vehicle where you tell it to go. Autopilot will check the calendar and drive you to your scheduled appointment if you are not in the mood for talking. For autonomous driving, every new Tesla comes completely equipped. Regulatory approval is all that is required so that the company can activate the program, placing AI in the driver's seat.
Artificial intelligence is not only changing what a vehicle can do, it is also changing how vehicles are built. Automakers can use AI-driven systems and electronic logging devices to create schedules and manage workflows, enable robots to work safely alongside humans on factory floors and assembly lines, and identify defects in components going into cars. These capabilities can help manufacturers reduce costs and downtime in production lines while delivering better-finished products to consumers.
Automated guided vehicles (AVGs) are used without human intervention to move products in automotive plants. AI helps these autonomous delivery vehicles to locate products and change their route accordingly. AI empowers them to detect material defects and to change or alert quality control staff accordingly.
For instance, for industrial automation, Rethink Robotics located at Boston makes co-bots or collaborative robots. Such robots are used to automate factory activities that are boring, dirty or even dangerous, for human employees.
In October 2018, Hyundai introduced an artificial intelligence-based robot named ‘Hyundai Chairless Exoskeleton (H-CEX). The company developed wearable robots, service robots, and micro-mobility robots.
In 2016, OTTO Motors introduced an intelligent material transport vehicle for manufacturing units. This vehicle is AI-driven, which navigates autonomously around a manufacturing unit. According to OTTO Motors, in 2018, it launched the self-driving vehicle for material handling with a payload of 750 kg. It also improved the production capacity of the manufacturing plant with reduced accidents.
The adoption of AI hardware will see a rapid increase in order to allow self-driving technologies and improve AI algorithms through dedicated AI-enabled GPUs. In providing accurate navigation and background awareness to onboard AI systems, the growth of the hardware segment is amplified by the importance of perception sensors, including high-resolution cameras, Lidar, and radar.
Furthermore, AI-optimized processors and computer hardware development will allow businesses to design and deploy enhanced autonomous solutions.
For instance, in September 2019, Horizon Robotics, a leading AI computing company, introduced its 2nd generation automotive AI processor – Horizon Journey 2. This latest solution allows car manufacturers to integrate advanced driving assistance system (ADAS) technologies of the next generation and smart cockpit experiences with low power consumption and high performance.
In March 2019, BMW and Daimler entered into a strategic collaboration to develop new advanced driving assistance system (ADAS) solutions and establish industry standards to influence future regulations on driver assistance technologies.
Many prominent AI players are focusing on improving their R&D capabilities and forming strategic alliances with other leading companies to accelerate the period of technology growth.
For instance, in June 2019, Audi entered into a partnership with Alibaba AI Labs in conjunction with Honda and Renault to collaboratively focus on the R&D of AI and voice technology. The partnership helped the company incorporate Tmall Genie Auto technology into its vehicles, helping drivers monitor their vehicles through voice commands, and providing drivers with an intelligent linked ecosystem.
Artificial intelligence in the automotive industry such as image recognition is expected to hold a dominant position in artificial intelligence in the automotive market due to the increasing deployment of traffic sign recognition software in autonomous vehicles. By detecting speed limit signs and automatically reducing vehicle speed as per the regulation, this program ensures that vehicles live up to speed limits. Moreover, traffic signals such as lane shifts and stop-go signs can also be identified by the recognition program to navigate the vehicle correctly in dense traffic conditions. The introduction of image/signal recognition solutions would drastically enhance road safety with the rising rate of road accidents caused by over-speeding.
For instance, in March 2019, the European Commission (EC) made traffic sign recognition mandatory for all vehicles manufactured from 2022 to ensure smooth traffic flow and minimize over-speeding accidents.
For instance, nuTonomy's technology, nuCore allows vehicles to navigate even the most complex traffic situations. NuTonomy partnered with Lyft to test vehicles in Boston's Seaport District, providing rides to Lyft users and gaining more traction towards transforming the way people ride.
Artificial intelligence in the automotive industry is also used for predictive maintenance. Hundreds of sensors are monitored by AI and can detect issues before it affects the performance of vehicles. By monitoring thousands of data points per second, AI can spot component failures way before it actually happens. AI-powered cloud-connected automotive software not only gathers real-time data but also maintains it for analytics and statistics. AI can recognize behaviors that hinder the efficiency of a car or evaluate the possible malfunction scenario and avoid it in accordance with permanent access to real-time alerts that are captured every single second. The greatest part is that AI does not complicate the user experience at all in your car apps.
For instance, in 2017, Predii, an AI software company based in Palo Alto, introduced Predii Repair Intelligence, an innovative machine learning platform, for part replacement and repairs in the automotive industry. This software uses data such as service orders, IoT data, and technical manuals for the repair and maintenance of vehicles.
With artificial intelligence, the manufacturing process could be reinvented to such an extent that human beings are no longer needed, at least not to carry out the same jobs. Eventually, automation and artificial intelligence processes will replace the need for low-skilled jobs, which, of course, has the potential to have a short-term negative effect on the labor force. The intention is to re-train certain employees for higher-level roles in the long term.
Artificial intelligence can certainly change the automotive industry. Artificial intelligence will improve the performance, safety, and productivity of automotive vehicles, and some cars will soon have their own Wi-Fi hotspots and will provide internet connectivity to the customers.
For car manufacturers, the wise move is to start embracing the leverage of artificial intelligence technology to boost their day-to-day operations, future opportunities, and overall performance.
