The automotive industry is one of the most technologically advanced and innovative industries, constantly breaking the boundaries of what’s possible. The integration of any new tech innovation in an industry typically begins with the question "Is it really necessary?". When it comes to AI in the automotive industry, the answer is a firm YES.
Innovating how vehicles are designed and produced, not to mention expanding their capabilities, Artificial Intelligence has the potential to provide solutions to both manufacturers and drivers.
In this article, we delve into the profound impact AI has had on the automotive field, exploring the latest software development trends that are reshaping the future of mobility. Let's discover together the incredible possibilities and challenges that AI brings to the world of automotive software development.
AI’s role in the automotive industry and its applications
AI technologies are being integrated into vehicles and automotive systems to enhance safety, efficiency, convenience, and the overall driving experience. AI in the Automotive sector covers many areas, from advanced driver assistance systems to sophisticated systems that can predict engine failure and optimize battery performance based on how drivers use the car.
The use of AI in the automotive industry is diverse. From design and manufacturing to sales and customer service, the applications of AI can be noticed throughout the life cycle of a vehicle. It is why top-level automotive brands strive to incorporate AI into their vehicles and in their production processes.
For instance, Tesla is using AI algorithms in its battery management systems to predict the energy requirements of the car based on driving conditions, such as speed and weather, and also driver behavior, such as acceleration and braking patterns.
Another automotive industry giant, BMW, is using AI to make car assembly more efficient. Also, AI has been available in many models since the end of 2018. Implemented in the Intelligent Personal Assistant, AI makes it easier and smarter for the driver to operate the vehicle.
Another great example is Waymo. Waymo’s dream is a future where there are minimal accidents caused by distracted, careless, or impaired human drivers and minimal traffic - a world where it is easier to move. Waymo produces autonomous vehicles that utilize computer vision techniques and Artificial Intelligence to perceive the surrounding environment and make real-time decisions about how the vehicle should move. The company has also developed a Simulation City system for testing its autonomous vehicles and bracing them for the real world.
To explore how AI is shaping the automotive industry, we’ve carefully selected the most popular areas of the industry where AI is used. Let’s explore some of the main AI use cases in the automotive industry:
AI’s role in improving vehicle safety and security
The integration of AI technologies in vehicles has led to significant advancements that enhance overall safety, reduce accidents, and protect occupants and pedestrians. When in the car, AI can help drivers remain more focused by reducing distractions, understanding driving habits, and improving the overall driving experience. Below are some key ways AI contributes to improving vehicle safety and security:
Advanced driver assistance systems (ADAS)
AI-powered ADAS technologies, such as adaptive cruise control, lane-keeping assist, automatic emergency braking, and blind-spot monitoring, help drivers avoid potential hazards and maintain safe driving behavior. These systems use sensors and AI algorithms to detect potential hazards and provide timely warnings or interventions to prevent accidents. The role of ADAS is to prevent deaths and injuries by reducing the number of car accidents and the serious impact of those that cannot be avoided.
Vehicle-to-Everything (V2X) communication
AI technologies facilitate communication between vehicles (V2V), infrastructure (V2I), pedestrians, and other road users (V2P). This allows vehicles to exchange real-time information, such as location, speed, and trajectory, leading to better decision-making and improved safety on the road.
Human errors are the cause of most road accidents. AI algorithms can recognize pedestrians and cyclists near the vehicle, even in challenging conditions. By alerting the driver or activating the vehicle's safety systems, AI helps avoid accidents involving road users.
Tiredness and distraction monitoring
AI can monitor the driver's behavior and identify signs of drowsiness or distraction. When detected, the system can issue sound alerts to the driver to regain focus on the road or even trigger interventions like adjusting the vehicle's settings to maintain a safe driving state.
Overall, AI plays a crucial role in enhancing vehicle safety by enabling faster and more accurate decision-making, continuous monitoring of the vehicle's surroundings, and proactive measures to prevent accidents. By incorporating AI into vehicles, carmakers continue to refine and expand safety and security measures, making our roads safer for everyone.
Enhancing customer service through AI
As digital modernization leads to smarter vehicles, carmakers are forced to use advanced technologies to keep up with customer needs. Today's consumers expect powerful digital experiences. So, it is no wonder why global automotive brands tend to bring car shopping and ownership experiences online.
Leading retail brands, especially high-end ones, are leveraging AI-based new technologies to help them provide high-touch customer experiences with cost efficiency. Also, many car buyers prefer sales and services that do not require physical contact.
AI-powered chatbots that provide immediate responses can handle complex customer queries. Stronger AI implementation will not only increase efficiency but also allow customers to enjoy a more customized service. Furthermore, AI enables dealerships to present their inventory online in a captivating way. The clients are getting the privilege to preview the cars from the comfort of their homes. Virtual showrooms created with metaverse technology provide customers with a fun and interactive way to shop for cars.
Therefore, if you find your dream car and it’s a thousand miles away from you, it's no longer a problem. You can easily preview your future driving experience using innovative AI technologies.
With virtual test drives and the ability to customize features, users get a unique shopping experience that's both enjoyable and convenient. This gives the buyers a real picture of what they are getting and helps them make a purchase decision before contacting the dealership. Of course, offering this service will enhance the overall customer experience.
AI’s role in supply chain optimization
From connected cars and autonomous driving to safety and mobility, it’s safe to say that AI is no stranger to the world of Automotive. While the previously mentioned enhance the driver's experience, what about the ones who stay behind the scenes, the manufacturers?
The new key to the success of any car manufacturer is based on the use of Artificial Intelligence throughout the supply chain process. Because supply chains come with various costs such as warehousing, transportation, server management, and working hours, mismanaging them can lead to cost increases, delays, and unhappy customers in the end. Poor supply chain management can also hinder quality control efforts, leading to more returns and disappointed customers.
AI-powered supply chains have the flexibility to adapt and respond to changes in product demand or unforeseen events, incorporating near-real-time data on advertising campaigns and prices. Moreover, AI systems will allow fully automated, complex supply-chain management decisions to be made autonomously, adjusting routes in terms of costs and volumes to meet changing demand.
Have you ever thought about how many parts your car has? According to GetJerry, an average passenger car has roughly 30.000 different parts. Imagine that these parts are usually sourced and ordered from hundreds of suppliers in different countries.
There’s an incredible volume of data created by modern manufacturing equipment. Therefore, by leveraging AI-based technologies, carmakers can eliminate guesswork and make data-driven decisions. Some of the core areas where AI can add valuable benefits to the supply chain are efficiently optimizing inventory management, part and product buying, and pricing optimization.
AI in the manufacturing process
AI is not only changing the vehicles that are built but also the way they are built. Many robots and machines are already available in automotive factories. Also, at many steps of the manufacturing process, AI delivers incredible results based on its capacity to understand the environment, analyze data, and learn from experiences. AI improves and optimizes vehicle manufacturing processes in many ways. Preventing unexpected equipment failure and lowering maintenance costs is one of them. AI-based algorithms are used in automotive factories to detect anomalies in equipment functions, diagnose the machine’s condition, and plan maintenance.
Likewise, the productivity of employees is increasing due to robot-human collaboration. Robots perform tasks like painting, welding, and assembly. Robotics and Automation have significantly improved efficiency, product quality, and safety in automotive manufacturing.
Robots are used to perform tasks such as inspecting parts, moving materials, and spraying paint onto cars. Due to this fact, people can focus on completing more specialized tasks. Also, a big advantage for carmakers is that robots can work nonstop without tiring or losing focus. That is why industrial robots are often left working on a 24/7 basis. And the most important thing is that they can perform repetitive tasks with high precision and few or no errors.
Another advantage of using AI in car manufacturing is the reduction of quality problems. AI-based systems are a powerful tool in quality control because they constantly learn to improve based on feedback. AI systems can visually inspect the vehicle in the production stage and detect potential issues.
AI-based machines can identify vehicle defects up to 90 percent more precisely than humans. Moreover, insights gathered from AI-based quality testing can also be used to analyze the root causes of defects and improve overall production processes in the factory.
A widespread concern among people is: will robots completely replace human work? The answer is NO. Every robot needs to be controlled periodically and maintained if necessary. They also must be designed, installed, and improved; therefore, some types of human work will remain irreplaceable.
AI-driven quality control and predictive maintenance
The combination of AI-driven quality control and vehicle predictive maintenance can significantly enhance vehicles' overall performance while reducing downtime and repair costs for vehicle owners and manufacturers alike. Without a doubt, quality control is very complicated, especially in the automotive field. Limited working hours, a lack of expertise, and multiple failures can be causes of delays or inefficient manual quality control.
In contrast, an AI-based system can be trained to analyze common defects and classify manufacturing failure types and patterns. It identifies the wrong aspects of production and forecasts failure. AI algorithms can analyze images and videos from cameras installed on production lines to detect defects and anomalies in real time. This allows manufacturers to identify potential issues early in the production process and take corrective actions promptly. The giant Audi, for instance, is already using AI for more efficient, targeted quality control.
Also, to help drivers, an AI-based system can be used to enable predictive maintenance. The system continuously analyzes the condition of connected parts and the entire vehicle. It can collect multiple types of data to build detailed models that reflect the vehicle's real-time status and how that is being used. AI can detect anomalies in sensor data, helping to identify deviations from normal operating conditions that might indicate impending issues.
Predictive maintenance is an approach that uses AI and machine learning to anticipate when a vehicle component is likely to fail and schedule maintenance before the failure occurs. The proactive approach with AI helps optimize the maintenance schedule and improve vehicle reliability.
Smart cities and smart transportation with AI
Every day, cities are getting smarter. Transportation will become smarter and safer as technology continues to evolve. By integrating AI into various aspects of urban planning, infrastructure, and transportation systems, cities can address challenges related to traffic congestion, pollution, energy consumption, and the overall quality of life for their residents.
Smart cities will also be using AI to improve public safety. The future of smart cities will use AI-powered cameras and sensors that can detect suspicious activity and alert authorities in real time. AI-powered facial recognition systems could also be used to identify criminals and potential threats to public security.
With the integration of aerial transportation and autonomous vehicles in future smart cities, traffic management will expand to include vertical dimensions, coordinating ground and air traffic to prevent conflicts and improve overall efficiency. Here, AI will be a great help.
Using AI-based systems can help analyze real-time data from various sources, such as smart traffic cameras, GPS devices, and cars, to optimize traffic flow and reduce congestion. Smart traffic lights can adapt their timing based on current traffic conditions, leading to smoother traffic movement and reduced travel times.
Vehicles and transportation infrastructure will be more connected, enabling real-time data sharing between vehicles, traffic lights, and other elements of the transportation ecosystem. Cooperative systems will allow vehicles to communicate with each other to optimize traffic flow and enhance safety.
To implement these innovations, a complex infrastructure is necessary. Therefore, the future of smart cities will be based on technology-driven solutions. For instance, AI-based systems will help identify the areas that need repairs before an infrastructure failure happens. They can use the collected data to improve processes and focus manual work where it's needed most. Smart transportation and smart city traffic management are revolutionizing how cities approach mobility while reducing traffic congestion. How? With sensors, advanced AI technologies, and high-speed networks.
As intelligent transportation systems for smart cities grow in use around the world, people can begin to collect the many safety, efficiency, and cost benefits that come with modern smart transport.
Oneest’s experience in Automotive software development
One of our clients, Globcom, a company from the Automotive Industry with headquarters in the Republic of Moldova, provides worldwide vehicle testing and legally valid data sensor validation with 15 years of professional experience. The main challenge for our client was managing Human Resources, and they needed to streamline and automate business processes, reduce operational costs, and scale the business.
The solution that we developed is an ERP software that makes management processes easier, more accessible, and clearer. The ERP system helps our client centralize data about everything that's happening in the firm and for all employees and projects.
In addition, employees provide daily reports on working hours, based on which payroll reports are generated and performance indicators are measured. Thanks to ERP statistics, the company board can quickly make decisions to develop and optimize resources.
The most important results that our client received were:
- Positive ROI in 12 months;
- A newly signed contract with The Largest Automotive Group in Europe;
- Reducing operational staff saves about $50.000 a year.
The role of AI in the Automotive Industry is undeniably transformative, pushing the sector towards greater automation, efficiency, and safety. As technology continues to advance, we can expect AI to drive new breakthroughs, ultimately shaping smarter cities and more connected transportation for years to come.
By 2033, AI in the automotive market is expected to grow by 55%. At the same time, the market value will grow to $744.39 billion. These numbers look incredible, right? AI has proven itself to be the transformational technology of the future. Therefore, a strong demand that will continue to grow is expected in the future, leading to exciting advancements and improvements in the vehicles and services available to consumers.
Throughout this article, we have explored the various applications of AI, shaping the present and future of automotive software development. Embracing and adapting to these emerging trends will be very important for automotive companies to stay competitive and provide cutting-edge solutions to meet the demands of clients in the dynamic Automotive Market.
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