By Apurva Agarwal
Most passenger vehicles today incorporate driver assistance technology, which relies on artificial intelligence (AI) to detect if a driver is drowsy or tired by watching their eyes. AI systems also learn a driver’s behavior pattern, including preferred temperature settings, songs and destinations, to make the commute experience convenient and comfortable. Almost all major automotive companies work with software providers to create the ideal interior atmosphere for the driver, leading to an engaging and individualized user experience.
It is therefore no wonder that the automotive artificial intelligence market is expected to grow at a CAGR of 24.1% between 2022 and 2027. MarketsandMarkets values the automotive artificial intelligence market at $2.3 billion in 2022 and predicts it will reach $7.0 billion. by 2027, based on growing adoption of ADAS technology by OEMs and growing demand for improved user experience and convenience features.
Based on the technology, the automotive artificial intelligence market has been segmented into deep learning, machine learning, computer vision, natural language processing (NLP), and context-aware computing. Deep learning is the main technology adopted by companies in human-machine interface (HMI), semi-autonomous and autonomous applications, making it the leading segment of the automotive artificial intelligence market.
Machine learning (ML) – which allows cars to analyze and learn from different driving situations, thereby reducing accidents and making cars safer and more efficient – is expected to hold the second-largest market share in the market. automotive artificial intelligence during the forecast period. ML also creates accurate patterns that can guide future actions and identify patterns at a scale that was not previously feasible. Machine learning has various technologies, namely supervised learning, unsupervised learning, deep learning and reinforcement learning, which are particularly applicable when it comes to feeding a system with new insights into the automotive industry, as data sets are large, diverse and rapidly changing.
The latest developments in automotive AI are delivering in-vehicle payments designed to revolutionize the way customers fuel up, pay for parking or tolls, or shop. Open Banking allows customers to pay for various conveniences directly from their bank account, reducing friction and security risks. Customers can also use Open Banking services to set up wallets and on-board payment systems, providing a seamless customer experience while reducing the need for third-party payment networks. The rapid expansion of in-car payments is also expected to fuel natural language processing and the deployment of voice assistants in automobiles, using AI.
On the other hand, the growing demand for improved user experience and convenient features has led to an increase in the number of electronic systems installed in a vehicle, consequently increasing the cost of the vehicle. Previously, electronic systems accounted for around 1-2% of a vehicle’s total cost, which has risen to almost 8-12%, especially in luxury and high-end cars with advanced technologies. Unfortunately, the demand for luxury and high-end cars is subdued due to their high price, which is likely to restrain the overall market growth.
Another major challenge encountered particularly with driverless automobiles is the effect of weather on sensors, resulting in impaired vision. Driver safety may be at risk as the accuracy of the sensors is greatly influenced by adverse weather conditions. However, technological developments should help overcome this problem, allowing fully autonomous vehicles to operate in all weathers.
Additionally, for self-driving cars to be effective, the infrastructure must support the technology. For example, lane assist technology requires lane lines on the road for the system to detect and adjust the vehicle’s position, increasing the cost of infrastructure development. Additionally, the installation of advanced features such as Blind Spot Detection (BSD), Lane Departure Warning (LDW), Adaptive Cruise Control (ACC) and Forward Collision Warning System (FCWS ) increases the overall cost of the vehicle. Although cost is not a priority area for high-end cars, the demand for small and medium segment cars is affected by the cost of the vehicle, which leads automakers to try to provide effective safety devices at reasonable prices.
As technology develops and matures, AI in the automotive industry will become more capable than ever, enabling vehicles to perform tasks previously considered unachievable. Some of the major players working to change the face of modern cars and the way we perceive them include globally established players such as Nvidia Corporation (US), Alphabet Inc. (US), Intel Corporation (US) , Microsoft Corporation (US), IBM Corporation (US), Qualcomm Inc. (US), Tesla Inc. (US), BMW AG (Germany), Micron Technology (US), and Xilinx Inc. (USA). As we move inexorably towards an increasingly automated future, it will be fascinating to see how consumers benefit from the immense opportunities that artificial intelligence is expected to create in the automotive sector.
The author is Apurva Agarwal, Senior Analyst, Electronics and Semiconductor Research, at MarketsandMarkets
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