According to the research report published by Research Cosmos, the size of the self-driving car market anticipated to reach $155.69 billion by the end of 2024, witnessing a CAGR (compound annual growth rate) of 50.9% from 2018 to 2024. Among the key market trends are:

Advancement in HMI (human-machine interface): One of the most promising trends for the self-driving car market is the application of advanced HMI technologies in vehicular systems. HMI technologies are based on natural language processing (NLP) and computer vision (CV) that allow machines to interact with humans, both in verbal and nonverbal languages. Recent applications are self-parking systems by Mercedes-Benz and BMW’s iDrive Controller with touchscreen controller and gesture recognition. Other applications include HUD (head-up displays) that help drivers to focus on the road and use of imaging devices such as Texas Instruments’ DLP (digital light processing) chips to project high-contrast images.

V2V and V2I enhances interactions with surroundings: An autonomous vehicle will not only communicate with the driver but also with its surroundings using vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) technologies. V2V technology is being developed progressively to allow vehicles on the road to “talk to each other” by sharing data about speed, road conditions, and other attributes through ad-hoc networks created among vehicles. It has great potential in enhancing car safety by avoiding crashes, easing traffic congestions, and improving overall road safety conditions. Similarly, V2I shares safety and operational data between vehicles and the transportation infrastructure. The technology, though in a nascent stage, is already in use. Recently, Audi deployed a V2I network in Las Vegas to check waiting time at traffic signals and BMW released a mobile app called EnLighten to perform similar functions.

Investments will focus on scalability and service enhancements: There are multiple ongoing investments in the autonomous car sector by technology companies, driven by its excellent future prospects. SoftBank is planning to invest a $2.25 billion in Cruise, the autonomous vehicle arm of General Motors. Similar investments in the technology are forthcoming from the likes of leading firms such as Tesla, Uber, and Waymo. Waymo, Alphabet’s self-drive division, is focusing on launching autonomous ride-hailing services. The company has also invested in LiDAR technology to increase production scalability.

Predictive maintenance enabled by vide telematics: Predictive maintenance uses data from the vehicle and its surroundings to help the driver make decisions while driving. This can help in controlling fuel consumption, increasing driver safety, and reducing maintenance and repair costs. The predictive analytics models are developed based on factors such as driving behavior, condition of cars, and road infrastructure. These models can be more accurately developed using video telematics. Currently, video telematics features installed in cars provide real-time video data, which is analyzed to provide more accurate predictions.

North America to lead the global market: The contribution of North American Self-Driving Cars Market towards autonomous vehicles has been boosted by the presence of different technology hubs along the West Coast of the U.S. Uber and Tesla are companies that have made headlines for both successes and failures. The U.S. has been leading the pack in its bid to get fully autonomous vehicles on the road as soon as possible.

Major self-driving car providers operating in the market are divided: Two groups, technology providers (Microsoft, Apple, IBM and Cisco) and automobile industry players (Waymo, Toyota, General Motors, Tesla, Volvo, and Nissan) are leading the charge. With an increase in disposable income, urbanization, and improved infrastructure, consumer preferences towards automotive features have changed. Rising disposable income enables individuals to afford additional features in their cars. Smart components of semi-autonomous cars, such as adaptive lighting controls and pedestrian and blind-spot detection, have gained priority, along with other aesthetic features. According to the KPMG Global Automotive Executive Survey 2017, 45% of automotive company executives feel that driver-assistance systems are key purchasing criteria. The increased use of these features will also drive the market for self-driving cars, since driving assistance is a precursor to fully autonomous cars.