Automotive Embedded Systems Market: Autonomous Cars to pilot Growth Prospects

In 1968, Volkswagen used the first embedded system in its Volkswagen 1600 to control its electronic fuel injection system. An embedded system is a computer or electronic system designed to access and control data in electronics-based systems. In automotive, embedded systems control engine management systems. According to Inkwood Research, the global automotive embedded systems market is estimated to project a CAGR of 5.44% during the forecast period, 2022-2030.

Embedded systems play a central role in automobiles due to their versatility and flexibility. The widely used embedded systems in vehicles include anti-lock braking systems, collision controls, navigation systems, in-vehicle entertainment systems, telematics, airbags, traction controls, etc. As a result, they are said to facilitate a comfortable, efficient, and safe automobile experience.

As per our evaluation, software is the fastest-growing embedded type in the market, set to register a CAGR of 6.31% by 2030.

Automotive Embedded Systems Market: Autonomous Cars to Steer Growth

Intelligence, analysis, and automation have moved beyond human-centric to machine-specific applications. Accordingly, the automotive industry is headed toward connected and autonomous cars. The primary factor propelling this transition is the surging recognition of human error in automobile accidents and fatalities. As per a Stanford Law School report, human errors are, in part or fully, responsible for at least 90% of total motor vehicle crashes globally.

As a result, autonomous cars are evaluated to play a central role in accomplishing the automotive industry’s ambitious goals of ‘zero accidents,’ ‘zero congestion,’ and ‘zero emissions.’ The evolution of embedded systems has enabled enhanced qualities and new functionalities in autonomous cars. These include assisting and alerting drivers about imminent accidents, information about traffic conditions, autonomous upgradation and diagnosis, etc.

Further, autonomous cars’ cost-effectiveness, efficiency, and reliability majorly rely on the seamless integration of their computer control, perception unit, and navigation sensors, and subsequently, how well they meet transportation needs. In addition, the cars must integrate their intelligent controls and environmental perception capabilities for optimal path-planning strategies. These strategies must be able to minimize pollution exposure, fuel consumption, and time of travel, and avoid obstacles. Such developments increase the need for advanced embedded systems in autonomous cars.

According to our assessment, commercial vehicles are the fastest-growing vehicle in the global automotive embedded systems market, expected to record a CAGR of 6.64% by 2030.

Accordingly, here are a few technologies used in autonomous cars that address the need for automotive embedded systems:

• Global Positioning System (GPS)

With no human intervention, an autonomous car operates on its own as it moves along different destinations. For this, it needs a global positioning system (GPS). This is because GPS uses at least four satellites to provide positioning information, helping the car know its location, speed, and direction. Also, the increasing accuracy of GPS devices has enabled them to discover the fastest routes and monitor traffic, thereby saving time for passengers.

At the same time, GPS is vulnerable to radio interference and can be blocked by skyscrapers or other environmental factors. Nevertheless, several embedded systems are being developed for navigation, such as automotive inertial measurement systems like gyroscopes and accelerometers to supplement the GPS.

• Digitally-Controlled Braking Systems

Automatic braking systems are vital for automobile safety. As per the Insurance Institute for Highway Safety (IIHS), crash avoidance features can prevent or lessen the impact of around 1.9 million crashes annually. Automatic braking systems, thus, play a central role in crash prevention. This is attributed to their principal use in adaptive cruise control and precrash & collision avoidance systems.

• Radar Systems

Cars with blind spot monitoring systems or adaptive cruise control embedded systems use radars. However, their use in autonomous cars is broad because autonomous cars must have front-facing or rear-facing radar systems to provide information about the surrounding objects. In addition, they alert the driver when objects are too near. For instance, the 24 GHz radar, placed in the rear and front bumpers, is already in use for short and mid-range collision avoidance, blind spot detection, and self-parking. As such, autonomous cars need more advanced radar systems.

• Lane Departure Warning System (LDWS)

The Lane Departure Warning System’s (LDWS) purpose is to avoid sideswipe and run-off-road crashes and supplement lane-keeping. For this purpose, the vehicle must sense the lane and road boundaries and the position of the vehicle in the lane. Accordingly, several methods are being researched for this task performance, image processing, highly accurate GPS and digital maps, and embedded magnetic markers.

For instance, the magnetic markers project a magnetic field that could be detected by the vehicle’s sensors, which gives a path to stay in between the sets of road magnets. Whereas another approach is the integration of the roadway lanes’ highly accurate digital mapping with satellite-positioning accuracies in the order of 0.5m or more.

According to Inkwood Research, sensors and drivers are the largest revenue-generating component in the global market, with a revenue share of 52.30% in 2021.

Next Generation Autonomous Cars: Converging AI and Embedded Systems

The next generation of fully-autonomous cars will need more advanced embedded systems than current ones. The operation of intricate artificial intelligence (AI) software and systems would be a requisite for such vehicles. As a result, the need for a new generation of embedded processors to address the computational and cognitive demands offers growth opportunities for automotive embedded systems.

Besides, AI is already gaining traction with the increasing number of advanced embedded designs. The convergence of AI and embedded systems will substantially improve the image and video recognition. Subsequently, the advancements in embedded technology may aid in developing imaging equipment with more compact designs and greater computing capability. Such developments offer lucrative growth opportunities for the global automotive embedded systems market.

By Akhil Nair