Automotive Camera Market’s Opportunities and Challenges

Posted on 2019-10-09 by MarketsandMarkets in Automotive, Industrial, Technology // 0 Comments

CITY, Country, 2019-Oct-09 — /EPR Network/ —

The Automotive Camera Market is estimated to be USD 8.2 billion in 2019 and is projected to reach USD 15.1 billion by 2025, at a CAGR of 10.8% during the forecast period.

High growth potential of multi camera systems in emerging markets

The multi camera systems are primarily associated with high-end passenger vehicles during their introductory phase. Nowadays, in North America and Europe, owing to increasing safety standards and government mandates, OEMs have started providing cameras for park assist and ADAS in their economy and mid-priced segments as well. However, in countries like China, India, Brazil, Russia, and South Africa, OEMs offer camera-based driver assistance system as a standard fit in their luxury and premium segments as they are part of a cost-driven market. In recent years, the demand for premium segment vehicles equipped with ADAS features has witnessed a rise in the emerging pockets of the Automotive Camera Market. Furthermore, owing to the increase in safety awareness, customers who are buying these premium vehicles are ready to spend on advanced safety features. This, in turn, is fueling the demand for multi camera systems. Hence, the steady increase in penetration of high-end vehicles in the emerging markets may provide growth potential for the multi camera system market.

Also, ADAS features are expected to find a place in the economy and mid-priced vehicles because of the adoption of economies of scale by vehicle manufacturers leading to lowered prices. Moreover, the addition of premium applications such as multi camera systems to basic car models is increasingly cantered on enabling better visibility and safety and proving to be a better economic proposition for OEMs as well. Due to these factors, the Automotive Camera Market is anticipated to grow in the coming years.

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Constraints in real-time image processing in surround view systems

The architecture of multi camera systems is based on integrated digital signal processing (DSP) units. This architecture operates in a particular order set by the programmed algorithm. The DSP-based multi camera system has major difficulty in extracting various views from inputs of multiple cameras and display it in real time in a short period. For instance, in May 2018, Uber’s autonomous cars with surround view cameras were not able to take corrective action when a pedestrian came in the way of the vehicle, which led to an accident. To reduce such incidents in the future, camera and other active systems should be more accurate and provide real-time results. Also, gathering data from different cameras and translating it into a single image involves a significant risk of deteriorating the quality of rest of the image, thereby creating barriers for real-time streaming of video. In addition to this, to present a uniform color combination and brightness effect for surround view image, the architecture for camera control is needed. As the display sizes are increasing, the need for high resolution cameras is also increasing as larger displays highlight poor video quality. The use of these high-resolution cameras also creates a challenge for real time image processing. This will serve as a challenge for the Automotive Camera Market

The road to autonomous vehicles

The automotive industry is witnessing a transition with the inception of advanced technological features. This transition involves multiple stages in which the level of automated driving is gradually increasing. Thus, semi-autonomous vehicles are equipped with features that need a certain amount of human interference. These features include lane departure warning (LDW), blind spot detection (BSD), cross traffic alerts (CTA), adaptive cruise control (ACC), autonomous emergency braking (AEB), parking assistance (PA), and surround view system. The vehicles equipped with such advanced features are categorized as semi-autonomous vehicles. The major vehicle manufacturers are focusing on integrating such features in vehicles to improve safety and luxury. Automotive cameras can be used for all these applications. The number of cameras is increasing as the number of driving assistance features is increasing in vehicles. According to primary respondents, camera technology in an average car will increase to more than two cameras by 2023. Hence, the increasing use of these semi-autonomous functions creates a huge opportunity for the Automotive Camera Market.

Modern vehicles are just at their initial stage of the autonomous vehicle era. The autonomous cars require a variety of sensors including camera, radar, and LiDAR, among others, which sense the environment around the vehicle. The average number of cameras in a vehicle is likely to increase with the increase in the level of autonomy. According to NXP, vehicles with level 3 autonomy will use 3–6 cameras along with other sensors. Also, nowadays, cars are equipped with the multi camera system that detects the surrounding of the vehicle. These cameras are helpful to gather a huge amount of data to implement the machine learning algorithms in the computer system of vehicles. With the help of AI, cognitive computing, and predictive analysis, OEMs and automotive Tier I suppliers along with non-automotive players are going to make autonomous vehicles a possibility. Thus, camera systems that can provide several advanced features have a lucrative market owing to the growing trend of autonomous and semi-autonomous vehicles.

As the level of autonomy is increasing, the involvement of the driver is decreasing, and the dependency on cameras and sensors is increasing drastically.

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Key Players:

The key players in the Automotive Camera Market are Continental (Germany), Robert Bosch (Germany), Valeo (France), Aptiv (Ireland), Magna (Canada), Autoliv (Sweden), Ficosa (Spain), Intel (Mobileye) (US), and Clarion (Japan).

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