The ADAS Market ( advanced driver assistance system) is estimated to be USD 30.0 billion in 2019 and is projected to reach USD 134.9 billion by 2027, at a CAGR of 20.7%.
This technology improves the driving experience while enhancing vehicle and pedestrian safety. It is becoming an integral part of modern automobiles and is now adopted in passenger cars as well as commercial vehicles which are driving the growth of this market. The rising disposable income levels, increased vehicle production in developing countries such as India and China, and increase in the number of luxury vehicles in countries such as Japan are expected to fuel the growth of this market in the Asia Pacific region.
Road Sign Recognition segment is estimated to be the fastest-growing market during the forecast period
The road sign recognition uses image sensors to recognize the traffic signs such as, “turn ahead,” “speed limit zones,’’ and “no-overtaking,” on the road. The technology was adopted by many automobile manufacturers, such as Volvo, Audi, BMW, Mercedes-Benz, Opel, and Volkswagen. The European road sign recognition market is estimated to be the fastest-growing market, by value, due to the increase in road infrastructure development activities in the region.
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Radar sensor is the fastest-growing segment of the ADAS market, by component
The increased traffic congestion, roadways infrastructure, and government regulations for vehicle safety will drive the growth of various radar-based ADAS applications. The rising trend of autonomous and semi-autonomous vehicles in the automobile industry is projected to be another major driver for the global automotive radar market. The increased traffic congestion, infrastructure roadways, government regulations for vehicle safety, and adoption of automotive radar-based ADAS technology by OEMs has eventually created opportunities for various radar-based ADAS applications.
Hybrid Electric Vehicle (HEV) to acquire the largest share of the ADAS market, by electric vehicle type
HEV is estimated to hold the largest share of the ADAS market, by electric vehicle. Stringent emission norms, environment safety, vehicle electrification, and government regulations are expected to boost the market for ADAS in HEV segment. ADAS is installed in HEVs for increasing passenger safety and also mitigate imminent accidents. Hence, an increase in demand for safer, efficient, and convenient driving experience will propel the demand for ADAS.
Hyundai Ioniq and Toyota Prius are the top-selling hybrid cars. Hyundai Ioniq is fitted with ADAS features such as adaptive cruise control, automatic emergency braking, and lane departure warning. Toyota Prius is equipped with ADAS as a pedestrian detection system, adaptive front light, collision avoidance system, adaptive cruise control, intelligent park assists, and lane departure warning.
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• In May 2019, Mitsubishi Electric Corporation and HERE Technologies have successfully piloted a system which enables vehicles to automatically warn about upcoming road hazards with lane-level precision. This technology was successfully tested in the US.
• In April 2018, Robert Bosch developed a highway assist system to help drivers keep their vehicle in the lane in order to mitigate an accident. The new Bosch highway assist system is installed on the 2018 Maserati Ghibli, Levante, and Quattroporte.
• In April 2018, Continental developed new concepts designed to warn drivers about an imminent risk of aquaplaning. Aquaplaning assistance concepts utilize surround-view camera images and signals from tire-mounted sensors (eTIS) for advanced tire information.
• In January 2018, ZF Friedrichshafen expanded its manufacturing and engineering footprint in Poland to produce products including an advanced camera for driver-assist systems. The 10,000-square-meter manufacturing facility will be fully operational by the end of 2019. The expansion would add more than 300 jobs.
• In January 2018, Continental opened Center for Deep Machine Learning in Budapest, Romania. The company’s advanced driver assistance systems business unit is using machine learning and neural networks for developing high-performance driver assistance system.