Camera-based DMS to be chief enablers of safe, semi-autonomous driving, says research

ABI Research has identified camera-based driver monitoring systems (DMS) as the chief enablers of safe, semi-autonomous driving. The market is forecast to reach 17.5 million camera-based DMS shipments in 2026. Biometric availability encompasses the driver's alertness, his or her engagement with the driving process and even the driver's ability to manually interact with the system as required. The key to enabling such a holistic driver monitoring system (DMS) is the use of internal cameras, either stereos
October 21, 2016 Read time: 2 mins
5725 ABI Research has identified camera-based driver monitoring systems (DMS) as the chief enablers of safe, semi-autonomous driving. The market is forecast to reach 17.5 million camera-based DMS shipments in 2026.

Biometric availability encompasses the driver's alertness, his or her engagement with the driving process and even the driver's ability to manually interact with the system as required. The key to enabling such a holistic driver monitoring system (DMS) is the use of internal cameras, either stereoscopic or time-of-flight, to identify and track facial features, gaze direction, and upper body position. ABI Research identifies a number of vision analytics companies active in this space, including EDGE3 Technologies, FotoNation, Jungo Connectivity and gestigon.

According to James Hodgson, industry analyst at ABI Research, a number of semi-autonomous system launches from OEMs like Mercedes-Benz, Nissan, and Tesla have highlighted the importance of a robust human machine interface, or HMI, in scenarios that require an automated system to work in tandem with a human driver. Leveraging camera-based DMS to provide the host autonomous system with a comprehensive understanding of the driver's biometric availability is the foundation of safe, semi-autonomous HMI.

"In many ways, this represents a new cost burden to OEMs looking to deploy semi-autonomous systems," concludes Hodgson. "As gesture control and driver identification emerge as popular features to justify the additional cost of an autonomous system to the end users, OEMs are exploring how these new features can be offered via the enabling hardware for next generation DMS, in order to capitalise on this movement."
Location Based Systems

Related Content

  • Is DSRC progressive enough for future connected mobility?
    February 3, 2012
    Dedicated Short Range Communications technology, says Cisco's Paul Brubaker, is not by itself progressive enough to sustain long-term innovation in the connected mobility environment - and yet IPv6 and other developments remain largely ignored by policy-makers
    Read More
  • Self-learning AI poised to disrupt automotive industry
    December 15, 2016
    Self-learning artificial intelligence (AI) in cars is the key to unlocking the capabilities of autonomous cars and enhancing value to end users through virtual assistance, according to Frost & Sullivan. It offers original equipment manufacturers (OEMs) fresh revenue streams through licensing, partnerships and new mobility services. Simultaneously, the use-case scenarios of self-learning AI in cars are drawing several technology companies, Internet of Things (IoT) companies and mobility service providers to
    Read More
  • Global V2V penetration into new vehicles to rise by 2027
    June 13, 2013
    A new report from ABI research concludes that global vehicle to vehicle (V2V) penetration into new vehicles will increase from just over 10 per cent in 2018 to 70 per cent in 2027, with the EU, US, and Japan as key regions adopting V2V in the mid-term. “V2X market and regulatory dynamics vary greatly from region to region. While the US will decide whether or not to mandate V2X by the end of 2013 with implementation not expected before 2018, in Europe the Car 2 Car Communication Consortium (C2C-CC) has issue
    Read More
  • New software could detect when people text and drive
    September 20, 2017
    Engineering researchers at Canada’s University of Waterloo are developing technology which can accurately determine when drivers are texting or engaged in other distracting activities. The system uses cameras and artificial intelligence (AI) to detect hand movements that deviate from normal driving behaviour and grades or classifies them in terms of possible safety threats.
    Read More

Highlighted Content