Both the United States and the European Union have issued rulings mandating that by year 2020 all vehicles must be equipped with autonomous emergency-braking systems and forward-collision warning systems. These life-saving decisions alone would be enough to make ADAS (Advanced Driver-Assistance Systems) the main focus of attention for many, especially manufacturers, OEM vendors and their suppliers. In addition, more and more car buyers are becoming sensitive to ADAS applications and features which would enhance economy and comfort, like parking assistance or blind spots monitoring. Last but not least, fully autonomous vehicles will be marketed not so many years from now and the huge business potential of this opportunity is very clear not only to car manufacturers, but also to high-tech companies like Google and other, who are spending huge sum on research and development to develop marketable solutions in the self-driving cars marketplace.

recent McKinsey report says that though current revenues for ADAS vendors are still moderate, most industry experts expect to see an annual increase of more than 10 percent from 2015 to 2020. Growth rates of this levels would be among the highest that the automotive sector and related industries had ever known.


Technologies integrated in ADAS

Technologies integrated in ADAS (image courtesy of McKinsey&Co)


ADAS integrates many technologies, as shown in the image above; the main ones regard processors, sensors, mapping and software algorithms. Naturally, it is software algorithms which involve image processing and as a consequence need work by RSIP Vision. We have done that in several projects, most of which are listed in our ADAS section. Our algorithms use input coming from sensors to synthesize in real time selected information from the surrounding road environment. These algorithms are developed for two main purposes: i) to provide output to driver, in the form of alert or other information; ii) to specify the way system should react to control the vehicle (brake, steer or other safety-related navigation commands).

These algorithms are not a trivial development. In the words of the report:

“they could require some of the most complex in-car-software integration ever created, since any decisions that the algorithms specify, such as the application of emergency brakes, are critical to ensuring safety.”

Some of these algorithms are developed to accurately predict all possible human behavior, which is by definition quite unpredictable and potentially irrational. This is key to allow safer car navigation when, for instance, a crash between two vehicles or with a pedestrian appears imminent to the ADAS application.