Airbag systems have dramatically reduced automobile fatalities worldwide, but they have led to unintended consequences where passengers (such as children located in the front seat) can be severely injured or even killed. Federal Motor Vehicle Safety Standard 208 requires automakers to offer advanced airbag systems that intelligently deploy the airbag based on the size and position of the occupant.
Today's weight- or pressure-based sensors built into seats can classify the occupant (for instance, as a large adult or small child) and instruct the airbag to deploy at full or reduced intensity. However, in many instances, those basic sensors fail to properly detect the passenger type and status. What's more, these systems are difficult to integrate and present significant design challenges to seat manufacturers as the seat often must be designed around the sensor. They also run against auto manufacturers' "common components" strategy because the system often needs to be customized for a particular vehicle model.
Canesta provides the better alternative: a cost-effective 3D-vision-based occupant sensor system that dramatically improves the effectiveness of advanced airbag systems and leads to fewer injuries and deaths in automotive crashes.
Unlike weight- or strain-based seat sensors, a Canesta-based occupant sensing system enables more accurate occupant classification, detects hazardous out-of-position conditions (e.g. the passenger is leaning forward to look in the glove compartment), simplifies seat design, saves integration costs, and provides a path to future safety applications and cost efficiencies.
A single sensor can offer multiple functions. With vision-based occupant sensing, a host of potential in-car applications are possible:
