Innovation Sighting: Toyota’s Mood-Detecting Car

by | May 21, 2012 | Creativity Tools, Evaluation Ideas, Ideation, Innovation Sighting, Jared Diamond | 0 comments

Toyota is designing a new technology that will react to the driver’s mood. It will adjust how the car behaves depending on whether the driver is sad, happy, angry or neutral. The technology uses a camera to identify facial emotions by taking readings from 238 points on the driver’s face.

A driver’s mood can affect performance on the road. Research has shown that people with negative (and sometimes positive) emotions are distracted even more than those using a cell phone while driving. Such emotions cause otherwise excellent drivers to:

  • Experience dimmed or otherwise impaired observation and reaction times.
  • Fail to recognize situations, such as an abrupt slowing of traffic or debris in the road.
  • Get to the point that they are unable to predict or to determine what the other drivers around us are doing.
  • Make risky maneuvers and risky changes, such as cutting across several lanes of traffic to take an off-ramp, suddenly change lanes, or even to drive on the freeway shoulder.
  • Lose the ability to perform driving skills that require precise timing or other subtle skills.
  • Make a driver feel as though he or she is detached from the other drivers, vehicles, and conditions on the road.

Toyota’s new technology will try to link to these emotions to prevent accidents.

Creating a dependency between the driver’s mood and how the car responds is a classic example of the Attribute Dependency Technique, one of five in Systematic Inventive Thinking. The modern automobile has many innovative solutions that use Attribute Dependency. Anything that customizes to the preferences of the driver could be considered an attribute dependency. Examples include automatic seats that adjust to the push of a button, radio channel presets, and dashboard information readouts. My favorite innovations are those that link an internal attribute of the car to an external attribute such as driving conditions. Examples include windshield wipers that change speed depending on the amount of rain falling, tires that tilt depending on the road curves, and anti-lock brakes that adjust stopping performance to the conditions of the road surface.

Once mood-detecting technology is perfected, the question becomes what else can it do. What other attributes of the car could be adjusted to the emotions of the driver? Keeping a driver safe from the affects of road rage is a significant benefit, but there are more emotional aspects of driving a car that could be linked in. For example, if the driver is confused, the car could provide information about location, destination, time of day, time to destination and so on. It could help the driver overcome anxiety of being lost.

Attribute Dependency differs from the other techniques in that it uses attributes (variables) of the situation rather than components. Start with an attribute list, then construct a matrix of these, pairing each against the others. Each cell represents a potential dependency (or potential break in an existing dependency) that forms a Virtual Product. Using Function Follows Form, we work backwards and envision a potential benefit or problem that this hypothetical solution solves.