SenseSafe
Drivers Safety
Use Case
Background
The client in this case is a well-known manufacturer of luxury automobiles.
The brand is synonymous with safety and is known worldwide for the high quality of its engineering and high-tech safety systems.
The company approached Opsis to produce advanced sensing equipment as a standard feature in all its new vehicles.
Objectives
To monitor the driver’s attention level, and protect against distractions while driving.
To sense and warn against emotions that endanger safety such as fatigue, anxiety, aggression/road rage.
Solutions
We integrated SenseSafe’s deep learning algorithm with cameras in cars which focus on the driver to make sure that he or she is paying attention to the road. The cameras detect how often the driver blinks, where the driver is looking, how frequently the rear-view mirror is used and whether the driver is paying attention to the car’s blind spots. The cameras also detect when the driver is dozing off, texting or eating while driving.
As long as the driver assistance system is switched on, our monitoring algorithm guarantees that drivers are alerted when they engage in risky behaviour that might endanger the driver or passengers.
The driver’s ability to drive may be affected by his or her emotional state. Our algorithm continuously interprets facial expressions as well as their intensity. It is sensitive to split second changes in micro expressions, and it detects aggression, extreme anxiety, anger and also less obvious emotional states such as fatigue and low-level engagement. The system is an important safeguard for passengers as well as for drivers.
The algorithm’s high accuracy is especially effective at detecting negative emotions. The addition of voice analytics greatly improved the system’s accuracy when it comes to detecting aggression or extreme anxiety.
Benefits
Our annotated data concerning mood and emotions has been drawn from studies of close to half a million people. It provides insight into the prevalence of disorders and risks that commonly determine premiums for automobile insurance.
Driving behavior and the driver’s emotional state may also be influenced by the weather and even the type of road. For instance, drivers may pay more attention to the road in rainy weather, and even when the weather is clear, than they do when the sky is simply cloudy. Engagement is likely to be higher on city streets and highways than on on one-lane roads and two-lane highways.
The frequency with which the driver blinks and the direction in which the driver looks can indicate drowsiness, especially during long distance driving. Opsis has worked closely with healthcare professionals on detecting mood swings and conditions such as mental stress, pre-stroke symptoms or signs of epilepsy likely to affect a driver.
Our system is capable of integrating emotional data into wearables such as smartwatches which can then collect physiological data (heart rate, temperature changes) in real time in order to identify sudden physiological changes that may affect driving.
