As people jump in their cars every day they drive off giving little consideration to the risks they may be undertaking. Driver’s emotions can get the best of them, taking their attention away from the road and the task of driving. When you’re driving while in an emotional state, there’s a tenfold increase in the risk of an accident. Cars can detect when they’re being driven abnormally and be aware of a distracted driver. If we expand the corpus of data from just the car to also information given off by drivers, we can even figure out why.
The sensors in cars understand driver behavior
There are several categories of information that vehicle-to-cloud systems might tap, to determine what’s going on. Let’s start with the driving. Issues with cars being driven erratically can mostly be detected by sensors embedded throughout a vehicle. Focus is on acceleration, speed, braking and the side to side drifting of the vehicle while it’s in motion. Lane departure warning systems in most premium cars already capture some of these actions and will continue to make their way into the volume segment. Also, vehicles are beginning to deploy predictive maintenance systems that can separate whether drifting is caused by a vehicle issue or the driver’s activity.
IBM Watson IoT Automotive and the connected car – data comes from everywhere
So, once erratic driving flags are triggered, we then need to figure out why? Here’s where we need to break some new ground by looking further at the vehicle’s systems, as well as examining the driver and other occupants more directly. We also want to add additional layers of contextual information that will help us act to help keep people safer.
We can classify diagnostic information into four categories:
Vehicle sensors, in addition to detecting erratic driving additional in-vehicle sensors such can be used to diagnose the cause
IoT sensors, that are not directly a part of the vehicle and connect through vehicle-to-cloud interchange to provide additional information
Emotional indicators, information directly given off by the driver or occupants through image, voice, audio or text
Contextual data, brought in through a vehicle-to-cloud provides supplemental information to understand the driver and the applicable responses
Previously disparate information can be newly assembled to both understand a driver’s baseline performance, and frame-of-mind, to ultimately keep them safer when there are departures from the norm. This information might also be utilized to enhance other aspects of the overall experience for people in the cars they use.
Watson IoT : Automotive Driver Behavior
Knowing drivers’ feelings is the key
It’s important to understand what is specifically going on with the driver to be able to provide relevant remedies. It’s insufficient to only know that the car is being driven erratically. Drivers could be feeling a myriad of emotions with varying intensity that affect driving ability. Proposing ill-fitting remedies will be ineffective and could even make the scenario worse.
The ultimate goal for automakers is to connect their vehicles to the broader Internet of Things, build a trusted personal connection to vehicle users and then provide a highly tuned, personalized experience that not only keeps people safer, but builds a greater attachment to the brand. The tools to enable this are now available and become the foundation for developing #CarsThatCare.
We recently talked to John Ward, IBM Solution Leader for Global Automotive and Aerospace & Defense Industries, to learn about how companies can improve product quality and reduce costs with IBM Maximo Visual Inspection. What is IBM Maximo Visual Inspection? IBM Maximo Visual Inspection detects and identifies objects in images and videos to stop defects ...read more