Contextual and Comprehensive Driving Score
By fusing real-time traffic and weather conditions with driving data, we give meaning to driving safety score. And by measuring fatigue and distractions, we’ve made it truly comprehensive.
Contextual and Comprehensive Driving Score
By fusing real-time traffic and weather conditions with driving data, we give meaning to driving safety score. And by measuring fatigue and distractions, we’ve made it truly comprehensive.
Real-time Driving Context
Driving does not happen in isolation. We encounter other drivers, sometimes demanding weather, fading light, and sometimes unexpected circumstances. And that’s why it is important to know the context of a driver’s actions to derive meaning and usable insights from it.
To achieve this, we capture and fuse driving context like current traffic, weather, road type, and the time of day and fuse it with driving behavior data. This gives true context and rich data, which is utilized for accurate risk measurement with respect to driving situations. We go beyond standard telematics and estimate not just driver behavior but also actual risk exposure.
Relative Speed
Speeding accounts for close to 30% of all accidents. But the actual risk is a function not only of the driver’s speed, but the average speed of others around him, visibility, traction, and in extreme conditions, even the wind speed.
That’s why when we calculate the speeding score, we factor in all the above factors to create a new paradigm in Driving Safety scoring.
Acceleration, Braking, Cornering
The acceleration, braking, and cornering patterns of a driver are a good indicator of a user’s driving habits.
By interpreting data from various motion sensors in the driver’s phone, our machine learning algorithms can generate insights about the driver’s acceleration, braking, and cornering score.
Fatigue Score
Driver fatigue sets in on long trips or when the drive is monotonous and can result in a micro-sleep. We profile every trip for data points like last trip duration, sleep patterns, current drive time, average trip duration, age, etc. and combine it with current driving conditions to predict the fatigue level of the driver.
This also helps us alert the driver to take a break when tiredness crosses the safe threshold.
Distraction Score
App captures phone use and screen on time when the vehicle is in motion and combines it with the real-time driving speed. This helps identify the phone usage pattern of the driver. For e.g., is the driver using his phone only when the speed is zero (predictably traffic light) or does he use his phone even at high speeds.
Kruzr’s distraction score is a realistic representation of distracted driving.
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