PROFILING MODELS

ACCURATE MODELS FOR PROFILING

Research-powered data science to assess mobility.

MODELS TO ASSESS DRIVING BEHAVIOR

EXTRACTING PATTERNS

We focus on finding patterns in your mobility pattern to quantify risk exposure of having an accident, eco-efficiency, and the impact on the vehicle wear. Running our models and algorithms over augmented data, we deliver per trip, driver, vehicle, and detailed fleet profiles to serve your products. 

SAFETY INSIGHTS

RISK PROFILING

Acceleration, Braking, Cornering, and speeding analytics use thresholds and count events. The result is a score that does not show exposure to risk at all. Why?
Speed Limit – not exceeding 80 km/h on a rural road seems safe, but road topography and road conditions may allow only 50 km/h. Harsh braking – indicates risk, but harsh braking in front of a pedestrian crossing is not that risky. Extreme acceleration – means danger, but high acceleration on a highway ramp is not dangerous. ABC analytics would not expose these simple yet everyday situations.
Driving style, where, when, and under which conditions one is driving, impacts the risk of having an accident. Our analytics comprises 21 base risk factors from six different categories taking into consideration the driving environment. This so-called contextualization is a crucial aspect of calculating reliable and objective risk scores.
Our approach empowers insurers, fleet operators, and TSPs to understand their drivers’ risk portfolio better, enabling them to cluster drivers and coach them to drive safer.

ECO & EV ASSESSMENT

SUSTAINABLE DRIVING & MOBILITY

Creating an objective EV and Eco assessment relies on multiple factors: the driving style (e.g., aggressive driving, harsh acceleration, …), the anticipation and adaptation to the route topology, the average trip distance, the time between charging cycles, among other factors.

Based on augmented trip data, the platform can calculate scores and metrics:

  1. Fuel consumption estimation: using fuel and electricity consumption models based on the driving profile and the road topology
  2. Eco score: as an indication of the driver’s driving profile efficiency, compared to an ideal driving of the route
  3. EV score: indicates the potential to switch to electric vehicles for a given profile

COMPONENT HEALTH

ASSESSING CAR WEAR

Every driver knows it: the way you drive your car and under which conditions influence your car’s components’ longevity. Frequent cold starts could damage your engine and battery. Driving on roads with high roughness stresses tires and suspension. Routine harsh maneuvers decrease brake lifetime.

Assessing your vehicle’s health status enables you to decrease downtimes and avoid corrective, unexpected maintenance interventions. 

Wear scoring monitoring provides you with the means to start with predictive maintenance and coach drivers in sustainable, component-friendly vehicle handling. 

 

OUR DEVELOPER WEBSITE WILL HELP YOU

MORE TECHNICAL DETAILS

More insights into mobility profiling?

Check out our developer website!  

READ OUR WHITE PAPER

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