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SAFETY SCORE

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OVERVIEW

The Navmatic Safety Score is Navmatic's proprietary software. It is used by municipalities, micromobility operators, and insurers to quantify micromobility safety. The Safety Score is computed based on dangerous events detected during the micromobility ride as well as other information such as the safety of the chosen route. 


    Proprietary machine learning algorithms instantly detect when and precisely where dangerous riding maneuvers such as aggressive swerving, heavy braking, hard acceleration, speeding, and crashes occur. For each event detected, the software computes a confidence level and estimated event intensity. An algorithm combines the events detected with metadata on the route ridden such as a possible designed bike lane or heavy pedestrian areas to quantify the overall safety of the ride.  
   

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MUNICIPALITIES

The Safety Score is used by municipalities to see aggregated rider safety statistics over time as well as support decision making for transportation infrastructure improvements. For example, if numerous crashes are detected in a particular location, the city government could prioritize a new bike lane on that street. If aggregated data shows repeated hard swerves in a particular location, that could indicate a dangerous obstacle in the road that should be addressed.

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OPERATORS

Micromobility operators use the Safety Score to improve the user's experience riding a vehicle they may feel uncomfortable with by providing feedback to the rider on how to ride safely. As the user gets more comfortable on the vehicle and minimizes dangerous maneuvers, increased vehicle performance can be unlocked. Similarly, operators can use the Safety Score to understand riding patterns that contribute to increased wear and tear, such as hard braking and skidding. 

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INSURERS

Insurers use the Safety Score to accurately calculate risk for a fleet of micromobility vehicles by accurately understanding mild and severe accident rates and patterns over time. Immediate crash detection ensures that riders can get help as soon as possible after an accident. 

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Reckless Riding

Vehicle Diagnostics

  • Hard Braking

  • Aggressive Turns

  • Crashes

  • Stop Sign Violation

  • Speeding


   

  • Skidding

  • Brake Failure

  • Tip Over Detection

  • “Black Box” Data Recorder


   

PRODUCT OVERVIEW

Proprietary algorithms detect aggressive riding events such as sudden braking, hard swerves, and crashes

Correlates rider action with location to support decision making for mobility infrastructure improvements

Encourage safe riding and improve user onboarding experience via specific rider feedback