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Autonomous vehicles: reliable perception in real time

Real-world environments are unpredictable, dynamic, and difficult to control: changing weather, variable lighting, unexpected objects,
and complex human behaviors.

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the problem

Autonomous vehicles rely on:

Real-time object detection and tracking

Semantic segmentation

Distance estimation

Obstacle classification

But:

Models are mistaken in rare cases

Actual conditions differ from the training data

The system does not always know when it is wrong

Models are mistaken in rare cases

Actual conditions differ from the training data

The system does not always know when it is wrong

Result

Decisions made with a false sense of certainty

Unexpected braking or lack of braking and poor obstacle detection

Costly human supervision

Decisions made with a false sense of certainty

Unexpected braking or lack of braking and poor obstacle detection

Costly human supervision

The real challenge is no longer average performance.
It is real-time reliability in critical and unexpected cases.

TrustalAI brings a real-time reliability layer to your embedded vision. We do not replace your perception models. We guarantee their level of confidence before a critical decision.

TrustalAI brings a real-time reliability layer to your embedded vision. We do not replace your perception models. We guarantee their level of confidence before a critical decision.

TrustalAI brings a real-time reliability layer to your embedded vision. We do not replace your perception models. We guarantee their level of confidence before a critical decision.