Artificially intelligent mobility safety system
AssigneeVelo Ai, Inc.
InventorGalen Clark Haynes
Life of this patent
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Abstract
In some examples, a mobility safety system includes a real-time data capturing component to capture data relating to conditions within a traffic environment using at least one of a camera, a radar sensor, a LiDAR sensor, a proximity sensor, an inertial measurement unit (IMU), and a global positioning system (GPS), at least one trained model to generate a risk estimation related to a mobility platform within the traffic environment, the at least one trained model being trained using at least one of supervised, unsupervised and semi-supervised learning, a risk estimation component to generate the risk estimation, and an alert activation component to generate a first alert directed at an operator of the mobility platform based on the risk estimation.
Claims16
A method to operate a mobility safety system of a mobility platform, the method comprising:
- capturing real-time data relating to conditions within a traffic environment;
- performing a localization and mapping operation based on the real-time data to generate localization and mapping data;
- performing a perception operation based on the real-time data and the localization and mapping data to generate object tracking and range estimation data;
- performing a prediction operation based on the real-time data, the localization and mapping data, and the object tracking and range estimation data to generate prediction data related to the traffic environment;
- using at least one trained model, generating a risk estimation related to the mobility platform within the traffic environment based on the real-time data, the localization and mapping data, the object tracking and range estimation data, and the prediction data;
- and based on the risk estimation, generating a first alert directed at an operator of the mobility platform.
A computing apparatus comprising:
- at least one processor;
- and at least one memory storing instructions that, when executed by the at least one processor, configure the computing apparatus to perform operations comprising:
- capturing real-time data relating to conditions within a traffic environment;
- performing a localization and mapping operation based on the real-time data to generate localization and mapping data;
- performing a perception operation based on the real-time data and the localization and mapping data to generate object tracking and range estimation data;
- performing a prediction operation based on the real-time data, the localization and mapping data, and the object tracking and range estimation data to generate prediction data related to the traffic environment;
- using at least one trained model, generating a risk estimation related to a mobility platform within the traffic environment based on the real-time data, the localization and mapping data, the object tracking and range estimation data, and the prediction data;
- and based on the risk estimation, generating a first alert directed at an operator of the mobility platform.
A non-transitory computer-readable storage medium, the non-transitory computer-readable storage medium including instructions that when executed by at least one computer, cause the at least one computer to perform operation comprising:
- capturing real-time data relating to conditions within a traffic environment;
- performing a localization and mapping operation based on the real-time data to generate localization and mapping data;
- performing a perception operation based on the real-time data and the localization and mapping data to generate object tracking and range estimation data;
- performing a prediction operation based on the real-time data, the localization and mapping data, and the object tracking and range estimation data to generate prediction data related to the traffic environment;
- using at least one trained model, generating a risk estimation related to a mobility platform within the traffic environment based on the real-time data, the localization and mapping data, the object tracking and range estimation data, and the prediction data;
- and based on the risk estimation, generating a first alert directed at an operator of the mobility platform.
A mobility safety system comprising:
- a real-time data capturing component to capture data relating to conditions within a traffic environment using at least one of a camera, a radar sensor, a LiDAR sensor, a proximity sensor, an inertial measurement unit (IMU), and a global positioning system (GPS);
- a unified trained model to perform operations comprising:
- a localization and mapping operation based on real-time data to generate localization and mapping data;
- a perception operation based on the real-time data and the localization and mapping data to generate object tracking and range estimation data;
- and
- a prediction operation based on the real-time data, the localization and mapping data, and the object tracking and range estimation data to generate prediction data related to the traffic environment, the unified trained model being trained using at least one of supervised, unsupervised and semi-supervised learning;
- at least one processor configured to generate a risk estimation using the unified trained model;
- and
- one or more alert mechanisms to generate a first alert directed at an operator of a mobility platform based on the risk estimation.
Dependencies are inferred from the claim text.