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US 2019/0317496 A1Published application
Method and apparatus for automatical rule learning for autonomous driving
AssigneeGM Global Technology Operations LLC
InventorsDmitriy V. Korchev, Rajan Bhattacharyya, Aruna Jammalamadaka
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Abstract
The present application generally relates to a method and apparatus for generating an action policy for controlling an autonomous vehicle. In particular, the method is operative to receive an input indicative of a training event, segmenting the driving episode into a plurality of time steps, generate a parse tree in response to each time step, and generate a most probable parse tree from a combination of the generated parse trees.
Claims20
A method of controlling a vehicle comprising:
- determining an autonomous driving episode in response to a sensor signal;
- segmenting the autonomous driving episode into a first event and a second event;
- segmenting the first event into a first time step and a second time step and the second event into a third time step and a fourth time step;
- generating a first association matrix in response to the first time step, a second association matrix in response to the second time step, a third association matrix in response to the third time step and a fourth association matrix in response to the fourth time step;
- generating a transition matrix in response to the first association matrix, the second association matrix, the third association matrix and the fourth association matrix;
- generating a 3D tensor in response to the transition matrix;
- determining a probable time step in response to the 3D tensor;
- generating a probable event in response to the probable time step;
- and
- generating a control signal for controlling an autonomous vehicle in response to the probable event.
7 more elements
An apparatus comprising:
- a sensor for sensing an environment proximate to an autonomous vehicle and generating a sensor signal;
- a perception module for detecting an agent within the environment in response to the sensor signal;
- an agent motion predictor for predicting a motion of the agent within the environment in response to the detection of the agent;
- a cognitive module for determining a driving episode in response to the predicted motion of the agent, for segmenting the driving episode into a first time step and a second time step, for receiving a first driving data indicating a first action in response to the first time step and a second driving data indicating a second action in response to the second driving data, for generating a rule in response to the first action and the second action for generating a control signal in response to the rule;
- and
- a motion control module for receiving the control signal and controlling an autonomous vehicle in response to the control signal.
3 more elements
A method of controlling a vehicle comprising;
- receiving an input indicative of a training event;
- segmenting the driving episode into a first time step and a second time;
- receiving a first driving data indicating a first action in response to the first time step and a second driving data indicating a second action in response to the second driving data;
- generating a rule in response to the first action and the second action;
- and
- controlling an autonomous vehicle in response to a driving event and the rule.
3 more elements
Dependencies are inferred from the claim text.