Deep learning based self-driving car, deep learning based self-driving control device, and deep learning based self-driving control method
AssigneeMando Corporation
InventorsHae Sueng Lim, Seong Hee Jeong, Jae Eun Lee
Life of this patent
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Abstract
The present embodiments relate to a deep learning-based self-driving vehicle, a deep learning-based self-driving control device, and a deep learning-based self-driving control method, and more particularly, to a deep learning-based self-driving vehicle, a deep learning-based self-driving control device, and a deep learning-based self-driving control method which are capable of reliably performing self-driving control to a necessary degree in a necessary situation by accurately distinguishing between and recognizing a control target object referenced while the self-driving vehicle is traveling and a structure not referenced.
Claims14
A deep learning-based self-driving control device comprising:
- a deep learning algorithm execution unit configured to output a result of executing a deep learning algorithm on a monitoring signal obtained by monitoring a periphery of a vehicle;
- a self-driving control unit configured to, when the vehicle is self-driving, control the self-driving of the vehicle on the basis of the result of executing the deep learning algorithm;
- and
- a deep learning processing unit configured to change the deep learning algorithm with reference to driver driving information,
- wherein the monitoring signal is input to an input layer of a deep neural network and the result of executing the deep learning algorithm corresponds to values of a plurality of output nodes of an output layer of the deep neural network,
- wherein the deep neural network includes the input layer having a plurality of input nodes, the output layer, a hidden layer having a plurality of connection nodes for connecting the plurality of input nodes to the plurality of output nodes, and a plurality of weight lines for connecting the plurality of input nodes to the plurality of connection nodes and for connecting the plurality of connection nodes to the plurality of output nodes.
A deep learning-based self-driving vehicle comprising:
- a sensor configured to monitor a periphery of the vehicle and output a monitoring signal;
- a deep learning-based self-driving control device configured to perform a deep learning algorithm on the monitoring signal and, when the vehicle is self-driving, output a control signal for controlling the self-driving of the vehicle on the basis of a result of executing the deep learning algorithm and change the deep learning algorithm with reference to driver driving information;
- and
- a driving device configured to drive the vehicle according to the control signal,
- wherein the monitoring signal is input to an input layer of a deep neural network and the result of executing the deep learning algorithm corresponds to values of a plurality of output nodes of an output layer of the deep neural network,
- wherein the deep neural network includes the input layer having a plurality of input nodes, the output layer, a hidden layer having a plurality of connection nodes for connecting the plurality of input nodes to the plurality of output nodes, and a plurality of weight lines for connecting the plurality of input nodes to the plurality of connection nodes and for connecting the plurality of connection nodes to the plurality of output nodes.
A deep learning-based self-driving control method comprising:
- outputting a result of executing a deep learning algorithm on a monitoring signal obtained by monitoring a periphery of a vehicle;
- when the vehicle is self-driving, controlling the self-driving of the vehicle according to the result of executing the deep learning algorithm;
- and
- changing the deep learning algorithm with reference to driver driving information,
- wherein the monitoring signal is input to an input layer of a deep neural network and the result of executing the deep learning algorithm corresponds to values of a plurality of output nodes of an output layer of the deep neural network,
- wherein the deep neural network includes the input layer having a plurality of input nodes, the output layer, a hidden layer having a plurality of connection nodes for connecting the plurality of input nodes to the plurality of output nodes, and a plurality of weight lines for connecting the plurality of input nodes to the plurality of connection nodes and for connecting the plurality of connection nodes to the plurality of output nodes.
Dependencies are inferred from the claim text.