Scenario generation system for state or situation of vehicle or user
AssigneeToyota Jidosha Kabushiki Kaisha
InventorsShintaro FUKUSHIMA, Yusuke Yamaura
Life of this patent
Estimating the term…
Abstract
A scenario generation system includes: a scenario estimation unit configured to integrate, by machine learning, a plurality of types of input data affecting a state or situation of a vehicle or user, to estimate a scenario of the state or situation, and configured to, when at least one type of data among the input data is data acquired at non-uniform frequencies or intervals and not time-synchronized, estimate a scenario for any given time point of the at least one type of data; and a machine learning model update unit configured to update a model of the machine learning.
Claims5
A scenario generation system configured to generate a scenario of a state or situation of a vehicle or user, the scenario generation system comprising:
- a scenario estimation unit configured to integrate, by machine learning, a plurality of types of input data affecting a state or situation of a vehicle or user, to estimate a scenario of the state or situation, and configured to, when at least one type of data among the input data is data acquired at non-uniform frequencies or intervals and not time-synchronized, estimate a scenario for any given time point of the at least one type of data;
- a probability estimation unit configured to estimate a probability of the estimated scenario;
- a predicted value estimation unit configured to estimate, for the at least one type of data, predicted value data that is not acquired at a time of scenario estimation;
- and
- a machine learning model update unit configured to update a model of the machine learning based on the estimated predicted value data, actual measured values corresponding to the estimated predicted value data among the input data, the estimated probabilities, and the input data.
A method for generating a scenario of a state or situation in which a vehicle or user is placed, the method comprising:
- integrating, by machine learning, a plurality of types of input data affecting a state or situation of a vehicle or user, to estimate a scenario of the state or situation, and, when at least one type of data among the input data is data acquired at non-uniform frequencies or intervals and not time-synchronized, estimating a scenario for any given time point of the at least one type of data;
- estimating a probability of the estimated scenario;
- estimating, for the at least one type of data, predicted value data that is not acquired at a time of scenario estimation;
- and
- updating a model of the machine learning based on the estimated predicted value data, actual measured values corresponding to the estimated predicted value data among the input data, the estimated probabilities, and the input data.
Dependencies are inferred from the claim text.