Toyota jidosha kabushiki kaisha (20240278792). TRAVEL CONTROLLER AND METHOD FOR TRAVEL CONTROL simplified abstract

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TRAVEL CONTROLLER AND METHOD FOR TRAVEL CONTROL

Organization Name

toyota jidosha kabushiki kaisha

Inventor(s)

Wataru Kawashima of Nisshin-shi (JP)

TRAVEL CONTROLLER AND METHOD FOR TRAVEL CONTROL - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240278792 titled 'TRAVEL CONTROLLER AND METHOD FOR TRAVEL CONTROL

The abstract describes a patent application for a travel controller that predicts future surrounding conditions of a vehicle by inputting a series of vicinity images into a neural network. The controller generates a control signal for the vehicle based on the predicted future image and the current vicinity image.

  • The travel controller uses neural networks to generate a future image of surrounding conditions of a vehicle.
  • The control signal for the vehicle is based on the predicted future image and the current vicinity image.
  • The system helps in controlling the travel of the vehicle by predicting future conditions and adjusting accordingly.
  • The first neural network processes the series of vicinity images to generate the future image, while the second neural network generates the control signal.
  • The predetermined period after the current time is used to predict the future conditions accurately.

Potential Applications: - Autonomous driving systems - Traffic management systems - Fleet management solutions

Problems Solved: - Predicting future surrounding conditions of a vehicle - Efficient control of vehicle travel based on predicted future conditions

Benefits: - Improved safety on the roads - Enhanced efficiency in vehicle control - Potential for reducing accidents and traffic congestion

Commercial Applications: Title: "Predictive Travel Controller for Autonomous Vehicles" This technology can be utilized in autonomous vehicles, transportation systems, and logistics companies to improve efficiency and safety in travel operations.

Questions about the technology: 1. How does the travel controller use neural networks to predict future surrounding conditions? - The travel controller inputs a series of vicinity images into a neural network to generate a future image representing predicted conditions. 2. What are the potential applications of this technology in the automotive industry? - The technology can be applied in autonomous driving systems, traffic management, and fleet management solutions.


Original Abstract Submitted

a travel controller generates a future image by inputting a series of vicinity images representing surrounding conditions of a vehicle up to a current time into a first neural network. the future image represents predicted surrounding conditions of the vehicle at a future time that is a predetermined period after the current time. the travel controller generates a control signal for controlling travel of the vehicle by inputting a vicinity image outputted at the current time of the series of vicinity images, the future image, and the predetermined period into a second neural network different from the first neural network.

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