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Neural Network for robust vehicle sideslip estimation.

Listing Description

Result description

The invention concerns a lateral velocity estimator based on a novel neural network that is designed with a structure in accordance with kinematics principles. 

The new neural network estimates lateral velocity with high accuracy by a generalization of kinematics equations and can be trained with little data. The kinematics structure on which it is based improves the robustness of lateral velocity estimation, ensuring appropriate accuracies even when the vehicle type varies. 

The invention uses the measurement of yaw rate, longitudinal and lateral acceleration, and longitudinal velocity and does not require an Inertial Measurement Unit (IMU).

Missions
Climate-neutral and smart citiesClimate-neutral and smart cities
Radical Innovation Breakthrough
Artificial Intelligence, Driverless.

Addressing target audiences and expressing needs

Our needs are
  • Collaboration
  • Business Angels
  • Venture Capital
We specifically need / are looking for

Investors (Automotive OEMs, Suppliers) willing to adopt the technology.

Target audiences
  • Public or private funding institutions
  • Research and Technology Organisations
  • Private Investors

R&D, Technology and Innovation aspects

Current stage description

The invention is demonstrated and Patented (TRL about 8). Needs investors, adopters, and deployment on production vehicles.

Scalability

The neural network architecture is modular, flexible, and customizable. It can be easily fine-tuned to different types of vehicles with little effort. It can self-adapt to varying operating conditions.

Replicability

The neural network is customizable at two levels: hyperparameters-modular configuration, and training. The latter requires very little training data because the networks have very few efficient parameters.

Sustainability

The solution improves the quality of vehicle control and driver assistance functions (including self-driving).

Result submitted to Horizon Results Platform by UNIVERSITA DEGLI STUDI DI TRENTO

Offer Details

Specifications and Deliverables:

Value Proposition:

This is a robust, explainable, and precise estimator of vehicle lateral speed which outperforms traditional solutions. It needs little training data and little computational power. It is flexible and customizable. It can significantly improve vehicle control and driver assistance functions.

Input Required from Customer:

Fields of Application:

Patent/Publication Number

Main Patent Claims:

Patent Family:

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Adress:

VIA CALEPINA 14
TRENTO
Trentino – Alto Adige/Südtirol
38122
Italy

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