Automotive Technologies International, Inc.

Kunhong Xu

David S Breed

Jeffrey L Morin

Wendell C Johnson

Wilbur E DuVall

Michael E Kussul

Tie-Qi Chen

Andrew J Varga

Wilbur E Duvall

Henk Helleman

Arrangement and method for controlling a component in a vehicle in which at least one morphological characteristic of an occupant is measured and a current position of at least a part of a seat on which the occupant is situated is obtained. The component is controlled based on the measured morphological characteristic(s) and the current position of the seat. The component may be an occupant restraint device, such as an airbag whose inflation, deflation and/or deployment direction is/are controlled.

Apparatus and method for controlling a vehicular component

Method for controlling an occupant protection device in a vehicle in which data is acquired from at least one sensor relating to an occupant in a seat to be protected by the occupant protection device, the type of occupant is classified based on the acquired data and when the occupant is classified as an empty seat or a rear-facing child seat, deployment of the occupant protection device is disabled or adjusted. Otherwise, the size of the occupant is classified based on the acquired data, the position of the occupant is determined by one of a plurality of algorithms selected based on the classified size of the occupant using the acquired data, each algorithm being applicable for a specific size of occupant. Deployment of the occupant protection device is disabled or adjusted when the determined position of the occupant is more likely to result in injury to the occupant if the occupant protection device were to deploy. The algorithms may be pattern recognition algorithms such as neural networks.

System for determining the occupancy state of a seat in a vehicle and controlling a component based thereon

Method for developing and adapting a system for determining the location of an object in a passenger compartment of a vehicle using a variety of transducers and pattern recognition technologies and techniques that applies to any combination of transducers that provide information about vehicle occupancy. These include weight sensors, capacitive sensors, inductive sensors, ultrasonic, optic, infrared, radar among others. The adaptation process begins with a selection of candidate transducers for a particular vehicle model based on, e.g., cost, vehicle interior passenger compartment geometry, desired accuracy and reliability, vehicle aesthetics, vehicle manufacturer preferences. Once a candidate set of transducers is selected, these transducers are mounted in the test vehicle and the vehicle is subjected to an extensive data collection process wherein various objects are placed in the vehicle at various locations and various databases are collected. A pattern recognition system is developed using the acquired data and an accuracy assessment is made. Further studies are made to determine which if any of the transducers can be eliminated from the design. The design process usually begins with a surplus of sensors plus an objective as to how many sensors are to be in the final vehicle installation. The adaptation process can determine the degree of importance of the transducers and the least important could be eliminated to reduce system cost and complexity. Various data collection techniques are utilized such as collecting data under the influence of thermal gradients and the use of neural networks to insure data quality. Other techniques used include the use of pre-processors, post-processors, modular networks, large databases and multiple databases.

Method of developing a system for identifying the presence and orientation of an object in a vehicle

System for determining the occupancy of a seat in a vehicle using pattern recognition technologies and techniques that apply to any combination of transducers that provide information about seat occupancy, for example, weight sensors, capacitive sensors, inductive sensors, ultrasonic, optical, electromagnetic, motion, infrared and radar sensors. A processor is coupled to the transducers for receiving data therefrom and processes the data to obtain an output indicative of the seat's current occupancy state. A combination neural network is resident in the processor and is created from data sets, each representing a different occupancy state of the seat and being formed from data from the transducers while the seat is in that occupancy state. The combination neural network produces the output indicative of the current occupancy state of the seat upon inputting a data set representing the current occupancy state of the seat and being formed from data from the transducers.

System for determining the occupancy of a seat in a vehicle using a variety of transducers and pattern recognition technologies and techniques that applies to any combination of transducers that provide information about seat occupancy. These include weight sensors, capacitive sensors, inductive sensors, ultrasonic, optical, electromagnetic, motion, infrared, and radar among others. The system includes a processor coupled to the transducers for receiving the data from the transducers and processing the data to obtain an output indicative of the current occupancy state of the seat. An algorithm is resident in the processor and is created from a plurality of data sets, each representing a different occupancy state of the seat and being formed from data from the transducers while the seat is in that occupancy state. The algorithm produces the output indicative of the current occupancy state of the seat upon inputting a data set representing the current occupancy state of the seat and being formed from data from the transducers. The algorithm may be a neural network or neural fuzzy algorithm generated by an appropriate algorithm-generating program.

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Rochester Hills, MI, United States of America

Kunhong Xu