METHOD OF DEVELOPING A SYSTEM FOR IDENTIFYING THE PRESENCE AND ORIENTATION OF AN OBJECT IN A VEHICLE

Patent №

US 6,529,809

Granted

2003-03-04

Filed 1999

Owner

AUTOMOTIVE TECHNOLOGIES INTERNATIONAL, INC.

Lab

AI components

4

ml · vision · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

09382406

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.

Machine learningVisionPlanningAI hardwareG01S 15/04B60R 21/01516B60R 21/0152B60R 21/01532B60R 21/01534B60R 21/01536B60R 21/01546B60R 21/01554+5 more

AI classification

Vision1.00
Machine learning1.00
Planning0.99
AI hardware0.97
Knowledge representation0.01
Speech0.01
Natural language0.00
Evolutionary computation0.00

Ownership

AUTOMOTIVE TECHNOLOGIES INTERNATIONAL, INC.

assignment · 104800955

Assignors

KUSSUL, MICHAEL E.

On an employer assignment, the assignors are typically the inventors.

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