Method for recognizing the severity of a vehicle collision

• US 6,459,975 B1
• Filed: 07/23/2001
• Issued: 10/01/2002
• Est. Priority Date: 07/21/2000
• Status: Active Grant

• Current Assignee: Bayerische Motoren Werke AG
• Original Assignee: Bayerische Motoren Werke AG
• Inventors: Kuhn, Andreas, Urbahn, Jan
• Primary Examiner(s): ARTHUR JEANGLAUDE, GERTRUDE
• Application Number:
  US09/909,848
• Publication Number:
  US 20020052679A1
• Time in Patent Office: 435 Days
• Field of Search: 701/45, 701/46, 701/47, 701/68, 180/268, 180/271, 180/282, 280/734, 280/735
• US Class Current: 701/45
• CPC Class Codes: B60R 2021/01034 Controlling a plurality of restraint devices
• CPC Class Codes: B60R 21/0132 responsive to vehicle motion parameters , e.g. to vehicle longitudinal or transversal deceleration or speed value
• CPC Class Codes: B60R 21/01558 monitoring crash strength

Abstract

In a method for recognizing the severity of a vehicle collision, wherein the output signal of one or more acceleration sensors is processed and fed to a neural network that controls a release unit for an occupant protection device, and further wherein several occupant protection devices can be selected by the release unit in accordance with the severity and course of the vehicle collision, the future time progression of the output signal of the acceleration sensor is predicted with the help of the neural network based on the acceleration sensor signal values during at least one defined point in time.

Claims

1. A method for recognizing the severity of a vehicle collision, the method comprising the acts of:

processing an output signal of at least one acceleration sensor on a vehicle;

feeding the output signal to a neural network that controls a release unit for an occupant protection device of the vehicle, wherein a future time progression of the output signal of the at least one acceleration sensor is predicted using the neural network based on acceleration sensor signal values during at least one defined point-in-time; and

selecting the occupant protection device in accordance with the severity and course of the vehicle collision based on the predicted future time progression of the output signal of the acceleration sensor.

2. The method according to claim 1, wherein the feeding of the processed output signal of the at least one acceleration sensor to the neural network occurs at a time at which a threshold value of the output signal is exceeded.

3. The method according to claim 1, wherein the feeding of the processed output signal to the neural network occurs also at subsequent points in time.

4. The method according to claim 3, wherein the subsequent points in time occur at equidistant time intervals.