Robert Boschgmbh

Rameez Ahmad

Gunther Lang

Muhammed Aquil Hamid

Robert Alan Jones

Rakesh Aswath Bandar

Vivek Shirgod Manjunath

Marc S Teufel

Ulrich C Michelfeit

Michael Vincent Masserant

Ulrich Christian Michelfeit

Dean Eiger

Robert Jones

Detecting and classifying damage to a vehicle. One example system includes a microphone positioned to detect sound waves inside the vehicle, one or more sensors positioned on the vehicle and configured to sense a characteristic of a windshield of the vehicle, and an electronic processor communicatively coupled to the one or more sensors and the microphone. The electronic processor is configured to receive sensor information from the one or more sensors and to receive an electrical signal from the microphone. The electronic processor is configured to determine, based on the sensor information, whether a crack event has occurred. The electronic processor is configured to, in response to determining that a crack event has occurred, determine a cause of the crack event based on the electrical signal received from the microphone. The electronic processor is configured to execute a mitigation action based on the cause of the crack event.

Automated windshield damage detection and mitigation for autonomous vehicles

Systems and methods for detecting low impact collisions for a vehicle (). The system includes at least one sensor (--) and an electronic controller (). The electronic controller () is configured to receive sensor data from the sensor (--) and determine one or more features of the sensor data received from the at least one sensor. The electronic controller () is further configured to determine if a collision has occurred based upon the one or more features of the sensor data, and take at least one action in response to determining that the collision has occurred.

Low impact crash detection for a vehicle

Detecting off-zone crashes involving a vehicle using lateral acceleration values detected at locations within the vehicle. In one example method, an electronic processor receives a first acceleration value at a centerline of the vehicle from a first acceleration sensor of at least two acceleration sensors. The electronic processor also receives a second acceleration value at the centerline of the vehicle from a second acceleration sensor of the at least two acceleration sensors. The method also includes deriving, with the electronic processor, an approximate yaw acceleration at the centerline of the vehicle based on the first acceleration value and the second acceleration value. The method also includes comparing, with the electronic processor, the approximate yaw acceleration to a threshold and initiating, with the electronic processor, one or more actions in response to the yaw acceleration exceeding the threshold.

Off-zone crash detection using lateral accelerations at different positions in a vehicle

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Canton, MI, United States of America

Rameez Ahmad