Ford Global Technolgoies, LLC

Tarik Safir

Sam Harris

Stuart C Salter

John Robert Van Wiemeersch

Donald Paul Bilger

James Nicholas Murray

Gabriel Mitchell

Aaron Abentheuer

Endre Hanak

Hasan Akoglu

Brendan F Diamond

Zeljko Deljevic

Nikhil Nagraj Rao

Douglas J Rogan

Shruthi Venkat

Betsy Fields Smith

Jamie Mahmutyazicioglu

Jonathan Hannaford

Julian Aaron Abentheuer

Paul Kenneth Dellock

David Brian Glickman

Hussein H Berry

Thomas Joseph Hermann

Andrew John Murray

Todd Ansbacher

Evangello Flouty

Stuart Alexander Lane

Andy Charalambous

Edward Ogorman

Benjamin George Brown

Andrew Charalambous

Andy John Murray

Edward O'GORMAN

Examples provide systems and methods for detecting vehicle tamper events without relying on a clear line-of-sight. Namely, examples leverage an intelligent insight that many types of vehicle tamper events have unique audio signatures. Accordingly, examples detect/classify vehicle tamper events based on these unique audio signatures. Moreover, examples can verify these audio-based classifications by analyzing acceleration-related data (e.g., relative acceleration data for a body of a vehicle, relative jerk data for a body of a vehicle, etc.) to determine suspicious movement of a body of a vehicle during a potential/suspected vehicle tamper event. This acceleration-related verification step can reduce occurrence of false positive audio-based classifications caused by other noise events proximate to the vehicle that have similar audio signatures to vehicle tamper events (e.g., drilling or other noise from a construction site, rain, etc.).

Systems and methods of using a machine learning model to classify catalytic converter theft tamper events based on audio data

A vehicle determines that a vehicle alarm system has been engaged and determines a local context applicable to the vehicle alarm system. The vehicle obtains an alarm system configuration mapping applicable in light of the local context. The vehicle changes sensitivity of one or more sensors associated with the alarm system based on the configuration mapping.

Contextual calibration of connected security device

Upon detecting an absence of a user inside a passenger cabin of a vehicle, an object inside the passenger cabin is classified as one of preferred or nonpreferred. Upon classifying the object as preferred, a sensor is activated to monitor an environment outside the passenger cabin based on determining the object is visible from outside the passenger cabin. A priority level for the preferred object is determined based on data from the sensor, wherein the priority level is one of high or low. A vehicle component is actuated to reduce the priority level based on determining the priority level for the preferred object is high.

Vehicle sensor control for optimized monitoring of preferred objects within a vehicle passenger cabin

A computer includes a processor and a memory storing instructions executable by the processor to select a scanning rate for a first sensor of a vehicle based on at least one of data related to a current time or data related to a location of the vehicle; instruct the first sensor to run at the selected scanning rate; in response to receiving data from the first sensor indicating a newly present object, turn on a second sensor; and then record data from the second sensor. The second sensor has a higher power draw than the first sensor.

Battery-powered vehicle sensors

The disclosure generally pertains to systems and methods for providing a vehicle-and-drone-based security service. In an example method, a first area of interest and a second area of interest associated with a structure may be determined. The first area of interest may then be determined to be monitored at the vehicle. The second area of interest may also be determined to be monitored at a drone associated with the vehicle. A route may be identified for the drone to travel along, where the route is configured for the drone to monitor the second area of interest. The drone may then be launched via the vehicle to travel along the route to monitor the second area of interest.

Systems and methods for providing a vehicle-and-drone-based security service

A system receives vehicle state data reported over a connection established with a vehicle and determines a loss of connection with the vehicle. Responsive to the loss of connection, the system performs an analysis of a plurality of predefined causes of incidental connection loss, based on vehicle state data previously reported compared to predefined values indicative of causing a lost connection. Responsive to the analysis indicating no predefined cause of incidental connection loss being present, the system triggers a vehicle alarm state protocol.

Malicious connectivity interruption detection

A monitoring system for a vehicle includes a plurality of surveillance sensors in connection with the vehicle and configured to capture sensor data proximate to the vehicle. A position sensor is configured to detect a location of the vehicle. A controller determines a surveillance mode for the vehicle based on the sensor data and a plurality of security factors associated with the location of the vehicle. The controller activates the surveillance mode in response to the security factors and monitors the sensor data. The controller further filters a plurality of security events from a plurality of benign events and selectively outputs alerts in response to the security events and the benign events.

System and method for vehicle security monitoring

Upon identifying an authorized user approaching a vehicle, vehicle locks are controlled to permit the authorized user to access an authorized area based on a user authorization. Permitted vehicle features within the authorized area for the authorized user are identified based on the user authorization. Upon receiving a user input selecting one permitted vehicle feature, the selected permitted vehicle feature is actuated based on determining that a state of charge of a battery is above a charge threshold. Upon determining that the state of charge of the battery decreases below the charge threshold, actuation of the selected permitted vehicle feature is stopped. Then an engine is controlled to charge the battery based on the user authorization.

Vehicle power management

The systems and methods disclosed herein are configured to provide security to a vehicle. A system includes a point measurement device inside a space of a vehicle. The system identifies a threat if points that differ from a calibrated set of points are localized in an area of the space.

Systems and methods for providing security to a vehicle

While a vehicle is in a minimal power state, a first sensor is activated based on a location of the vehicle within a monitored area. The vehicle is transitioned to an on state based on detecting an object via data from the first sensor. Then the vehicle is operated to block an exit from the monitored area based on identifying the object as an unauthorized object.

Vehicle object detection

A charge level of a sensor battery providing power to a sensor in a vehicle is determined. A charge depletion of the sensor battery is determined based on the charge level. A recharge rate to recharge the sensor battery is determined based on a time elapsed on a previously traveled path, a current charge level, and the charge depletion. Upon activation of the vehicle, one or both of a propulsion or a vehicle battery is actuated to recharge the sensor battery at the recharge rate.

Vehicle sensor operation

A vehicle includes determines that a vehicle alarm system has been engaged and determines a local context applicable to the vehicle alarm system. The vehicle obtains an alarm system configuration mapping applicable in light of the local context. The vehicle changes sensitivity of one or more sensors associated with the alarm system based on the configuration mapping.

A computer includes a processor and a memory storing instructions executable by the processor to detect an object in data received from a rear-facing radar on a vehicle and activate an alarm in response to the object moving through a predesignated region behind the vehicle at a speed below a threshold speed or for a duration above a threshold time.

Vehicle alarm

A computer includes a processor and a memory storing instructions executable by the processor to receive radar data from a radar sensor of a vehicle; demarcate a zone of coverage of the radar sensor, the zone of coverage having an area based on a number of objects indicated by the radar data; and after demarcating the zone of coverage, in response to detecting a newly present object in the zone of coverage, adjust a scanning rate of the radar sensor based on a distance of the newly present object from the radar sensor.

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Chesterfield, United Kingdom

Tarik Safir