A system comprises an autonomous vehicle (AV) and a control device operably coupled with the AV. The control device detects a series of events within a threshold period of time, where a number of series of events in the series of events is above a threshold number. The series of events taken in the aggregate within the threshold period of time deviates from a normalcy mode. The normalcy mode comprises events that are expected to the encountered by the AV. The control device determines whether the series of events corresponds to a malicious event, where the malicious event indicates tampering with the AV. In response to determining that the series of events corresponds to the malicious event, the series of events are escalated to be addressed.

A system comprises an autonomous vehicle (AV) and a control device operably coupled with the AV. The control device detects a series of events within a threshold period of time, where a number of series of events in the series of events is above a threshold number. The series of events taken in the aggregate within the threshold period of time deviates from a normalcy mode. The normalcy mode comprises events that are expected to the encountered by the AV. The control device determines whether the series of events corresponds to a malicious event, where the malicious event indicates tampering with the AV. In response to determining that the series of events corresponds to the malicious event, the series of events are escalated to be addressed.

A machine may comprise a security monitoring system and an engine start/stop system (ESS) where the security monitoring system is configured to detect an object proximate to the machine and classify characteristics of the object and the ESS is configured to turn on an engine of the machine based at least in part on the characteristics of the object. The machine may further comprise a battery to supply power for operation of the security monitoring system and a charging system to charge the battery while the engine is turned on. The ESS may monitor a charge level of the battery, determine whether the charge level is below a preselected threshold start level, and in response to determining that the charge level is below the preselected threshold start level, turn on the engine based at least in part on the characteristics of the object.

A machine may comprise a security monitoring system and an engine start/stop system (ESS) where the security monitoring system is configured to detect an object proximate to the machine and classify characteristics of the object and the ESS is configured to turn on an engine of the machine based at least in part on the characteristics of the object. The machine may further comprise a battery to supply power for operation of the security monitoring system and a charging system to charge the battery while the engine is turned on. The ESS may monitor a charge level of the battery, determine whether the charge level is below a preselected threshold start level, and in response to determining that the charge level is below the preselected threshold start level, turn on the engine based at least in part on the characteristics of the object.

Methods and systems for autonomous vehicle recharging or refueling are disclosed. Autonomous electric vehicles may be automatically recharged by routing the vehicles to available charging stations when not in operation, according to methods described herein. A charge level of the battery of an autonomous electric vehicle may be monitored until it reaches a recharging threshold, at which point an on-board computer may generate a predicted use profile for the vehicle. Based upon the predicted use profile, a time and location for the vehicle to recharge may be determined. In some embodiments, the vehicle may be controlled to automatically travel to a charging station, recharge the battery, and return to its starting location in order to recharge when not in use.

Methods and systems for autonomous vehicle recharging or refueling are disclosed. Autonomous electric vehicles may be automatically recharged by routing the vehicles to available charging stations when not in operation, according to methods described herein. A charge level of the battery of an autonomous electric vehicle may be monitored until it reaches a recharging threshold, at which point an on-board computer may generate a predicted use profile for the vehicle. Based upon the predicted use profile, a time and location for the vehicle to recharge may be determined. In some embodiments, the vehicle may be controlled to automatically travel to a charging station, recharge the battery, and return to its starting location in order to recharge when not in use.

Methods and systems autonomously parking and retrieving vehicles are disclosed. Available parking spaces or parking facilities may be identified, and the vehicle may be navigated to an available space from a drop-off location without passengers. Special-purpose sensors, GPS data, or wireless signal triangulation may be used to identify vehicles and available parking spots. Upon a user request or a prediction of upcoming user demand, the vehicle may be retrieved autonomously from a parking space. Other vehicles may be autonomously moved to facilitate parking or retrieval.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Vehicle collision and/or smart home incident monitoring, damage detection, and responses are also described, with particular focus on the particular challenges associated with incident response for unoccupied vehicles and/or smart homes. Operating data associated with the autonomous vehicle and/or smart home may be received. Within the operating, an unusual condition indicative of a likelihood of incident may be detected. Based on the unusual condition, it may be determined that the incident occurred. Accordingly, a response to the incident may be determined. The response may be implemented by the autonomous vehicle and/or smart home.

An embodiment vehicle includes at least one first camera, a communicator, and a controller connected to the at least one first camera and the communicator. The controller is configured to identify an ignition-off state of the vehicle, acquire at least one first image through the at least one first camera based on the ignition-off state of the vehicle, identify a possibility of occurrence of a security-related dangerous situation of the vehicle based on the acquired at least one first image, and in response to the identifying on the possibility of occurrence of the security-related dangerous situation of the vehicle, and transmit information on the possibility of occurrence of the security-related dangerous situation of the vehicle to at least one external device through the communicator.

An embodiment vehicle includes at least one first camera, a communicator, and a controller connected to the at least one first camera and the communicator. The controller is configured to identify an ignition-off state of the vehicle, acquire at least one first image through the at least one first camera based on the ignition-off state of the vehicle, identify a possibility of occurrence of a security-related dangerous situation of the vehicle based on the acquired at least one first image, and in response to the identifying on the possibility of occurrence of the security-related dangerous situation of the vehicle, and transmit information on the possibility of occurrence of the security-related dangerous situation of the vehicle to at least one external device through the communicator.