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.

Systems, methods and apparatus of vehicle security operations during parking. For example, a vehicle includes: a proximity sensor configured to detect presence of an object approaching the vehicle when the vehicle is in a parking state; at least one camera configured to monitor surroundings of the vehicle when the vehicle is in the parking state; and an artificial neural network configured to extract identification information of the object from images generated by the camera and determine a security classification of the presence of the object. The identification information is stored in the vehicle and/or transmitted to a server or a mobile device, in response to the security classification being in a predefined category.

A vehicle cabin hazard detection and management system includes an engine state sensor, a driver presence sensor, a cabin passenger sensor, a door latch sensor for each passenger door, a vehicle movement sensor, a cabin temperature sensor, an alarm device, a wireless messaging system, and a controller. The controller receives signals from the sensors, evaluates whether a hazardous condition is imminent for a cabin occupant, and activates an alarm and/or takes other action to counter the hazard.

A vehicle cabin hazard detection and management system includes an engine state sensor, a driver presence sensor, a cabin passenger sensor, a door latch sensor for each passenger door, a vehicle movement sensor, a cabin temperature sensor, an alarm device, a wireless messaging system, and a controller. The controller receives signals from the sensors, evaluates whether a hazardous condition is imminent for a cabin occupant, and activates an alarm and/or takes other action to counter the hazard.

The present disclosure relates to apparatus and methods for locking and/or unlocking a vehicle based on a location of a mobile device associated with the vehicle. In one embodiment a processor in a vehicle analyzes a position of a mobile device relative to the vehicle and allows the vehicle to be unlocked when the mobile device is determined to be approaching the vehicle.

The present disclosure relates to apparatus and methods for locking and/or unlocking a vehicle based on a location of a mobile device associated with the vehicle. In one embodiment a processor in a vehicle analyzes a position of a mobile device relative to the vehicle and allows the vehicle to be unlocked when the mobile device is determined to be approaching the vehicle.

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 system for a system for controlling a vehicle fuel-level display includes one or more processors and a memory communicably coupled to the one or more processors and storing a fuel-level display control module. The module includes computer-readable instructions that when executed by the one or more processors cause the one or more processors to, responsive to generation of a control signal, control operation of the vehicle so as to cause the fuel-level display to display a predetermined false low-fuel level.