There is disclosed a Service Vehicle storage compartment door alarm system. In an embodiment, the system comprises an alarm pin switch bracket having one or more apertures for mounting the alarm pin switch bracket to a vehicle storage compartment door latch system using existing mounting fasteners and an alarm pin switch mounted to the alarm pin switch bracket, the alarm pin switch adapted to detect movement of the vehicle storage compartment door handle to trigger an alarm signal, the alarm pin switch including a connection point for connecting a signal wire. A plurality of alarm pin switch brackets mounted to a plurality of vehicle storage compartment door latch systems may all be connected via signal wires to a central alarm system for activating an alarm upon detection of movement of any one of the vehicle storage compartment door handles.

A vehicle security alarm assembly includes a plurality of window sensors coupled to windows of a vehicle and plurality of handle sensors coupled to door handles of the vehicle. A motion sensing array is coupled to the vehicle to detect motion proximate the vehicle. Each of the window sensors, the handle sensors and the motion sensing array is in communication with the alarm system of the vehicle to selectively trigger the alarm system. A surveillance unit is mounted to a rear view mirror of the vehicle thereby facilitating the surveillance unit to surveil a back seat of the vehicle. A personal electronic device is included that is in communication with the alarm system for alerting an owner of the vehicle when the alarm system is triggered.

Vehicle systems, computer-implemented methods, and computer program products to enhance the situational competency and/or the safe operation of a vehicle by automatically controlling the vehicle in response to a biometric attribute analysis of one or more objects detected within a predetermined threshold distance of the vehicle.

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 data, a divergence between sensor data from one or more sensors and control data from one or more autonomous operation features may be identified. Based on the divergence, it may be determined that an incident has occurred. Accordingly, a response to the incident may be determined. The response may be implemented by the autonomous vehicle and/or smart home.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Malfunctions may be detected by receiving sensor data from a plurality of sensors. One of these sensors may be selected for assessment. An electronic device may obtain from the selected sensor a set of signals. When the set of signals includes signals that are outside of a determined range of signals associated with proper functioning for the selected sensor, it may be determined that the selected sensor is malfunctioning. In response, an action may be performed to resolve the malfunction and/or mitigate consequences of the malfunction.

Methods and systems for autonomous and semi-autonomous vehicle routing are disclosed. Roadway suitability for autonomous operation is scored to facilitate use in route determination. Maps of roadways suitable for various levels of autonomous operation may be generated. Such map data may be used by autonomous vehicles or other computer devices in determining routes based upon criteria for vehicle trips. Such routes may be automatically updated based upon changes in road conditions, vehicle conditions, operator conditions, or environmental conditions. Emergency routing using such map data is described, such as automatic routing and travel when a passenger is experiencing a medical emergency.

Methods and systems for communicating between autonomous vehicles are described herein. Such communication may be performed for signaling, collision avoidance, path coordination, and/or autonomous control. Several communications from autonomous vehicles may be received at a computing device, where the autonomous vehicles are travelling within a threshold distance of each other. Each communication may include an indication of the next waypoint on a route for the respective vehicle. The computing device may analyze the communications to determine maneuvers for the autonomous vehicles so that each autonomous vehicle may navigate to the corresponding waypoint in the least amount of time or distance. The computing device also may cause each of the autonomous vehicles to move in accordance with the maneuvers for the respective vehicle.

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 to determine the robustness of autonomous systems, including the use of virtual assessment of software components within a simulated environment. A server may retrieve one or more routines associated with autonomous operation. The server may also generate a set of test data associated with test conditions. The server may also execute an emulator that virtually simulates autonomous environment. The test data may be presented to the routines executing in the emulator to generate output data. The server may then analyze the output data to determine a quality metric.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. A risk of malfunction and/or cyber-attack may be determined by collecting operating data from a plurality of autonomous vehicles and/or smart homes. The operating data may be analyzed to identify occurrences of a component malfunctioning. For each component, a risk associated with malfunctioning and/or cyber-attack may be determined based upon the identified occurrences. Based on the risks, at least one result associated with the malfunction and/or cyber-attack may be determined. A component profile may be generated based upon the determined risk and/or the impact of the determined results.

Methods and systems for autonomous and semi-autonomous vehicle control relating to anomalies are disclosed. Anomalous conditions with a vehicle operating environment, such as ice patches or flooded roads, may be identified and categorized using autonomous vehicle operating data, and corrective actions to mitigate the impact of such anomalies may be taken. Corrective actions may include maneuvering the vehicle in the area of the anomaly or rerouting the vehicle around the area of the anomaly. A vehicle encountering an anomaly may further communicate an alert to warn other nearby vehicles, including non-autonomous vehicles. Such communication may be limited to anomalies of certain types or severity, and duplicative communications may be suppressed. Vehicles receiving such alerts may take corrective actions or present information regarding the anomaly for operator response.