Aspects of the disclosure relate to computing platforms that utilize machine learning to reduce false positive/negative collision output generation. A computing platform may apply machine learning algorithms on received data to generate a collision output. In response to generating the collision output indicating a collision, the computing platform may identify a data collection location. If the data collection location is within a predetermined radius of a false positive collection location, the computing platform may modify the collision output to indicate a non-collision. If the data collection location is not within the predetermined radius, the computing platform may compute a score using telematics data and compare the score to a predetermined threshold. If the score does not exceed the predetermined threshold, the computing platform may modify the collision output to indicate a non-collision. If the score exceeds the predetermined threshold, the computing platform may affirm the collision output indicating a collision.

An incident response system for a vehicle, the incident response system comprising: incident detection means, exterior audio detection means, communication means and control means. The incident detection means detects an event indicative of a vehicle incident. The exterior audio detection means detects audio exterior to the vehicle. The communication means operatively supports an audio communication channel with a remote communication means. The control means is arranged to control the communication means in dependence on the detection of an event indicative of a vehicle incident, to establish an audio communication channel between the vehicle and the remote communication means. The control means is operable to cause selective transmission of the audio detected exterior to the vehicle to the remote communication means over the established audio communication channel.

Among other things, a documentation of a crash involving a vehicle is generated automatically. Telematics data is received that has been produced by one or more sensors associated with a telematics device at the vehicle. Based on the telematics data, a vehicle crash period is determined that begins at a start time and ends at an end time of the vehicle crash. Based on the telematics data, one or more metrics are determined associated with the vehicle during the vehicle crash period. Based on one or more metrics, a human-readable documentation of the vehicle crash is generated automatically.

The subject disclosure relates to detecting cosmetic damage on a vehicle. The disclosed technology can have one or more processors, a projector system in communication with the one or more processors, the projector system configured to project electromagnetic radiation onto at least one surface of a vehicle and receive, via one or more sensors, sensor data containing at least a portion of the electromagnetic radiation reflected off of the at least one surface of the vehicle, memory storing computer-readable instructions, the instructions effective to cause the one or more processors to receive the sensor data from the projector system, analyze the sensor data based on the reflected electromagnetic radiation and an expected pattern of reflected electromagnetic radiation, and determine if the vehicle has cosmetic damage on the at least one surface of the vehicle based on the analysis of the sensor data. Methods and machine-readable media are also provided.

A system to monitor vehicle accidents using a network of aerial based monitoring systems, terrestrial based monitoring systems and in-vehicle monitoring systems is described. Aerial vehicles used for this surveillance include manned and unmanned aircraft, satellites and lighter than air craft. Aerial vehicles can also be deployed from vehicles. The deployment is triggered by sensors registering a pattern in the data that is indicative of an accident that has happened or an accident about to happen.

Embodiments relate to transportation systems. More particularly, embodiments relate to methods and systems of vehicle data collection by a user having a mobile device. In a particular embodiment, vehicle data (also termed herein “driving data” or “data”) is collected, analyzed and transformed, and combinations of collected data and transformed data are used in different ways, including, but not limited to, predicting, detecting, and reconstructing vehicle accidents.

An apparatus includes a door frame, a carriage movable along a path relative to the door frame, a window, a bolt fixing the window to the carriage, a housing fixed to the window by the bolt, a striker mounted in the housing, and a pyrotechnic charge positioned to drive the striker into the window.

Methods and systems for monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, a virtual log of data regarding performance of the features in a virtual test environment may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include evasive maneuvers performed by the vehicle under the control of the features. The performance data in the virtual log may be used to determine risk levels associated with vehicle operation by the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicle and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the condition of components for salvage following a collision or other loss-event. To this end, the information regarding a plurality of components may be received. A component of the plurality of components may be identified for assessment. Assessment may including causing test signals to be sent to the identified component. In response to the test signal, one or more responses may be received. The received response may be compared to an expected response to determine whether the identified component is salvageable.

An occupant monitoring device for a vehicle includes an image acquisition unit, a memory, a collision detector, and a controller. The image acquisition unit is configured to acquire a captured image of an occupant in the vehicle. The memory is configured to record the captured image acquired by the image acquisition unit. The collision detector is configured to detect collision of the vehicle. The controller is configured to control the image acquisition unit, the memory, and the collision detector. The controller is configured to detect each of consecutive collisions of the vehicle by the collision detector, acquire the captured image after each of the collisions by the image acquisition unit, and record the captured image acquired for each of the collisions on the memory.