Systems and methods for vehicle lifecycle management using onboard vehicle onboard data capture devices are disclosed. In one embodiment, a method of vehicle lifecycle management may include: enrolling, by a vehicle lifecycle computer program executed by an electronic device, a vehicle in a vehicle lifecycle management service; receiving, by the vehicle lifecycle computer program, a request to initiate a vehicle lifecycle event; enabling, by the vehicle lifecycle computer program, a telematics unit in the vehicle; receiving, by the vehicle lifecycle computer program, vehicle attributes from the telematics unit; requesting, by the vehicle lifecycle computer program, vehicle condition data from an on-board vehicle management computer program; receiving, by vehicle lifecycle computer program, the vehicle condition data from the on-board vehicle management computer program; receiving, by the vehicle lifecycle computer program, a request to terminate the vehicle lifecycle event; and disabling, by the vehicle lifecycle computer program, the telematics unit.

A method and a system determine a change of state of an autonomous device, such as an autonomous vehicle. A plurality of performance parameter values obtained by monitoring at least one performance parameter during the autonomous operation of the device is received. A performance quantity quantifying the quality of autonomous operation of the device, in particular the quality of driving of the autonomous vehicle, is determined based on the obtained performance parameter values and information associated with a flux of software and/or hardware related to the autonomous operation of the device. Further, a change of state value for the device is determined based on the performance quantity.

A method and system for driver monitoring by fusing contextual data with event data to determine context as cause of event is provided. The method includes detecting an event from event data received from one or more inertial sensors associated with a vehicle of a driver or with the driver. The method also includes determining a context from an audio or video feed received from one or more devices associated with the vehicle or the driver. Further, the method includes fusing the event with the context to determine the context as a cause of the event. In addition, the method includes assigning a score to a driver performance metric based at least on the context and the event.

Methods and systems for determining risk associated with operation of autonomous vehicles using autonomous communication are provided. According to certain aspects, autonomous operation features associated with a vehicle may be determined, including features associated with autonomous communication between vehicles or with infrastructure. This information may be used to determine risk levels for a plurality of features, which may be based upon test data regarding the features or actual loss data. Expected use levels and autonomous communication levels may further be determined and used with the risk levels to determine a total risk level associated with operation of the vehicle. The autonomous communication levels may indicate the types of communications, the levels of communication with other vehicles or infrastructure, or the frequency of autonomous communication. The total risk level may be used to determine or adjust aspects of an insurance policy associated with the vehicle.

A vehicle is provided that comprises two or more radio frequency (RF) antennas and two or more RF transceivers to communicate wirelessly sensitive information associated with a user of the vehicle (the two or more RF antennas being at different physical locations on an exterior of the vehicle). The vehicle determines which one of the two or more RF antennas is receiving a strongest signal from a common signal source, selects a first RF transceiver associated with the RF antenna with the strongest signal to send the sensitive information associated with the user to the common signal source, and sends the sensitive information associated with the user to the first RF transceiver for transmission to the common signal source.

A driving assistance apparatus is configured to perform an assistance control of assisting in driving a vehicle, when a first condition and a second condition are satisfied, in a situation in which a target is recognized. The driving assistance apparatus is provided with: a determinator configured to determine a state of the assistance control. The determinator is configured (i) to determine that the state of the assistance control is a standby state if a standby condition is satisfied, wherein the standby condition requires that the first condition is satisfied, but the second condition is not satisfied, in the situation in which the target is recognized, and (ii) to determine that the state of the assistance control is an interruption state if an interruption condition is satisfied, wherein the interruption condition requires that the first condition is no longer satisfied while the satisfaction of the standby condition is continued.

Systems and techniques are described herein for configuring an automotive controller within an EE architecture. The automotive controller is connected to other components within the EE architecture. An initialisation process is activated in the automotive controller in which the automotive controller determines diagnostic data for identifying other components connected to it within the EE architecture. The diagnostic data is transmitted from the automotive controller to an update controller. An identifier is assigned to the automotive controller by the update controller based on a location within the EE architecture determined from the diagnostic data. The software in the automotive controller is then updated based on the determined location.

A system for managing a set of fleet vehicles includes a central command unit having a processor and tangible, non-transitory memory on which instructions are recorded. The fleet vehicles have one or more respective electronic components and respective vehicle controllers adapted to perform self-diagnosis of their respective electronic components. The central command unit is adapted to receive notification of the self-diagnosis and classify the respective electronic components as working ones and non-working ones. The central command unit is adapted to perform component matching, including polling inventory across the fleet vehicles. Working ones of the respective electronic components are selectively redistributed for reuse across the fleet vehicles. In some embodiments, at least one of the fleet vehicles is designated as a master vehicle and the central command unit is stored in the master vehicle. In other embodiments, the central command unit is stored in a cloud computing service.

A system for simultaneously testing whether a plurality of electronic devices connected via a communication network correctly handle exceptions. The system includes a communication network, and a plurality of electronic devices and a testing device connected via the communication network. The testing device includes an electronic processor. The electronic processor is configured to send a first status query message to the plurality of electronic devices, send fuzzed data to one or more of the plurality of electronic devices, and send a second status query message to the plurality of the electronic devices. The electronic processor is also configured to, for each electronic device that responds to the first status query message with a valid response and responds to the second status query message with an invalid response or fails to respond to the second status query message, record the electronic device in a failure log.

Methods for detecting potential thermal events of a towable trailer and associated monitoring systems are provided. The method comprises the following steps, namely, first, obtaining at least one data set comprising a plurality of physical sensor inputs. The plurality of physical sensor inputs may comprise a brake chamber pressure input from the brake chamber sensor, a brake lining temperature input from the brake lining temperature sensor, and a wheel end temperature input from the wheel end temperature sensor, and other inputs from additional physical sensors. Second, transmitting at least one data set to an analytics engine. Third, selecting, with the analytics engine, a thermal risk value from a look-up table based on the data set. Fourth, comparing, with the analytics engine, the selected thermal risk value to a predetermined threshold. Fifth, generating, with the analytics engine, a thermal alert if the thermal risk value exceeds the predetermined threshold.