A method may include obtaining sensor data relating to an autonomous vehicle (AV) and a total measurable world around the AV. The method may include identifying an operating environment of the AV and determining a projected computational load for computing subsystems that facilitate a driving operation performable by the AV corresponding to the identified environment. The method may include off-loading first computing subsystems of the computing subsystems in which computations of the first computing subsystems may be processed by an off-board cloud computing system and processing computations associated with second computing subsystems of the computing subsystems by an on-board computing system. The method may include obtaining first computational results corresponding to the computations processed relating to the first computing subsystems and determining the driving operation of the AV based on the first computational results and second computational results corresponding to computations processed relating to the second computing subsystems.

A driving lane keeping control system includes a number of vehicles and a server. Each vehicle is configured to transmit wheel position information to the server. The server is configured to receive the wheel position information from each vehicle, to match the wheel position information with a detailed map to generate a moving trajectory of each vehicle, to analyze the generated moving trajectory of each vehicle to select an optimum moving trajectory, to generate virtual lane information based on the selected optimum moving trajectory, and to transmit the generated virtual lane information to at least one of the vehicles to enable the at least one vehicle to correct a driving position based on the virtual lane information.

An autonomous vehicle (AV) computing device including at least one processor may be provided. The at least processor may be programmed to (i) receive a proposed trip including a destination location and a departure time, (ii) determine environmental conditions data based on the destination location and the departure time, (iii) retrieve current software ecosystem data for the AV, (iv) retrieve aggregated data for a plurality of AVs, the aggregated data including a plurality of correlations, each correlation including a) an interaction between at least one software application and at least one environmental condition and b) an adverse performance outcome associated with the interaction, (v) compare the environmental conditions data for the proposed trip and the current software ecosystem data for the AV to the plurality of correlations to identify an adverse performance outcome, and (vi) execute a remedial action to avoid the adverse performance outcome.

A method for clearing passage of a tunnel in the automated driving mode of a vehicle involves checking, in a manual driving mode with passive automated driving mode of the vehicle, whether the tunnel is suitable for passage in the automated driving mode of the vehicle. During the check control commands for actuators of a longitudinal and transverse movement of the vehicle are generated, but are not implemented by the actuators. In the event that no unmanageable situation is detected in the tunnel during the check and the generated control commands are plausible in relation to interventions made by a vehicle user in manual driving mode with passive automated driving mode, the tunnel is assessed as suitable for automated driving mode.

A vehicle information processing method for calculating a feature related to an operation of a vehicle includes: receiving input information including at least one of information on a driving operation performed on the vehicle, information on an operating state of driver assistance of the vehicle, and information on a behavior of the vehicle; and calculating the feature by using the input information received during a predetermined period in which a predetermined condition is satisfied out of a period in which the input information is received. The predetermined condition includes a condition that a driving situation of the vehicle is a predetermined driving situation corresponding to the feature.

A vehicle-based apparatus for noise injection and monitoring includes a first processing device coupled to a plurality of components and a second processing device coupled to the plurality of components. The second processing device injects noise into at least one component among the plurality of components and monitors behavior of the at least one component in response to the injected noise. The second processing device determines, based, at least in part, on the monitored behavior of the at least one component responsive to the injected noise, a susceptibility to the injected noise exhibited by the at least one component and transmits signaling indicative of the determined susceptibility to the injected noise exhibited by the at least one component to the first processing device.

Disclosed are devices, systems and methods for using a rotating camera for vehicular operation. One example of a method for improving driving includes determining, by a processor in the vehicle, that a trigger has activated, orienting, based on the determining, a single rotating camera towards a direction of interest, and activating a recording functionality of the single rotating camera, where the vehicle comprises the single rotating camera and one or more fixed cameras, and where the single rotating camera provides a redundant functionality for, and consumes less power than, the one or more fixed cameras.

Novel electric vehicles are disclosed herein. In addition, a control system for an electric vehicle comprising a plurality of vehicle corner modules (VCMs) comprises a network of VCM-controllers. Each VCM comprises at least two subsystems selected from a drive subsystem, a steering subsystem, and a braking subsystem. Each VCM-controller is onboard and installed within a different respective VCM, and is operatively linked to each one of the at least two subsystems of its respective VCM to receive sensor data and to regulate operation in response to incoming signals received from outside its VCM. The control system provides a no-fault operating mode defined by the absence of a control-system fault. A VCM-controller of a first VCM is programmed to control, when operating in the no-fault operating mode, at least one subsystem in a second VCM.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, the operating status and/or configuration of autonomous operation features of an autonomous or semi-autonomous vehicle may be determined, such as via an on-board computer system or mobile device, and/or then directly or indirectly wirelessly communicated via data transmission from the vehicle computer system or mobile device to a remote server. An adjustment to one or more risk levels associated with operation of the autonomous or semi-autonomous vehicle may also be determined, and an auto insurance policy, premium, or discount may be adjusted based upon the adjustment to the risk levels and presented to the customer for their review and approval. As a result, insurance cost savings may be passed onto risk averse customers that opt into to a rewards program.

In one embodiment, a computing system of a vehicle may receive perception data associated with a scenario encountered by a vehicle while operating in an autonomous driving mode. The system may identify the scenario based at least on the perception data. The system may generate a performance metric associated with a vehicle navigation plan to navigate the vehicle in accordance with the identified scenario. In response to a determination that the performance metric associated with the vehicle navigation plan fails to satisfy one or more criteria for navigating the vehicle in accordance with the identified scenario, the system may trigger a disengagement operation related to disengaging the vehicle from the autonomous driving mode. The system may generate a disengagement record associated with the triggered disengagement operation. The disengagement record may include information associated with the identified scenario encountered by the vehicle related to the disengagement operation.