A failure cause analyzing system utilizes numerical data of vehicle equipment during vehicle operation and analyzes the equipment numerical data included in running data of the vehicle to select a failure inducible factor, thereby extracting the numerical data of each equipment from the running data of the vehicle even if a failure symptom does not persist and occurs intermittently, and analyzes the equipment numerical data to select the failure inducible factor, so as to reduce the time and the cost necessary for inspecting and repairing the vehicle equipment upon the occurrence of the failure symptom, and to avoid improper or excessive maintenance.

A computer system for verifying vehicle software configuration may be provided. The computer system may include a processor and a non-transitory, tangible, computer-readable storage medium having instructions stored thereon that, in response to execution by the processor, cause the processor to: (1) transmit, to a vehicle computing system, an authentication request including a hash algorithm specification; (2) receive, from the vehicle computing system, a current configuration hash value and a vehicle identifier; (3) retrieve a trusted data block from a memory based upon the vehicle identifier, the trusted data block including a stored configuration hash value and a smart contract code segment; (4) execute the smart contract code segment, the smart contract code segment including a failsafe code segment; and/or (5) transmit the authentication response to the vehicle computing system, and cause the vehicle computing system to execute the failsafe code segment.

This application relates to the field of automobile diagnosis technologies, and discloses a method and apparatus for remotely calibrating an advanced driver assistance system (ADAS), and a computer device. A diagnosis device may establish a remote connection to a client to directly remotely calibrate the ADAS of an automobile without the limitation of a distance. Therefore, a repair factory does not need to purchase diagnosis devices for all vehicle models. Instead, the diagnosis device can remotely calibrate the ADAS for the automobiles in the repair factory. In this way, the operation costs of the repair factory are greatly reduced. By means of the remote connection established between the client and the diagnosis device, the application of the diagnosis device is no longer limited to a specific area. Instead, the diagnosis device is applicable to any place where a remote connection can be established.

A position estimation system includes: a position estimation unit configured to estimate a position of a mobile terminal based on a reception status of signals that are transmitted from the mobile terminal and received by a plurality of communication devices; a scene determination unit configured to determine, based on information from a sensor mounted in a vehicle, whether a current status is a simultaneous operation scene in which both a millimeter wave radar and a radar vicinity device are operable simultaneously; and an operating mode changing unit configured to change an operating mode of at least one of the millimeter wave radar, the communication device, or the position estimation unit in response to the scene determination unit determining that the current status is the simultaneous operation scene.

A system for executing functionally equivalent applications. The system includes a cloud system including a plurality of cloud instances, the plurality of cloud instances being set up in each case to execute a functionally equivalent application in each case based on the same input data, the respective execution including a processing of the input data by the respective application in order to output an application result in each case, and a comparison device, which is set up to compare the respective application results in order to ascertain a comparison result and to output the comparison result that has been ascertained. A method for executing functionally equivalent applications, a computer program, and a machine-readable storage medium, are also described.

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 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.

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.