A control system configured to accurately determine a condition of a road surface on which a vehicle travels. A learned model estimates the road surface condition based on the travelling data collected during propulsion of the vehicle, and a controller determines the road surface condition based on the road surface condition estimated by the learned model.

A method includes acquiring, by one or more processing circuits, an operating parameter of a component of a vehicle; acquiring, by the one or more processing circuits, at least one of static information or dynamic information regarding at least one route characteristic; determining, by the one or more processing circuits, an adjustment for the component of the vehicle based on the operating parameter and the at least one of the static information or the dynamic information indicating that an upcoming event is expected to cause the operating parameter of the component to be outside of a target operating range; and implementing, by the one or more processing circuits, the adjustment for the component of the vehicle to preemptively adjust the operating parameter of the component in advance of the upcoming event to maintain the operating parameter within the target operating range as the upcoming event is traversed.

Embodiments of the present invention utilize mobile devices to provide information on a user's behaviors during transportation. For example, a mobile device carried by a user can be used to detect and analyze driving behaviors during trips in vehicles. The mobile device can further be used to assign and display scores relating to the driving behaviors, scores for individual trips, and an overall driving score for the particular user.

Provided are a method for processing an image, an electronic device, a vehicle, a server, and a storage medium, which relate to a field of artificial intelligence technology, and in particular, to the fields of autonomous driving, intelligent transportation, and the like. The specific implementation scheme is as follows: sending at least one piece of image information to a server, the at least one piece of image information being collected by a vehicle during driving in a target area; acquiring a first mapping result generated by the server, the first mapping result including first environmental characteristic information in the target area; and storing the first mapping result as the map information of the target area, the map information of the target area being used for driving the autonomous driving of the vehicle in the target area.

Provided is a vehicle travel control device capable of improving the usability of a following control by detecting dangerous behavior in a preceding vehicle, and differing the release timing of the following control. A vehicle travel control device having a preceding vehicle behavior recognition means for obtaining behavior information for a preceding vehicle, a preceding vehicle behavior determination means for detecting the degree of risk of dangerous behavior in the preceding vehicle from the behavior information, and determining the feasibility of a following control targeting the preceding vehicle on the basis of the detected dangerous behavior risk degree, and a vehicle operation control means for outputting an acceleration/deceleration/braking/steering control command to an actuator on the basis of the feasibility determination for the following control, wherein dangerous behavior is detected on the basis of the preceding vehicle behavior information, and the timing differs between a first release timing for the following control when a first dangerous behavior is detected and a second release timing for the following control when a second dangerous behavior different from the first dangerous behavior is detected.

The present disclosure relates to a method, system, a vehicle and a computer-readable storage medium. The method comprises determining a fulfilment of a set of predefined Operational Design Domain (ODD) conditions for an Automated Driving System (ADS) feature of an ego-vehicle at least partly based on sensor data obtained from on-board sensors of the ego-vehicle and determining a first ODD exit boundary along an estimated route to be travelled by the ego-vehicle. The method further comprises obtaining data from at least one external vehicle located on the estimated route to be travelled by the ego-vehicle. Further, the method comprises evaluating the obtained data from the at least one external vehicle against an ODD assessment scheme to determine a fulfilment of the predefined ODD conditions in the surrounding environment of the external vehicle and determining a second ODD exit boundary along the estimated route of the ego-vehicle based on the evaluation.

A method for selecting a driving profile of a motor vehicle, a driver assistance system therefor and a motor vehicle equipped therewith is disclosed. In the method and based on an operating action by a driver, a deviation between the number of predetermined driving profiles currently desired by the driver and that previously used is recognized. After the deviation has been recognized, a query is output to the driver as to whether the deviation should be taught by the driver assistance system for the current situation. After the query has been confirmed by the driver, the driver assistance system is accordingly adapted for the current situation in at least one parameter influencing the selection of the driving profile to be used such that the deviation in the automatic selection of the driving profile to be used in future situations that correspond to the current situation is taken into account.

A system and method for interfacing an autonomous or remote control drive-by-wire controller with a vehicle's control modules. Vehicle functions including steering, braking, starting, etc. are controllable by wire via a control network. A CAN architecture is used as an interface between the remote/autonomous controller and the vehicle's control modules. A CAN module interface provides communication between a vehicle control system and a supervisory, remote, autonomous, or drive-by-wire controller. The interface permits the supervisory control to control vehicle operation within pre-determined bounds and using control algorithms.

This invention provides a secure self-driving system or drive-assisting system. A drive control system of the present invention has an image recognition unit for detecting the peripheral environment of a vehicle and a drive control apparatus that controls driving of the vehicle, characterized by having a peripheral environment storage unit for storing the peripheral environment of the vehicle and by changing a mode of drive control performed by the drive control apparatus on the basis of a detection performance status of the image recognition unit obtained on the basis of information about the peripheral environment stored in the peripheral environment storage unit and information detected by the image recognition unit.

A system, method, and computer program product are described for dynamically assessing and improving driver performance, including that of an autonomous driving system. Based on received electronic driver performance messages, the system determines whether an instant feedback message is required to dynamically adjust driving behavior of a subject driver or autonomous driving system. If yes, then the system provides an instant feedback message, otherwise the system provides an aggregate feedback message, calibration message, and/or coaching recommendation as appropriate. An aggregate feedback message may be provided based at least on integral rating and/or driver performance score calculated and based at least on the driver performance messages received over a predetermined time period. The system may be adapted to perform one or more of the following: calculate insurance premium, insurance coverage, calculate cost of hiring a vehicle, monitor driving quality of drivers, recruit drivers, provide incentives, provide coaching, provide driver performance reports, and inform a third party about the driving performance of a subject driver.