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.

A method for processing friction data for vehicle tires on road segments, implemented by a processing system including at least one computer and an interface for remote communication with a plurality of vehicles, the method including: acquiring, from the plurality of vehicles, friction data for tires of the vehicles on a plurality of road segments, each friction datum including at least: a maximum coefficient of friction available to the vehicle on the road segment, and information relating to the road segment; establishing, for each road segment, a distribution of the friction data obtained from the plurality of vehicles for the road segment; and determining a plurality of road types, each road type comprising a set of road segments, from a measurement of similarity between the distributions of friction data obtained for each road segment.

A data memory, a computing unit and a method for performing a function of a vehicle are described, wherein values of an item of information relating to predefined local areas of a digital map are taken into account when the function is performed, the values of the information being stored in the form of an expected value and a distribution of the values around the expected value.

A system for monitoring a driver comprises that a first sensor configured to detect first physical condition information of the driver, a second sensor configured to detect first driving state information of a vehicle; and a controller configured to determine whether a physical condition of the driver is abnormal on the basis of the first physical condition information, and determine whether a driving pattern of the driver is abnormal on the basis of the first driving state information.

An autonomous driving device may include: a sensor configured to sense a surrounding object of an own vehicle, a controller configured to generate an autonomous driving path of the own vehicle based on movement data of the surrounding object sensed by the sensor unit, and a surrounding object analyzer configured to receive the movement data of the surrounding object from the controller and stochastically analyze an expected movement trajectory of the surrounding object. The controller may generate the autonomous driving path based on the expected movement trajectory of the surrounding object that is stochastically analyzed by the surrounding object analyzing unit.

A method including generating a curvilinear coordinate system from a current position of the vehicle. The method further includes generating a probability distribution from the curvilinear coordinate system and predicting a future vehicle behavior of the vehicle based on the probability distribution.

A method for determining event data including: sampling a first data stream within a first time window at a first sensor of an onboard vehicle system coupled to a vehicle, extracting interior activity data from the first data stream; determining an interior event based on the interior activity data; sampling a second data stream within a second time window at a second sensor of the onboard vehicle system; extracting exterior activity data from the second image stream; determining an exterior event based on the exterior activity data; correlating the exterior event and the interior event to generate combined event data; automatically classifying the combined event data to generate an event label; and automatically labeling the first time window of the first data stream and the second time window of the second data stream with the combined event label to generate labeled event data.

The present application discloses a method for determining an automatic driving feature, an apparatus, a device, a medium and a program product, and relates to automatic driving technology in the field of artificial intelligence. A specific solution is: acquiring scenario information of a plurality of driving scenarios and driving behavior information of an automatic driving system in each of the driving scenarios, where the driving behavior information includes a decision made by the automatic driving system and an execution result corresponding to the decision; determining an automatic driving feature of the automatic driving system according to the scenario information of the plurality of driving scenarios and respective driving behavior information. The automatic driving feature determined through the above process can represent a characteristic of an automatic driving strategy adopted by the automatic driving system.

A method and an apparatus for automated driving, a device, and a computer-readable storage medium are provided. The method for automated driving includes: obtaining data associated with a parameter and an external environment of a vehicle, the data being collected according to a collection policy for a target scenario for the vehicle; generating an automated driving model for the target scenario based on the obtained data; and updating the collection policy by testing the automated driving model.

A control device of a vehicle comprises a vehicle control part 61 configured to use a probability distribution of at least one predetermined parameter to calculate an expected value of each of at least one evaluation value and control the vehicle 1 based on the expected value.