An information processing method is provided to reduce an amount of data to be monitored in an onboard system of a vehicle. In the method, detection results that indicate whether an abnormality is included in communication data on an onboard network are obtained, and a first log transmission instruction is generated to cause periodic transmission of a first log from the onboard system to a server device. The first log is a log of some of the communication data. A second log transmission instruction is generated to cause transmission of a second log from the onboard system to the server device in a case of the detection results indicating the abnormality is included in the communication data. The second log is a log of more of the communication data than the first log.

A system for detection of a target sound in an environment of a vehicle, includes an audio sensor, a computer processor, and a memory storing a digital target sound template produced by converting a sample of the target sound in accordance with conversion parameters. The computer processor receives a sound signal from the audio sensor, digitizes the sound signal in accordance with the conversion parameters, and determines a degree of similarity between the digitized signal and the digital target sound template. The sound signal may be logarithmically amplified before being digitized. The sound signal may be received from two audio sensors, and the direction of the target sound may be determined based on a difference between time indices for detection of the target sound for each audio sensor.

An information processing method is provided to reduce an amount of data to be monitored in an onboard system of a vehicle. In the method, detection results that indicate whether an abnormality is included in communication data on an onboard network are obtained, and a first log transmission instruction is generated to cause periodic transmission of a first log from the onboard system to a server device. The first log is a log of the communication data. A second log transmission instruction is generated to cause transmission of a second log from the onboard system to the server device in a case of the detection results indicating the abnormality is included in the communication data. The second log is a log of the communication data and includes an amount of data generated per unit time that is greater than the first log.

A method and apparatus for planning a travelling path, and a vehicle are provided. The method includes: determining at least one reference curve covering a first length range, and selecting a target reference curve covering the first length range from the at least one reference curve covering the first length range; extracting a curve to be adjusted covering a second length range from the target reference curve covering the first length range; processing the curve to be adjusted based on a safety parameter within the second length range, to obtain an adjusted curve; and determining a travelling path covering the first length range based on the adjusted curve and the target reference curve. The complexity of an actual traffic scene is taken into account, and a travelling path planning is not affected by the accuracy of sampling points.

The present disclosure relates to systems and methods for determining a driving action in autonomous driving. The systems may obtain driving information associated with a vehicle; determine a state of the vehicle; determine one or more candidate driving actions and one or more evaluation values corresponding to the one or more candidate driving actions based on the driving information and the state of the vehicle by using a trained driving-action model; select a target driving action from the one or more candidate driving actions based on the one or more evaluation values; determine a target driving path based on the target driving action; and send signals to a control component of the vehicle to direct the vehicle to take the target driving action to follow the target driving path.

A method for sampling of task relevant data in sensors in a vehicle, wherein a number of sensors are arranged in the vehicle. The method comprises receiving a task at a computer or data processing unit arranged in the vehicle, the task being associated with task information, providing a set of abstract models associated with context and content information, the abstract models including models describing traffic scenes and the context and context information describing traffic scene environment, classifying sampling of sensor data according to the task information and a selected abstract model in order to sample task relevant data, evaluating the selected abstract model based on received sensor data whether to maintain the selected abstract model or to select a new abstract model, the received sensor data representing an actual traffic scene, and adapting the classification of sampling of sensor data based on selected abstract model.

Provided is a travel control device for a vehicle such that comfortable and safe control for the vehicle is possible without disturbing the driver. The travel control device for the vehicle is provided with a control command computation unit for calculating a steering assist amount for assisting the steering of the vehicle and an acceleration command value for controlling braking and driving forces of the vehicle. The control command computation unit calculates an estimated lateral position of the vehicle at a gaze distance ahead of the vehicle; calculates a lateral displacement amount of the vehicle at the estimated lateral position from a target traveling path and a lateral displacement speed; calculates a steering assist amount on the basis of the lateral displacement amount and the lateral displacement speed; calculates a lateral acceleration and lateral jerk generated by the vehicle according to the steering assist amount; and calculates an acceleration command value based on the lateral acceleration and the lateral jerk.

A vehicle adjusts a distance between a subject vehicle and a front vehicle according to a height of the front vehicle. The vehicle includes a distance sensor, and a processor which determines data of the front vehicle among data obtained by the distance sensor, and maintains a distance to the front vehicle equal to or more than a predetermined distance when a longitudinal dispersion value of the determined data is a predetermined reference value or more.

A control apparatus for a hybrid vehicle is configured to control the hybrid vehicle. The control apparatus is provided with: an arithmetic operator configured to arithmetically operate a pulsation compensating torque for compensating a pulsation component; an arithmetic operation controller configured to control the arithmetic operator (i) to arithmetically operate the pulsation compensating torque in a first cycle in a period that does not include a vertex portion in which the pulsation compensating torque is locally maximal or locally minimal and (ii) to arithmetically operate the pulsation compensating torque in a second cycle, a length of which is shorter than that of the first cycle, in a period that includes the vertex portion; and a torque controller configured to control the electric motor to output a torque including the pulsation compensating torque arithmetically operated by the arithmetic operator.

The present disclosure relates to methods and apparatuses for decision making. An example method includes obtaining a predicted moving track of an ego vehicle and predicted moving tracks of obstacles around the ego vehicle. The method further includes determining a game object. The game object is an obstacle that is in the obstacles around the ego vehicle and whose predicted moving track intersects the predicted moving track of the ego vehicle or whose distance from the ego vehicle is less than a specified threshold. The method further includes constructing one sampling game space for each game object based on vehicle information of the ego vehicle, obstacle information of the game object, and road condition information that are collected by a sensor system. Each sampling game space includes one or more game policies. The method further includes calculating a policy cost of each game policy.