A method for storing shard data and data formats for storing shard data are proposed. Shard data entries are generated and stored, wherein each shard data entry comprises a definition of one or more semantic objects covered by the shard data entry. Shard metadata is generated and stored, wherein the metadata comprises references to the shard data entries and, for each of the shard data entries, data representative of a bounding box indicative of an area in a geographical area that is covered by the shard data entry.

A method for controlling motion of a legged robot includes determining one or more candidate landing points for each foot of the robot. The method further includes determining a first correlation between a center of mass position change parameter, candidate landing points, and foot contact force. The method further includes determining, under a constraint condition set and based on the first correlation, a target center of mass position change parameter, a target step order, and a target landing point for each foot selected among the one or more candidate landing points for the respective foot, the constraint condition set constraining a step order. The method further includes controlling, according to the target center of mass position change parameter, the target step order, and the target landing point for each foot, motion of the legged robot in the preset period.

A vehicle dispatch system is configured to execute user type identification processing for identifying a user type indicating whether the user is a visually handicapped person or a healthy person, and when the user is identified to be a visually handicapped person, execute voice guidance processing for performing voice guidance for a visually handicapped person. The autonomous driving vehicle includes an image recognition unit configured to perform image recognition of the user. The voice guidance processing includes guidance information generation processing for generating guidance information including a moving direction for allowing the user to approach the autonomous driving vehicle based on an image recognition result of the image recognition unit, and guidance information transfer processing for transferring the guidance information to the user by voice.

Embodiments of the present disclosure relate to a method for training a trajectory classification model. The method includes: acquiring trajectory data; computing a trajectory feature of the trajectory data based on a temporal feature and a spatial feature of the trajectory data, the trajectory feature comprising at least one of a curvature or a rotation angle; and training the trajectory feature to obtain the trajectory classification model. Embodiments of the present disclosure further provide an apparatus for training a trajectory classification model, an electronic device, and a computer readable medium.

A parking support apparatus is configured to automatically park a target vehicle in a target parking space, which is one parking space out of a plurality of parking spaces. The parking support apparatus is provided with: an acquirer configured to obtain parking information indicating a parking posture of a parked vehicle in one or a plurality of parking spaces around the target parking space, out of the plurality of parking spaces; and a determinator configured to determine a parking posture of the target parking vehicle with respect to the target parking space, on the basis of the obtained parking information.

A vehicle includes a wiper switch that manually operates a wiping mode of a windshield wiper. The vehicle control system includes a first controller configured to execute an automated driving of the vehicle, and a second controller configured to control the wiping mode of the windshield wiper based on a request from the first controller or operation information of the wiper switch. The first controller transmits an auto-wiper request to the second controller during execution of the automated driving. Here, the auto-wiper request is a request for executing an auto-wiper process for automatically switching the wiping mode of the windshield wiper according to an external environment. The second controller executes the auto-wiper process when the auto-wiper request is received from the first controller in a state where the wiper switch is operated to the wiper-off position.

Provided is an information processing apparatus having a control unit configured to execute instruction proxy processing in a case where an instruction from a user specifies another information processing apparatus as an instruction target.

A vehicle includes a light switch for manually operating a lighting state of a lighting device. The light switch includes a light-off position and an auto-light position for executing an auto-light process. A vehicle control system includes a first controller for executing an automated driving of the vehicle, and a second controller for controlling a lighting state of the lighting device based on a request from the first controller or operation information of the light switch. The first controller is configured to transmit an auto-light request for executing the auto-light process to the second controller during execution of the automated driving. The second controller is configured to execute the auto-light process when the auto-light request is received from the first controller in a state where the light switch is operated to the light-off position.

A vehicle is configured to transport a passenger through autonomous travel. The vehicle includes an in-vehicle camera configured to image the passenger to generate an image, a camera controller configured to control the in-vehicle camera, and a passenger information detection unit configured to detect information about the passenger. The passenger information detection unit measures the number of passengers and the camera controller stops an operation of the in-vehicle camera in a case where the number of passengers is one.

Various technologies described herein pertain to controlling an autonomous vehicle to provide indicators to distinguish the autonomous vehicle from other autonomous vehicles in a fleet. The autonomous vehicle includes a vehicle propulsion system, a braking system, a notification system, and a computing system. The notification system outputs an indicator that is perceivable external to the autonomous vehicle. The computing system receives data specifying an identity of a passenger to be picked up by the autonomous vehicle. Moreover, the computing system controls at least one of the vehicle propulsion system or the braking system to stop the autonomous vehicle for passenger pickup. Further, the computing system controls the notification system to output the indicator; a characteristic of the indicator outputted by the notification system is controlled based on the identity of the passenger to be picked up and whether the autonomous vehicle is stopped for passenger pickup.