Systems, methods, and computer-readable media are provided for determining operator availability to provide remote assistance to an autonomous vehicle, determining which of a first plurality of routes will provide a positive ride experience based on the operator availability, and selecting a route of the first plurality of routes for a user based on the determining of which of the first plurality of routes will provide a positive ride experience.

A method, apparatus, and system for identifying objects based on grayscale images in the operation of an autonomous driving vehicle is disclosed. In one embodiment, one or more first color images are received from a camera mounted at an autonomous driving vehicle (ADV). One or more first grayscale images are generated based on the one or more first color images, which comprises converting each of the one or more first color images into one of the first grayscale images. One or more objects in the one or more first grayscale images are identified based on a pre-trained grayscale perception model. A trajectory for the ADV is planned based at least in part on the identified one or more objects. Control signals are generated to drive the ADV based on the planned trajectory.

The present disclosure relates to a pull up controlling system of a vehicle for controlling the vehicle in a planned stop-and-go situation. The pull up controlling system determines a position of the vehicle and identifies a stop-and-go destination within a predeterminable distance from the vehicle position. The stop-and-go destination includes an interaction interface. The pull up controlling system provides a user input request relating to whether to discard or acknowledge the stop-and-go destination. The pull up controlling system receives intention data indicative of confirmation to acknowledge the stop-and-go destination. The pull up controlling system further derives preference data indicative of an openable section of the vehicle. The pull up controlling system maneuvers the vehicle to pull up at the stop-and-go destination, with the openable section aligned with the interaction interface.

A method of processing data for a driving automation system, the method comprising steps of: obtaining image data from a camera of an autonomous vehicle, AV; image processing the image data to obtain a vehicle registration mark, VRM, of another vehicle within the surrounding area of the AV; looking up the VRM in a vehicle information database to obtain information indicative of the make, the model and the date of manufacture of the other vehicle; looking up information indicative of the make, the model and the date of manufacture of the other vehicle in a vehicle dimensions database to obtain at least one dimension of the other vehicle; and updating a context of the autonomous vehicle based on said at least one dimension of the other vehicle.

A server apparatus and the like that improve operation efficiency of a marketplace for trading products are provided. The server apparatus includes a communication interface, and a controller configured to transmit and receive information to and from another apparatus via the communication interface. The controller calculates a time required until sale of a product at a display position based on a temporal change in captured images of the display position where the product is displayed until the product is sold, determines an exhibition fee for the display position based on the time required, informs a terminal apparatus of an exhibitor of the exhibition fee, and urges the exhibitor to exhibit the product for sale at the display position.

The present invention relates to a method and apparatus that utilize production vehicles to develop new path planning features for Automated Driving Systems (ADSs) by using federated learning. To achieve this the “under-test” path planning module's output is evaluated in closed-loop in order to produce a cost-function that is subsequently used to update or train a path planning model of the path planning development-module.

The present disclosure relates to an information processing apparatus, an information processing method, and a program that allow for appropriately pulling over to a safe road shoulder when an emergency occurs during automated driving. On the basis of distance information from a depth sensor or the like, a travelable region available for a vehicle to travel is set like an occupancy map, and image attribute information is generated from an image by semantic segmentation. On the basis of the image attribute information, an evacuation space is set in the travelable region in accordance with the situation of the road surface of the travelable region, and thus an evacuation space map is created. The present disclosure can be applied to a mobile object.

In some examples, a system may receive, from at least one camera of a vehicle, at least one image including a road. The system may further receive vehicle location information including an indication of a location of the vehicle. In addition, the system may receive at least one of historical information from a historical database, or road anomaly information, where the road anomaly information is determined from at least one of a road anomaly database or real-time road anomaly detection. Based on the at least one image, the indication of the location of the vehicle, and the at least one of the historical information or the road anomaly information, the system may generate at least one of a disparity map or a disparity image.

A planning system for an autonomous work vehicle system includes a controller having a memory and a processor. The controller is configured to determine an action to be performed by the autonomous work vehicle system and an action location of the action in a work area, determine a transition operation associated with the action that enables the autonomous work vehicle system to perform the action at the action location, and generate a plan for operation of the autonomous work vehicle system. The plan includes the action, the action location, and the transition operation.

A planning system for an autonomous work vehicle system includes a controller having a memory and a processor. The controller is configured to provide an indication of a work area for operation of the autonomous work vehicle system, identify a plurality of zones of the work area, and identify one or more rules for each respective zone of the plurality of zones. The one or more rules define operation of the autonomous work vehicle system in the respective zone. The controller is configured to generate a plan for operation of the autonomous work vehicle system based on the plurality of zones and the one or more rules for each respective zone of the plurality of zones.