An automated valet parking system, an automated valet parking method, and an automated valet parking infrastructure, and a vehicle having an automated valet parking feature are disclosed. In particular, the vehicle can autonomously move to and park in a designated parking spot by communicating with the infrastructure. In addition, the vehicle can autonomously move to a pickup area from a parking spot by communicating with the infrastructure.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for agent trajectory prediction using anchor trajectories.

The present technology is effective to cause at least one processor to receive attributes of a sidewalk section within a threshold distance from a location selected by a passenger, determine a potential location for pick-up or drop-off of the passenger by the autonomous vehicle, receive an authorization from the passenger, and navigate the autonomous vehicle to the potential location for pick-up or drop-off. The attributes may include a respective curb height of the sidewalk section within the threshold distance. The potential location may be determined based upon a height of a portion of an autonomous vehicle and the respective curb height of the sidewalk section within the threshold distance. The authorization may confirm the potential location for pick-up or drop-off.

The present technology is effective to cause at least one processor to receive attributes of a sidewalk section within a threshold distance from a location selected by a passenger, determine a potential location for pick-up or drop-off of the passenger by the autonomous vehicle, receive an authorization from the passenger, and navigate the autonomous vehicle to the potential location for pick-up or drop-off. The attributes may include a respective curb height of the sidewalk section within the threshold distance. The potential location may be determined based upon a height of a portion of an autonomous vehicle and the respective curb height of the sidewalk section within the threshold distance. The authorization may confirm the potential location for pick-up or drop-off.

Example embodiments relate to identification of proxy calibration targets for a fleet of sensors. An example method includes collecting, using a sensor coupled to a vehicle, data about one or more objects within an environment of the vehicle. The sensor has been calibrated using a ground-truth calibration target. The method also includes identifying, based on the collected data, at least one candidate object, from among the one or more objects, to be used as a proxy calibration target for other sensors coupled to vehicles within a fleet of vehicles. Further, the method includes providing, by the vehicle, data about the candidate object for use by one or more vehicles within the fleet of vehicles.

A method for reconstructing a motion track applied to a terminal is provided. The method includes: obtaining a data set, the data set including positioning data obtained by positioning a target object; performing data fitting on target data in the data set to obtain a plurality of segments of first curves, the target data being positioning data obtained by performing noise filtering on the data set; and determining a motion track of the target object based on the plurality of segments of first curves. Counterpart apparatus and non-transitory computer-readable storage medium embodiments are also contemplated.

An operation device for a vehicle includes an operation body configured to be displaced by being operated so as to turn the vehicle according to a displacement of the operation body while the vehicle is being manually operated, a detector configured to detect the displacement of the operation body so as to turn the vehicle according to the displacement of the operation body while the vehicle is being manually operated, and a determination section configured to determine a state of the operation body and the detector based on the displacement of the operation body as detected by the detector while the vehicle is in non-manual operation.

A computer-implemented method of evaluating the performance of a full or partial autonomous vehicle (AV) stack in simulation, the method comprising: applying an optimization algorithm to a numerical performance function defined over a scenario space, wherein the numerical performance function quantifies the extent of success or failure of the AV stack as a numerical score, and the optimization algorithm searches the scenario space for a driving scenario in which the extent of failure of the AV stack is substantially maximized, wherein the optimization algorithm evaluates multiple driving scenarios in the search space over multiple iterations, by running a simulation of each driving scenario in a simulator, in order to provide perception inputs to the AV stack, and thereby generate at least one simulated agent trace and a simulated ego trace reflecting autonomous decisions taken in the AV stack in response to the simulated perception inputs, wherein later iterations of the multiple iterations are guided by the results of previous iterations of the multiple iterations, with the objective of finding the driving scenario for which the extent of failure of the AV stack is maximized.

Provided are an apparatus and a method for analyzing a state of a vehicle occupant and performing illumination and image output control by a projector in units of a screen sectioned area of a vehicle ceiling, in accordance with an analysis result. There is provided a data processing unit configured to execute state analysis of an occupant of a vehicle and execute output control of a projector in accordance with an occupant analysis result. The data processing unit performs projector control of outputting illumination light having luminance determined in accordance with the occupant analysis result, in units of a sectioned area of a screen of a vehicle ceiling on which projector output light is outputted. The data processing unit analyzes a state of an occupant on the basis of a camera-captured image, and outputs illumination light having luminance determined in accordance with an occupant state, in units of a screen sectioned area above each occupant.

There is provided an information processing system capable of performing driving assistance according to different automated driving levels.

An information processing system according to an embodiment of the present disclosure includes one or more mobile devices capable of setting an automated driving level, and an external network device capable of communicating with the mobile devices. The external network device includes a communication device that communicates with the mobile device, an arithmetic model determination device that determines an arithmetic model corresponding to the automated driving level and provides the arithmetic model to the mobile device via the communication device, and a registration determination device that determines whether or not registration of the automated driving level is possible on the basis of information regarding possession of the arithmetic model, and gives a notification of registration permission to the mobile device via the communication device. The mobile device includes an arithmetic model request unit that requests the arithmetic model from the arithmetic model determination device, and causes the information to be transmitted to the registration determination device when the requested arithmetic model is provided, and a movement control unit that starts movement control based on the automated driving level permitted to be registered when the notification is received from the registration determination device.