A control device of a vehicle comprises: a driving plan generating part 90 configured to generate a driving plan in automated driving of the host vehicle; a package extracting part 91 configured to extract driving assistance packages packaging permissions for a plurality of driving assistance operations based on at least one of the surrounding environment information, the vehicle information, and the driver information; a package proposing part 92 configured to propose driving assistance packages to the driver of the host vehicle based on the driving assistance packages extracted by the package extracting part and the driving plan; and an automated driving executing part 93 configured to perform driving assistance operations permitted in a driving assistance package proposed by the package proposing part and approved by the driver of the host vehicle.

A system for navigating a vehicle automatically from a current location to a destination location without a human operator is provided. The system of the vehicle includes a global positioning system (GPS) for identifying a vehicle location and a communications system for communicating with a server of a cloud system. The server is configured to identify that the vehicle location is near or at a parking location. The communications system is configured to receive mapping data for the parking location from the server, and the mapping data is at least in part used to find a path at the parking location to avoid a collision of the vehicle with at least one physical object when the vehicle is automatically moved at the parking location. The mapping data is processed by electronics of the vehicle so that when the vehicle is automatically moved collision with the at least one physical object is avoided and the electronics of the vehicle is configured to process a combination of sensor data obtained by sensors of the vehicle. The processing of the sensor data uses image data obtained from one or more cameras and light data obtained from one or more optical sensors.

A computer-implemented method of adaptively controlling an autonomous operation of a vehicle is provided. The method includes steps of (a) in a critic network in a computing system configured to autonomously control the vehicle, determining, using samples of passively collected data and a state cost, an estimated average cost, and an approximated cost-to-go function that produces a minimum value for a cost-to-go of the vehicle when applied by an actor network; and (b) in an actor network in the computing system and operatively coupled to the critic network, determining a control input to apply to the vehicle that produces the minimum value for the cost-to-go, wherein the actor network is configured to determine the control input by estimating a noise level using the average cost, a cost-to-go determined from the approximated cost-to-go function, a control dynamics for a current state of the vehicle, and the passively collected data.

In some examples, a controller receives information of a route of a vehicle, and selects a first parameter set from among a plurality of parameter sets based on the route of the vehicle, the plurality of parameter sets corresponding to different conditions of usage of the vehicle, where each parameter set of the plurality of parameter sets includes one or more parameters that control adjustment of one or more respective adjustable elements of the vehicle. The controller causes application of the first parameter set to control a setting of the one or more adjustable elements of the vehicle.

A system for an automated vehicle includes a user input interface and an electronic controller. The electronic controller is programmed with instructions to operate at least one aspect of the automated vehicle, is configured to process information input through the user input interface, the information including data directed to predetermined parameters related to the at least one aspect of the automated vehicle at a predetermined location, and update the instructions based on the information to alter the least one aspect of the automated vehicle.

A route generation device includes: an autonomous route generator configured to generate, based on surrounding information around an own vehicle detected by a vehicle-mounted detector, an expected autonomous route along which the own vehicle is to travel; a map route acquirer configured to acquire an expected map route along which the own vehicle is to travel based on map data; and an integrated route generator configured to generate an integrated route using the autonomous route and the map route.

Embodiments of the present disclosure relates to dynamic virtual platoon. According to embodiments of the present disclosure, a first device receives driving information from vehicles and forwards the driving information to a network device. The second device determines the vehicle platoon based on the driving information and transmits the information related to the vehicle platoon to the first device. The first device determines control information to remotely drive the vehicles. In this way, the coverage of the vehicle platoon is increased and a dynamic platoon is formed. The first device controls the driving of the vehicles instead of the head vehicle, which reduces burden on the head vehicle.

The present application provides a point cloud data processing method, an apparatus, a device, a vehicle, and a storage medium, the method includes: acquiring, according to a preset frequency, raw data collected by sensors on a vehicle; and performing, according to the raw data of the sensors, data fusion processing to obtain a fusion result. By acquiring, according to the preset frequency, the raw data collected by the sensors on the vehicle in a latest period, and performing the data fusion processing to obtain the fusion result, a synchronous clock source may be removed, a weak clock synchronization may be realized, and the cost may be effectively reduced. The preset frequency may be flexibly set, which, when set with a larger value, can reduce a time difference between the raw data of the sensors and improve data accuracy.

An approach is provided for using a passenger-based driving profile. The approach involves detecting an identity of a user of a vehicle. The approach also involves retrieving a passenger profile of the user based on the identity. The passenger profile is generated based on sensor data indicating a reaction of the user to at least one vehicle driving behavior previously experienced by the user as a vehicle passenger. The approach further involves configuring the vehicle based on the passenger profile.

Systems, methods, and devices are disclosed for predicting behaviors of objects (vehicles, bicycles, pedestrians, etc.) at a location. A model descriptive of a possible object behavior can be received by an autonomous vehicle, where the model provides conditional predictions about a future behavior of an object based on a position of the object in a lane. The autonomous vehicle can detect the position of a specific object in the lane, and the model can then be applied to determine probabilities of a future behavior of the specific object.