The invention discloses a method, system and related device of implementing vehicle automatic loading and unloading, so as to achieve the automatic loading and unloading of the unmanned vehicle. The method includes: controlling, by a vehicle controller, a vehicle to drive automatically and stop at a loading and unloading position; obtaining, by a loading and unloading control apparatus corresponding to the loading and unloading position, vehicle identification information of the vehicle; verifying the vehicle identification information and controlling a loading and unloading machine to load and unload when the verification succeeds; sending a loading and unloading completion indication to the vehicle controller after the loading and unloading is completed; and controlling, by the vehicle controller, the vehicle to leave the loading and unloading position when receiving the loading and unloading completion indication.

The invention discloses a method, system and related device of implementing vehicle automatic loading and unloading, so as to achieve the automatic loading and unloading of the unmanned vehicle. The method includes: controlling, by a vehicle controller, a vehicle to drive automatically and stop at a loading and unloading position; obtaining, by a loading and unloading control apparatus corresponding to the loading and unloading position, vehicle identification information of the vehicle; verifying the vehicle identification information and controlling a loading and unloading machine to load and unload when the verification succeeds; sending a loading and unloading completion indication to the vehicle controller after the loading and unloading is completed; and controlling, by the vehicle controller, the vehicle to leave the loading and unloading position when receiving the loading and unloading completion indication.

An information processing device (20) includes a route acquisition unit (202) and an automatic driving section determination unit (204). The route acquisition unit (202) acquires route information indicating a moving route of a mobile body. The automatic driving section determination unit (204) acquires adaptation coefficients for a plurality of sections included in the moving route indicated by the route information, with reference to an adaptation coefficient storage unit (206) that stores automatic driving adaptation coefficients set for the respective sections. Further, the automatic driving section determination unit (204) determines the automatic driving sections of the mobile body in the moving route, based on the acquired adaptation coefficients.

The disclosed technology provides solutions for facilitating the selection of a parking space by a user of a parking application. A process of the disclosed technology can include steps for monitoring sensor data and location data associated with a user device, retrieving, based on the location data associated with a user device, listing data associated with one or more parking spaces in a vicinity of the user device, and capturing image data that includes at least a portion of the one or more parking spaces. In some aspects, the process may further include steps for overlaying one or more graphical objects onto the image data, wherein the one or more graphical objects are based on the listing data associated with the one or more parking spaces. Systems and machine-readable media are also provided.

One variation of a method for accessing supplemental data from other vehicles includes, at an autonomous vehicle: recording a scan image of a scene around the autonomous vehicle at a first time; detecting insufficient perception data in a region of the scan image; in response to detecting insufficient perception data in the region, defining a ground area of interest containing the region and wirelessly broadcasting a query for perception data representing objects within the ground area of interest; in response to receiving supplemental perception data—representing objects within the ground area of interest detected by the second vehicle at approximately the first time—from a second vehicle proximal the scene, incorporating the supplemental perception data into the scan image to form a composite scan image; selecting a navigational action based on objects in the scene represented by the composite scan image; and autonomously executing the navigational action.

Location technologies are combined with other information systems to provide augmented information for individuals such as a traveler in an automobile.

An example method of providing an at least partially automatic driving function and/or a personalized function in a motor vehicle as well as to the motor vehicle may include establishing a communication link between a communication interface of the motor vehicle and a communication interface of a mobile terminal, which is associated with a user of the motor vehicle; receiving terminal data transferred via the communication link in the motor vehicle, which is recorded on the mobile terminal and which describes at least navigation information and/or user information relating to the user; and providing an at least partially automatic driving function of a driver assistance system of the motor vehicle and/or a personalized function in the motor vehicle by evaluating the received terminal data.

An electronic device may include a magnetic sensor and at least one processor operatively connected with the magnetic sensor, wherein the at least one processor may be configured to: collect a plurality of pieces of path data based on first magnetic data related to a plurality of movements of the electronic device, by using the magnetic sensor; identify a plurality of pieces of second magnetic data, which have at least a predetermined level of mutual similarity, from among the plurality of pieces of path data; determine, to be an intersection area related to the plurality of movements of the electronic device, an area range in which the plurality of pieces of second magnetic data are collected; determine, on the basis of the intersection area, a first space and a second space related to the plurality of movements of the electronic device; and determine, on the basis of the third magnetic data acquired by using the magnetic sensor, the space in which the electronic device is located from among the first space and the second space.

Techniques for determining a location and type of traffic-related features and using such features in route planning are discussed herein. The techniques may include determining that sensor data represents a feature such as a traffic light, road segment, building type, and the like. The techniques further include determining a cost of a feature, whereby the cost is associated with the effect of a feature on a vehicle traversing an environment. A feature database can be updated based on features in the environment. A cost of the feature can be used to update costs of routes associated with the location of the feature.

Among other things, stored data is maintained indicative of potential stopping places that are currently feasible stopping places for a vehicle within a region. The potential stopping places are identified as part of static map data for the region. Current signals are received from sensors or one or more other sources current signals representing perceptions of actual conditions at one or more of the potential stopping places. The stored data is updated based on changes in the perceptions of actual conditions. The updated stored data is exposed to a process that selects a stopping place for the vehicle from among the currently feasible stopping places.