A system for mapping a lane mark for use in autonomous vehicle navigation is provided. The system includes at least one processor programmed to: receive two or more location identifiers associated with a detected lane mark; associate the detected lane mark with a corresponding road segment; update an autonomous vehicle road navigation model relative to the corresponding road segment based on the two or more location identifiers associated with the detected lane mark; and distribute the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles.

Disclosed is an electronic device. An electronic device according to one embodiment may comprise: a communication module; a sensor module which acquires movement information of the electronic device and image information of the place where the electronic device is moving; a memory which stores space information corresponding to the place where the electronic device is moving; and a processor which uses the movement information and space information to determine a plurality of first candidate locations, within the place, corresponding to the electronic device, and then, on the basis of the image information and the plurality of first candidate locations, determines whether the location accuracy corresponding to the plurality of first candidate locations is smaller than a valid value, and, on the basis of the result of the determination, uses the electronic device or an external server to acquire at least one second candidate location from among the plurality of first candidate locations, and uses the acquired at least one second candidate location to determine an estimated location for the electronic device.

A system for mapping a lane mark for use in autonomous vehicle navigation is provided. The system includes at least one processor programmed to receive two or more location identifiers associated with a detected lane mark, associate the detected lane mark with a corresponding road segment, update an autonomous vehicle road navigation model relative to the corresponding road segment based on the two or more location identifiers associated with the detected lane mark, and distribute the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles.

Systems and methods for processing at least one service request for an on-demand service are provided. The systems may perform the methods to obtain a plurality of example service orders, each example service order of the plurality of example service orders may include a feature associated with a section of a plurality of sections of a measurement; cluster the plurality of example service orders into a plurality of subsets of example service orders, the feature of each example service order in a same subset of example service orders may be associated with a same section of the measurement; for each of the plurality of subsets of example service orders, train a first model of estimated time of arrival (first ETA model) using the subset of example service orders; and store structured data in the at least one storage medium encoding the plurality of first ETA models.

A system for mapping traffic lights and for determining traffic light relevancy for use in autonomous vehicle navigation. The system may include at least one processor programmed to: receive at least one location identifier associated with a traffic light; receive a state identifier associated with the traffic light; receive navigational information indicative of one or more aspects of motion of the first vehicle along the road segment, and determine, based on the navigational information, a lane of travel traversed by the first vehicle along the road segment. The processor may also determine whether the traffic light is relevant to the lane of travel traversed by the first vehicle; update an autonomous vehicle road navigation model relative to the road segment; and distribute the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles.

A method for forming a localization layer for a digital localization map for automated driving. The method includes: providing the localization layer for a defined region; providing a planning layer for the region; and extracting alignment features from the localization layer that is provided for an alignment with the planning layer, the alignment features being extracted in such a way from the localization layer that an inadmissible deformation of the localization layer may be recognized during the alignment of the planning layer with the localization layer.

A system for vehicle navigation is provided. The system includes at least one processing circuitry programmed to receive via a data interface one or more images captured by one or more cameras representative of an environment of a vehicle, identify, based on analysis of the one or more images, at least one direction of at least one directional arrow on a road surface in the one or more images, determine a direction of travel for the vehicle based on the at least one direction of the at least one directional arrow on the road surface, determine at least one navigational action for the vehicle based on the determined direction of travel for the vehicle, and cause one or more actuator systems of the vehicle to implement the determined at least one navigational action for the vehicle.

A control system is configured to receive a first signal indicative of a current position of a vehicle and a second signal indicative of a desired path for the vehicle. The control system is configured to calculate a virtual path between the current position and a target position on the desired path and to output a third signal indicative of curvature command corresponding to an initial curvature of the virtual path to cause a steering control system of the vehicle to adjust a steering angle of the vehicle. The control is also configured to iteratively receive an updated current position, receive any updates to the desired path, calculate an updated target position, calculate an updated virtual path based on the updated current position and updated desired path, and output an updated curvature command corresponding to a respective initial curvature of the updated virtual path as the vehicle travels across a surface.

A field traveling route production system includes: a field information storage section that stores field information including position information each of a field and an entrance/exit area of the field; a work traveling route calculation section (61) that calculates a work traveling route for the field work vehicle based on the field information and specification of the field work vehicle, the work traveling route interconnecting a traveling work starting point and a traveling work ending point; a fore traveling route calculation section (62) that calculates a fore traveling route extending from the entrance/exit area to the traveling work starting point of the work traveling route; and a post traveling route calculation section (63) that calculates a post traveling route extending from the traveling work ending point to the entrance/exit area.

A location estimation device includes an external sensor, a storage to store partial environmental maps including first and second partial environmental maps linked to each other based on a coordinate transformation relationship, and a location estimator to match scan data received from the external sensor against the partial environmental map so as to estimate the location and attitude of the vehicle. Upon movement of the estimated location of the vehicle from a location on the first partial environmental map to a location on the second partial environmental map, the location estimator determines, in accordance with the coordinate transformation relationship, a corresponding location and a corresponding attitude on the second partial environmental map that are associated with the estimated location and estimated attitude of the vehicle on the first partial environmental map, corrects, in accordance with a history of estimated locations and estimated attitudes of the vehicle on the first partial environmental map, the corresponding location and corresponding attitude on the second partial environmental map at a point of timing when matching to estimate the location and attitude of the vehicle on the second partial environmental map starts, and executes the matching by using, as initial values, the corresponding location and corresponding attitude that have been corrected.