Aspects of the disclosure relate providing a lane change notification when a vehicle is to perform a lane change. One or more computing devices may generate and display a video, where the video is generated from a perspective of a virtual camera at a default position and default pitch. The one or more computing devices may receive an indication that the vehicle is to perform a lane change from a first lane to a second lane and adjust, after the vehicle receives the indication, the default position and default pitch of the virtual camera to an updated position further above the vehicle relative to ground than the default position and an updated pitch directed more towards the ground than the default pitch. The video may be generated and displayed from the perspective of the virtual camera at the updated position and updated pitch.

A vehicle control device configured to perform control related to pickup and delivery by a vehicle. The vehicle is movable forward bi-directionally and includes package compartments on first and second sides. The vehicle control device is configured to perform operations including: acquiring position information of a target user point; acquiring position information of a target package compartment for storing a package to be delivered or picked up with respect to an advancing direction in which the vehicle travels toward the target user point; and outputting an instruction to reverse the advancing direction of the vehicle to a vehicle controller configured to perform traveling control of the vehicle in a case where a side of a side surface where the target package compartment is positioned and a side of the target user point with respect to the advancing direction of the vehicle do not coincide with each other.

Systems, methods, and autonomous vehicles for detecting road marking points from LiDAR data may obtain a LiDAR dataset generated by a LiDAR system; process, for each laser emitter of the LiDAR system, a point cloud associated with that laser emitter by: determining, for each point in the point cloud, based on a gradient of intensity at that point, whether that point corresponds to a gradient edge point; and determining, based on intensities of points in an interior segment of points between at least one candidate pair of gradient edge points and intensities of points in exterior segments of points outside the at least one candidate pair of gradient edge points, whether that candidate pair of gradient edge points corresponds to a road marking edge; and aggregate, from the processing of the plurality of point clouds, candidate pairs of gradient edge points determined to correspond to road marking edges.

Systems, methods, and autonomous vehicles for detecting road marking points from LiDAR data may obtain a LiDAR dataset generated by a LiDAR system; process, for each laser emitter of the LiDAR system, a point cloud associated with that laser emitter by: determining, for each point in the point cloud, based on a gradient of intensity at that point, whether that point corresponds to a gradient edge point; and determining, based on intensities of points in an interior segment of points between at least one candidate pair of gradient edge points and intensities of points in exterior segments of points outside the at least one candidate pair of gradient edge points, whether that candidate pair of gradient edge points corresponds to a road marking edge; and aggregate, from the processing of the plurality of point clouds, candidate pairs of gradient edge points determined to correspond to road marking edges.

A vehicle dispatch service boarding location determination method uses a vehicle dispatch information data server and a terminal to determine a boarding location for a dispatched vehicle based on a vehicle dispatch request from the terminal. When there is a vehicle dispatch request, position information of a vehicle dispatch request point is acquired. Boarding location candidates present in a periphery of the vehicle dispatch request point are calculated based on the position information point and map information. A boarding location recognition difficulty, which is a difficulty for the user in recognizing the boarding location candidate as a boarding location, is calculated for each of the boarding location candidates. A boarding location candidate for which the boarding location recognition difficulty is low among the boarding location candidates is determined as the boarding location where the user will be picked up by the dispatched vehicle.

In an automatic driving vehicle, traveling is continued in a case where a section in which a detailed map in which information required for automatic driving is recorded is not usable occurs during the traveling by the automatic driving. Automatic driving control means 100 for controlling automatic driving of a vehicle and map information holding means 601 for holding a detailed map including traveling lane information are provided. In a case where a section in which a detailed map newer than the detailed map held in the map information holding means 601 is not usable is in a traveling scheduled route, the automatic driving control means 100 continues to perform the automatic driving until a start point of the section is reached, using the detailed map held in the map information holding means 601.

In an automatic driving vehicle, traveling is continued in a case where a section in which a detailed map in which information required for automatic driving is recorded is not usable occurs during the traveling by the automatic driving. Automatic driving control means 100 for controlling automatic driving of a vehicle and map information holding means 601 for holding a detailed map including traveling lane information are provided. In a case where a section in which a detailed map newer than the detailed map held in the map information holding means 601 is not usable is in a traveling scheduled route, the automatic driving control means 100 continues to perform the automatic driving until a start point of the section is reached, using the detailed map held in the map information holding means 601.

Park monitoring methods, park monitoring systems, and computer-readable storage media are provided. A method includes: determining a first path from a current position of a first object to a first position; generating a 3D virtual image of a surrounding environment when the first object is moving along the first path based on a perspective of the first object; and when the first object is located at the first position, displaying a real image of the first position.

Park monitoring methods, park monitoring systems, and computer-readable storage media are provided. A method includes: determining a first path from a current position of a first object to a first position; generating a 3D virtual image of a surrounding environment when the first object is moving along the first path based on a perspective of the first object; and when the first object is located at the first position, displaying a real image of the first position.

Communication between autonomous vehicles, in 5G or 6G, is necessary for cooperative hazard avoidance and to coordinate the flow of traffic. However, before cooperative action, each vehicle must determine the wireless address of other vehicles in proximity, so that they can communicate directly with each other. Methods and systems disclosed herein include a computer-readable wireless “connectivity matrix”, an array of black and white squares showing a connectivity code. The connectivity code may be the vehicle's wireless address, an index code, or other information about the vehicle. The connectivity code may be an index in a tabulation of information that provides the wireless address, among other data. Other vehicles, or their cameras, may read the connectivity matrix, determine the code therein, and find the vehicle's wireless address. After determining the wireless address of the other vehicles, the vehicles can then communicate and cooperate to avoid accidents and facilitate the flow of traffic.