A vehicle control device can include a memory; and a processor to generate driving information including information of driving the vehicle in a manual driving mode from a first point to a second point in a preset manner based on traffic regulations stored in the memory, store the driving information in the memory, and drive the vehicle in an autonomous driving mode based on the driving information stored in the memory.

Systems and methods are provided for constructing, using, and updating the sparse map for autonomous vehicle navigation. A method may comprise processing, by a mapping server, collected navigation information from a plurality of vehicles obtained by sensors coupled to the plurality of vehicles, wherein the navigation information describes road lanes of a road segment; collecting data about landmarks identified proximate to the road segment, the landmarking including a traffic sign; generating, by the mapping server, an autonomous vehicle map for the road segment, wherein the autonomous vehicle map includes a spline corresponding to a lane in the road segment and the landmarks identified proximate to the road segment; and distributing, by the mapping server, the autonomous vehicle map to an autonomous vehicle for use in autonomous navigation over the road segment.

Systems and methods are provided for constructing, using, and updating the sparse map for autonomous vehicle navigation. A system may comprise a processor and a memory. The memory may include instructions, which when executed on the processor, cause the processor to initiate identification of a landmark based on images from multiple vehicles, the landmark including a traffic sign, fuse the landmark with an existing map to produce an updated map, and distribute the updated map to a plurality of vehicles for use in autonomous operation.

An automatic driving control apparatus includes a controller. Upon execution of automatic driving control, the controller determines, on the basis of positioning and map information, presence of a tollgate within a predetermined distance from a vehicle. The controller makes a transition to a tollgate passing mode, on a condition that the presence of the tollgate is determined within the predetermined distance and an increase in width of the road is recognized on the basis of the recognition of the outside environment. The controller causes the vehicle to approach the tollgate, on the basis of one or both of the map information and position information of an object recognized on the basis of the recognition of the outside environment, in a first period of time during which the tollgate passing mode is set and a position of the tollgate is unrecognizable on the basis of the recognition of the outside environment.

A vehicle control device including a communication unit configured to obtain a current position of a vehicle; a sensing unit configured to sense another vehicle subject to a driving regulation and obtain current position of the other vehicle; a processor; and a computer-readable medium coupled to the processor having stored thereon instructions which, when executed by the processor, causes the processor to perform operations including autonomously driving the vehicle based on the respective current positions of the vehicle and the other vehicle in compliance with the driving regulation.

Systems and methods are provided for navigating a vehicle using a crowdsourced sparse map. In one implementation, a method of autonomously navigating a vehicle along a road segment may include receiving a sparse map model, receiving at least one image representative of an environment of the vehicle, analyzing the sparse map model and the at least one image, and determining an autonomous navigational response for the vehicle based on the analysis of the sparse map model and the at least one image. The at least one image may be received from a camera, and the sparse map model may include at least one line representation of a road surface feature extending along the road segment, each line representation representing a path along the road segment substantially corresponding with the road surface feature.

A vehicle travel control device controls travel of a vehicle toward a target stop position. Travel state information indicates a travel state of the vehicle and includes vehicle position information indicating positions the vehicle and each wheel. Difference-in-level position information indicates a position of a difference-in-level on a travel path. The vehicle travel control device determines whether the vehicle goes beyond the target stop position when a subject wheel of the vehicle passes the difference-in-level, based on the difference-in-level position information and the vehicle position information. When determining that the vehicle goes beyond the target stop position, the vehicle travel control device changes the target stop position so as to prevent the subject wheel from passing the difference-in-level, or generates a braking force to stop the vehicle before the subject wheel passes the difference-in-level.

An autonomous parking control device executes vehicle traveling control that calculates a command value of a propulsive force based on an operating state, and moves the vehicle to a target position autonomously by controlling a propulsive force generating device in accordance with the command value. The control device executes an additional command value varying process of adding a predetermined additional command value to the command value when the vehicle stops due to the propulsive force being insufficient during the vehicle traveling control, and decreasing or keeping the additional command value by a predetermined degree of suppression, when the vehicle which is stopped is started. Here, when executing the additional command value varying process in the first position far from the target position, the degree of suppression is set to be smaller as compared with a case of executing the process in a second position close to the target position.

An obstacle avoidance reminding method includes: performing ground detection based on acquired image data to acquire ground information of a road; performing passability detection based on the acquired ground information, and determining a traffic state of the road; if it is determined that the road is impassable, performing road condition detection for the road to acquire a first detection result, and performing obstacle detection for the road to acquire a second detection result; and determining obstacle avoidance reminding information based on the first detection result and the second detection result.

Aspects of the present disclosure describe systems, methods, and devices for automated vehicular control based on glare detected by an optical system of a vehicle. In some aspects, automated control includes controlling the operation of the vehicle itself, a vehicle subsystem, or a vehicle component based on a level of glare detected. According to some examples, controlling the operation of a vehicle includes instructing an automatically or manually operated vehicle to traverse a selected route based on levels of glare detected or expected along potentials routes to a destination. According to other examples, controlling operation of a vehicle subsystem or a vehicle component includes triggering automated responses by the subsystem or the component based on a level of glare detected or expected. In some additional aspects, glare data is shared between individual vehicles and with a remote data processing system for further analysis and action.