An apparatus, method and computer program product provide a map layer of one or more temporary dynamic obstructions. For example, the apparatus is configured to receive vehicle/driver behavior data associated with a vehicle at a portion of a road, determine a likelihood of a temporary dynamic obstruction existing proximate to the portion based on the vehicle behavior data, and update a datapoint of a map layer based on the likelihood. The datapoint indicates a state of existence of the temporary dynamic obstruction at the portion.

Techniques for generating and validating map data that may be used by a vehicle to traverse an environment are described herein. The techniques may include receiving sensor data representing an environment and receiving map data indicating a traffic control annotation. The traffic control annotation may be associated, as projected data, with the sensor data based at least in part on a position or orientation associated with a vehicle. Based at least in part on the association, the map data may be updated and sent to a fleet of vehicles. Additionally, based at least in part on the association the vehicle may determine to trust the sensor data more than the map data while traversing the environment.

A travel road determination apparatus includes a vehicle position acquisition unit and a travel road determination unit. The vehicle position acquisition unit acquires position information of a vehicle. In first determination processing, the travel road determination unit determines whether or not the vehicle that is determined to be traveling on a first-type road based on first position information of the vehicle has started traveling on a second-type road, based on second position information of the vehicle and first map data. In second determination processing, the travel road determination unit determines whether or not the vehicle that is determined to be traveling on the second-type road based on third position information of the vehicle has started traveling on the first-type road, based on fourth position information of the vehicle and the second map data.

Provided are a method for constructing a three-dimensional map in a high-definition map, a device and a storage medium. The method includes: acquiring vehicle trajectory data, where the vehicle trajectory data is three-dimensional trajectory data; matching the vehicle trajectory data with a lane in a two-dimensional map and determining vehicle trajectory data matched with the lane; and assigning a height to the lane in the two-dimensional map according to the matched vehicle trajectory data to obtain a three-dimensional map.

Systems and methods of processing crowdsourced navigation information for use in autonomous vehicle navigation are disclosed. A method may include processing, by a mapping server, crowdsourced 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.

The present disclosure is related to generating map data explicitly indicating a total drivable surface, which may include multiple types of drivable surfaces. For instance, a given portion of a map may include map data indicating a combination of various drivable surfaces, such as road segments, lane properties, intersections, parking areas, shoulders, driveways, etc. Examples of the present disclosure join these different types of drivable surfaces into combined map data that explicitly indicates a total drivable surface, such as a perimeter boundary indicating or representing a transition from a drivable surface to a non-drivable surface. The map data indicating the total drivable surface may be searched to determine information related to a drivable surface boundary, such as location and type. This boundary information may be used in various contexts, such as when planning a trajectory or remotely controlling a vehicle.

A navigation service generates a route for navigating from a route origin to a route destination using a private roads repository. A ghost road is along the route, and a ghost origin and a ghost destination of the ghost road is identified. Using an application programming interface of a base roads engine, a request for a route is sent from the ghost origin to the ghost destination. From the base roads engine and in response to the request, a replacement section from the ghost origin to the ghost destination is received. The ghost road is replaced with the replacement section to create an updated route, which is presented.

Even when there is a plurality of road surface states within one geographical range or when there is a local road surface state, a road surface state is estimated with accuracy. Included are an aggregation unit (13, 15) that aggregates, on a per predetermined geographical unit basis, results of estimating road surface states using sensor data collected in advance for each of geographical ranges and including positional information obtained during travel of a moving object, the aggregation being based on the positional information, and an estimation unit (17) that estimates the road surface state for each of the geographical ranges and based on the estimation results aggregated by the aggregation unit.

Disclosed herein are systems, methods, and computer program products for object detection. The methods comprise performing the following operations by a computing device: obtaining an image that comprises a plurality of layers superimposed on each other; identifying a center point of a robot on a map; selecting a portion of the map contained in a geometric shape overlaid on the map so as to have a center set to the center point of the robot; obtaining map information associated with the selected portion of the map; generating at least one additional layer using the map information; superimposing the at least one additional layer onto the image to generate a modified image; and performing an object detection algorithm to detect at least one object in the modified image.

A method for generating a three-dimensional (3D) lane model, the method including calculating a free space indicating a driving-allowed area based on a driving image captured from a vehicle camera, generating a dominant plane indicating plane information of a road based on either or both of depth information of the free space and a depth map corresponding to a front of the vehicle, and generating a 3D short-distance road model based on the dominant plane.