A method, apparatus and computer program product are provided for generating structured trajectories based on probe data for simulating traffic flow. Methods include: receiving a plurality of sequences of probe data points; identifying splitting points in each of the plurality of sequences representing points where a respective sequence is split and decomposed into a plurality of legs; identifying the plurality of legs between pairs of splitting points; grouping legs according to a hierarchical optimizer into bunches of legs; determining, from the bunches of legs, a map representation of a road network; composing bunches of legs into a directed graph based on leg continuations, where the directed graph is formed by bunches of legs connected to continuation bunches of legs, and graph nodes of the directed graph represent intersection decision points; and simulating a condition including traffic flow within the road network based on decisions made at the intersection decision points.

An apparatus, a method and a computer program product are provided for updating link information on a client device. The method may include determining at least one map area comprising one or more links, the map area having at least one map area identifier, Sending to a data service, a request for at least one categorized link. Receiving, from the data service, at least one bloom filter, the at least one bloom filter encoding the at least one categorized link, determining one or more link identifiers for the one or more links in the map area and associating candidate link of the one or more links to the at least one categorized link, based on the link identifier of the at least one candidate link satisfying the at least one received bloom filter, to update the link information on the client device.

A vehicle, system and method of navigating the vehicle. The system includes a sensor and a processor. The sensor is configured to obtain a first set of detection points representative of a lane of a road section at a first time step and a second set of detection points representative of the lane at a second time step. The processor is configured to determine a set of predicted points for the second time step from the first set of detection points, obtain a set of fused points from the second set of detection points and the set of predicted points, and navigate the vehicle using the set of fused points.

A processing apparatus for traffic management of a network of roads is provided, to, generate, based on journey data sets, first count data indicative of a first count of the road users travelling on an incoming road leading to the intersection node, and second count data indicative of a second count of the road users travelling on an outgoing road of at least two outgoing roads, each outgoing road leading away from the intersection node, generate result data indicative of a result that is determined based on the first count and the second count, if the result satisfies a condition for restriction, generate restriction data indicative of a restriction of traffic from the incoming road to the outgoing road via the intersection node, and generate, based on an angular relationship between the outgoing road and the incoming road, type data indicative of a type of the restriction.

Aspects of the disclosure relate to generating map data. For instance, data generated by a perception system of a vehicle may be received. This data corresponds to a plurality of observations including observed positions of a passenger of the vehicle as the passenger approached the vehicle at a first location. The data may be used to determine an observed distance traveled by a passenger to reach a vehicle. A road edge distance between an observed position of an observation of the plurality of observations and a nearest road edge to the observed position may be determined. An inconvenience value for the first location may be determined using the observed distance and the road edge distance. The map data is then generated using the inconvenience value.

A map update controller of a map data management apparatus predicts meshes whose pieces of map data will be requested from a map application, and identifies meshes whose pieces of map data stored in the map database are not latest as update-necessary meshes, from among the predicted meshes whose pieces of map data will be requested. The map update controller performs a first map update process of immediately updating pieces of map data of the update-necessary meshes when the pieces of map data of the update-necessary meshes can be updated before the map application requests the pieces of map data of the update-necessary meshes, and performs a second map update process of updating the pieces of map data of the update-necessary meshes at the timing that an operation of the map application satisfies a predefined condition when the pieces of map data cannot be updated.

Provided are a road network extraction method, a device, and a storage medium, which relate to the technical field of artificial intelligence and, in particular, to the fields of image processing, computer vision, and the like and are specifically applicable to scenarios such as intelligent transportation and a smart city. A specific implementation scheme includes: extracting a first road network of a target region according to user trajectories of the target region; extracting a second road network of the target region according to a satellite aerial image of the target region; and extract a target road network of the target region according to the first road network, the second road network, and the user trajectories. Efficient and accurate road network extraction can be achieved through techniques in embodiments of the present disclosure.

A method is provided for generation of map geometry through rasterization of probe data over time, where the generated map geometry can be used for map element generation. Methods may include: receiving probe data from a plurality of probe apparatuses within a geographic area where the probe data includes location information and time information; rasterizing the received probe data to generate an image corresponding to the probe data associated with the geographic area, where each pixel of the image includes a property representing at least one component of the probe data; processing the image to obtain one or more map elements; and updating a map database with the one or more map elements.

A method is provided to using a generative adversarial network to generate map geometry from images representing probe data. Methods may include: receiving a rasterized image representative of probe data within a geographic area, where each pixel of the rasterized image includes a property representing at least one component of the probe data; generating a prediction image of road features within the geographic area using a generative adversarial network based on trained model parameters and the rasterized image; determining one or more map elements based, at least in part, on the prediction image and georeferenced locations of the road features within the prediction image; and updating a map of the geographic area with one or more map elements.

A method is provided automatically creating map geometry from data from various sources gathered within a geographical area using data aggregation and conflation with statistical analysis. Methods may include: receiving observation data associated with a geographic area; rasterizing objects within the observation data onto corresponding channels in a raster image corresponding to the geographic area having a given resolution; determining a distribution of locations of the objects parameterized by values in different channels in the raster image from the observation data; extracting analytic geometries from the raster image; generating map geometry based on the extracted analytic geometries; and updating a map database with the generated map geometry.