Abstract: A processing apparatus for generating route navigation data is provided, to, generate training data based on road network data corresponding to a network of roads in a defined geographical area, and journey data sets, each journey data set comprising data indicative of a journey by a road user through the network of roads and being derived using geolocation transmissions from a communications device of the road user, train a classifier model based on the training data, apply the trained classifier model on road data corresponding to a road in the defined geographical area, for the trained classifier model to predict a direction of traffic flow on the road, and generate the route navigation data indicative of the predicted direction of the traffic flow on the road. A method for generating route navigation data is also provided.

Abstract: Aspects concern a method for predicting the destination location of a vehicle, comprising processing a local preference graph of a user of the vehicle having nodes corresponding to locations visited before by the user by a first graph neural network, processing one or more of a spatial graph representing information about geographical proximity of locations, a temporal graph representing information about locations which have been visited one after another by users and the time between the visits of the locations and a preference graph representing information about locations which have been visited one after another and the frequency of visits of the locations by a second graph neural network, combining the result of the processing by the first graph neural network and the result of the processing by the second graph neural network by at least one neural network layer and using the output of the at least one neural network layer as prediction of the destination location.

Abstract: A method, a computer-readable medium, and an apparatus for transport service are provided. The apparatus may receive a plurality of transport service transactions associated with a point of interest entity. For each transport service transaction, the apparatus may determine a transport service location at which the transport service transaction is executed. The apparatus may cluster the transport service locations determined for the plurality of transport service transactions. The apparatus may determine one or more candidate transport service locations for the point of interest entity based on the clustering. The apparatus may provide the one or more candidate transport service locations to a client or a service provider associated with a transport service transaction that is to be executed at the point of interest entity.

Abstract: A method of predicting one or more road segment attributes corresponding to a road segment in a geographical area, the method including: providing trajectory data and satellite image of the geographical area; calculating one or more image channels based on the trajectory data; and using at least one processor, classi-fying the road segment based on the one or more image channels and the satellite image using a trained classifier into prediction probabil-ities of the road attributes A data processing system including one or more processors configured to carry out a the method of predicting road attributes. A computer executable code including instructions for predicting one or more road segment attributes according to the method.

Abstract: A processing apparatus for generating route navigation data is provided, to, generate training data based on road network data corresponding to a network of roads in a defined geographical area, and journey data sets, each journey data set comprising data indicative of a journey by a road user through the network of roads and being derived using geolocation transmissions from a communications device of the road user, train a classifier model based on the training data, apply the trained classifier model on road data corresponding to a road in the defined geographical area, for the trained classifier model to predict a direction of traffic flow on the road, and generate the route navigation data indicative of the predicted direction of the traffic flow on the road. A method for generating route navigation data is also provided.

Abstract: A method, a computer-readable medium, and an apparatus for transport service are provided. The apparatus may receive a plurality of transport service transactions associated with a point of interest entity. For each transport service transaction, the apparatus may determine a transport service location at which the transport service transaction is executed. The apparatus may cluster the transport service locations determined for the plurality of transport service transactions. The apparatus may determine one or more candidate transport service locations for the point of interest entity based on the clustering. The apparatus may provide the one or more candidate transport service locations to a client or a service provider associated with a transport service transaction that is to be executed at the point of interest entity.

Abstract: A method of predicting one or more road segment attributes corresponding to a road segment in a geographical area, the method including: providing trajectory data and satellite image of the geographical area; calculating one or more image channels based on the trajectory data; and using at least one processor, classifying the road segment based on the one or more image channels and the satellite image using a trained classifier into prediction probabilities of the road attributes A data processing system including one or more processors configured to carry out a the method of predicting road attributes. A computer executable code including instructions for predicting one or more road segment attributes according to the method.

Abstract: A processing apparatus is provided, to, for each candidate point-of-interest of at least one candidate point-of-interest identified for association with a road in a network of roads for determining a name for the road, generate first data indicative of a relationship relating to a distance between the candidate point-of-interest and a road segment of the road, generate second data indicative of a relationship between the road segment and a projection of the candidate point-of-interest in a direction of the road segment, and, if the first and second relationships satisfy a first and second conditions for association respectively, generate data indicative of the candidate point-of-interest being an associated point-of-interest, process data corresponding to the associated point-of-interest to extract name data indicative of a road name associated with the associated point-of-interest, and generate, based on the name data, data indicative of the name for the road.

Abstract: 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.

Abstract: Disclosed are systems and methods for predicting the destination location of a vehicle by processing a local preference graph of a user of the vehicle having nodes corresponding to locations visited by the user. In some embodiments, information about locations which have been visited one after another by users and the time between visits of the locations are also used in the prediction.

Abstract: A method for generating map data comprising training a generator neural network by acquiring training data elements and training a generative adversarial network, comprising training a generator neural network to generate, for a satellite image and a road usage image of a training data element, the map data image of the training data element and comprising generating map data for a geographical region by acquiring road usage information specifying which parts of a geographical area have been used for driving a vehicle, acquiring a satellite image of the geographical area, forming a road usage image of the geographical area which has pixels, each pixel corresponding to a respective part of the geographical area and having a value indicating whether its part of the geographical area is specified by the road usage information to have been used; and feeding the satellite image and the road usage image to the trained generator neural network.

Abstract: A method of predicting one or more road segment attributes corresponding to a road segment in a geographical area, the method including: providing trajectory data and satellite image of the geographical area; calculating one or more image channels based on the trajectory data; and using at least one processor, classifying the road segment based on the one or more image channels and the satellite image using a trained classifier into prediction probabilities of the road attributes A data processing system including one or more processors configured to carry out a the method of predicting road attributes. A computer executable code including instructions for predicting one or more road segment attributes according to the method.

Abstract: Aspects concern a method for predicting the destination location of a vehicle, comprising processing a local preference graph of a user of the vehicle having nodes corresponding to locations visited before by the user by a first graph neural network, processing one or more of a spatial graph representing information about geographical proximity of locations, a temporal graph representing information about locations which have been visited one after another by users and the time between the visits of the locations and a preference graph representing information about locations which have been visited one after another and the frequency of visits of the locations by a second graph neural network, combining the result of the processing by the first graph neural network and the result of the processing by the second graph neural network by at least one neural network layer and using the output of the at least one neural network layer as prediction of the destination location.

Abstract: A processing apparatus for generating route navigation data is provided, to, generate training data based on road network data corresponding to a network of roads in a defined geographical area, and journey data sets, each journey data set comprising data indicative of a journey by a road user through the network of roads and being derived using geolocation transmissions from a communications device of the road user, train a classifier model based on the training data, apply the trained classifier model on road data corresponding to a road in the defined geographical area, for the trained classifier model to predict a direction of traffic flow on the road, and generate the route navigation data indicative of the predicted direction of the traffic flow on the road. A method for generating route navigation data is also provided.

Abstract: A method, data processing apparatus, and computer code for identifying road intersections includes providing location data obtained from at least one vehicle's trajectory, wherein the location data may include geographical data within a geographical perimeter. The method includes determining node vectors by applying a geographical descriptor model on a target location included in the geographical perimeter. The geographical descriptor model includes a plurality of multiscale node descriptors including a target multiscale descriptor and neighboring multiscale descriptors. Each of the plurality of multiscale node descriptors includes at least two shape descriptors of different geographical resolution. Each of the neighboring locations is at a respective geographical distance from the target location. The node vectors may be respectively determined for each of the plurality of multiscale node descriptors.

Abstract: A processing apparatus for traffic management of a network of roads is provided, to, process data corresponding to the network of roads to identify an incoming road and an outgoing road intersecting at an intersection node of the network, the incoming road being for incoming traffic leading to the intersection node and the outgoing road being for outgoing traffic leading away from the intersection node, determine, based on the data corresponding to the network, whether there is a bypass road to allow the incoming traffic from the incoming road to bypass the intersection node and flow to the outgoing road via the bypass road, and, if it is determined that there is the bypass road, generate data indicative of a turn restriction for communicating to road users of restriction of flow of the incoming traffic to the outgoing road via the intersection node.

Abstract: A processing apparatus is provided, to, for each candidate point-of-interest of at least one candidate point-of-interest identified for association with a road in a network of roads for determining a name for the road, generate first data indicative of a relationship relating to a distance between the candidate point-of-interest and a road segment of the road, generate second data indicative of a relationship between the road segment and a projection of the candidate point-of-interest in a direction of the road segment, and, if the first and second relationships satisfy a first and second conditions for association respectively, generate data indicative of the candidate point-of-interest being an associated point-of-interest, process data corresponding to the associated point-of-interest to extract name data indicative of a road name associated with the associated point-of-interest, and generate, based on the name data, data indicative of the name for the road.

Abstract: Communications server apparatus (102) for generating navigable map data comprises a processor (116) and a memory (118), and is configured, under control of the processor, to execute instructions (120) stored in the memory: to generate a series (340) of journey trace data sets (338), each journey trace data set comprising data representing a user journey (310), each journey trace data set being derived using geolocation transmissions (318) from a communications device (104, 106) of a user (308) undertaking the user journey; to aggregate the series of journey trace data sets to generate route image data comprising data representing a network of navigable routes; and to generate, from the route image data, the navigable map data, the navigable map data comprising data representing a series of geolocations corresponding to the network of navigable routes.

Abstract: The disclosure relates to a method of predicting one or more road attributes. The method may include providing trajectory data of a geographical area. The method may further include providing map data, wherein the map data may include image data of the geographical area. The method may further include extracting trajectory features from the trajectory data and extracting map features from the map data. The method may further include using at least one processor to predict road attributes by inputting the trajectory features and the map features in a neural network and by classifying an output of the neural network into prediction probabilities of the road attributes. The disclosure also relates to a data processing system; to a non-transitory computer-readable medium storing computer executable code; and to a method of training an automated predictor.

Abstract: A method, data processing apparatus, and computer code for identifying road intersections includes providing location data obtained from at least one vehicle's trajectory, wherein the location data may include geographical data within a geographical perimeter. The method includes determining node vectors by applying a geographical descriptor model on a target location included in the geographical perimeter. The geographical descriptor model includes a plurality of multiscale node descriptors including a target multiscale descriptor and neighboring multiscale descriptors. Each of the plurality of multiscale node descriptors includes at least two shape descriptors of different geographical resolution. Each of the neighboring locations is at a respective geographical distance from the target location. The node vectors may be respectively determined for each of the plurality of multiscale node descriptors.