Abstract: A traffic adjustment or a traffic command, for example, is based on data congestion on a cellular network. Position data is received from a mobile device. A portion of a cellular network that corresponds to the position data is selected. The portion of the cellular network may be the geographic area covered by a cell. The network state of the portion of the cellular network is identified. A traffic device is also identified. The traffic device may be a traffic light or a variable speed sign. The traffic adjustment or traffic command for the traffic device is calculated based on the network state.

Abstract: A method is provided that includes: receiving a plurality of estimated position points, each estimated position point including a timestamp, where each estimated position point is an estimate of a position of a vehicle at a time respective timestamp; receiving on or more path events, where each of the one or more path events includes a timestamp and data from at least one sensor of the vehicle; generating a path from the plurality of estimated position points, where the estimated position points are arranged in order of ascending time represented by the respective timestamp; and interpolating between two of the estimated position points to determine a location corresponding to one of the one or more path events, where the timestamp of the one of the one or more path event corresponds to a time that is between the times represented by the timestamps of the two estimated position points.

Abstract: An approach is provided for constructing a delivery path that enables a UAV to safely access a delivery surface and avoids restricted access surfaces from the open sky. The approach involves determining at least one delivery path to at least one delivery surface, wherein the delivery path represents at least one three-dimensional variable width path along which an aerial delivery vehicle can access the at least one delivery surface. The approach also involves transecting the delivery path with one or more planar surfaces. The approach further involves determining one or more shapes on the one or more planar surfaces, wherein the one or more shapes represent one or more intersections of the delivery path and the one or more planar surfaces. The approach also involves constructing at least one delivery path data object comprising at least one ordered list of the one or more shapes to represent the delivery path.

Abstract: Systems, apparatuses, and methods are provided for developing a fingerprint database and selecting feature geometries for determining the geographic location of a device. A device collects a depth map at a location in a path network. Two-dimensional feature geometries from the depth map are extracted using a processor of the device. The extracted feature geometries are ranked to provide ranking values for the extracted feature geometries. A portion of the extracted feature geometries are selected based upon the ranking values and a geographic distribution of the extracted feature geometries.

Abstract: Systems, apparatuses, and methods are provided for developing a fingerprint database and extracting feature geometries for determining the geographic location of an end-user device. A device collects, or a processor receives, a depth map of a location in a path network. A physical structure is identified within the depth map. The depth map is divided, at the physical structure, into a horizontal plane at an elevation from the road level. A two-dimensional feature geometry is extracted from the horizontal plane of the depth map using a linear regression algorithm, a curvilinear regression algorithm, or a machine learning algorithm.

Abstract: A method, apparatus and computer program products are provided for automatically determining or fine-tuning bus service schedules for bus stops along a route. One example method includes causing reception of GPS data from a plurality of buses or uses from along a transit route, the GPS data comprised of a plurality of location points and associated temporal data, aggregating the location data by route and direction to determine a trip count, causing reception of at least one bus stop location, partitioning the associated temporal data into a number of clusters in accordance with the trip count, calculating a mean arrival time at the at least one bust stop for each cluster, and generating, using a processor, at least one service schedule for the at least one bus stop, wherein the mean arrival time of each cluster represents the service schedule.

Abstract: In one embodiment, a mobile device or a network device is configured to identify when a transit vehicle deviates from a transit path. The mobile device is configured to perform a positioning technique to generate data indicative of the location of a mobile device. Based on the location of the mobile device, a path is identified. The path is associated with an estimated path width based on the classification of the path and/or the accuracy of the positioning technique. A target route is calculated using the estimated path width. As the transit vehicle travels, the target route is compared to the location of the mobile device. If the mobile device and or transit vehicle deviates from the target route, a message is generated. The message may indicate that the transit vehicle is being re-routed and/or recommends the computation of a new path.

Abstract: Methods for providing a highly assisted driving (HAD) service include: (a) transmitting telematics sensor data from a vehicle to a remote first server; (b) transmitting at least a portion of the telematics sensor data from the remote first server to a remote second server, wherein the remote second server is configured to execute a HAD application using received telematics sensor data, and wherein the HAD application is configured to output a HAD service result; and (c) transmitting the HAD service result from the remote second server to a client. Apparatuses for providing a HAD service are described.

Abstract: In an embodiment, a system detects when vehicle bunching is about to occur or is already occurring within a given transit system. The system resolves the bunching using an event and tone based system which regulates the arrival and departure times of vehicles at vehicle stops. Also, an embodiment includes a method for receiving location information for a plurality of vehicles along a route, determining a relative distance between a first vehicle of the plurality of vehicles and at least a second vehicle of the plurality of vehicles as a function of the received location information, and generating an action signal for at least one of the plurality of vehicles located on the route, wherein the action signal is in response to the determined relative distance.

Abstract: A method, apparatus and computer program products are provided for automatically determining or fine-tuning bus service schedules for bus stops along a route. One example method includes causing reception of GPS data from a plurality of buses or uses from along a transit route, the GPS data comprised of a plurality of location points and associated temporal data, aggregating the location data by route and direction to determine a trip count, causing reception of at least one bus stop location, partitioning the associated temporal data into a number of clusters in accordance with the trip count, calculating a mean arrival time at the at least one bust stop for each cluster, and generating, using a processor, at least one service schedule for the at least one bus stop, wherein the mean arrival time of each cluster represents the service schedule.

Abstract: Systems, apparatuses, and methods are provided for determining the geographic location of an end-user device (e.g., vehicle, mobile phone, smart watch, etc.). An end-user device may collect a depth map at a location in a path network. Feature geometries may be obtained from a fingerprint database in proximity to the location in the path network. The depth map may be oriented with the feature geometries of the fingerprint. Control points from an extracted feature geometry in the depth map may be compared with control points within the fingerprint. Match rates may be calculated based on the comparison, and a geographic location of the end-user device may be determined when an overall match rate exceeds a minimum threshold value.

Abstract: An approach is provided for constructing a delivery path that enables a UAV to safely access a delivery surface and avoids restricted access surfaces from the open sky. The approach involves determining at least one delivery path to at least one delivery surface, wherein the delivery path represents at least one three-dimensional variable width path along which an aerial delivery vehicle can access the at least one delivery surface. The approach also involves transecting the delivery path with one or more planar surfaces. The approach further involves determining one or more shapes on the one or more planar surfaces, wherein the one or more shapes represent one or more intersections of the delivery path and the one or more planar surfaces. The approach also involves constructing at least one delivery path data object comprising at least one ordered list of the one or more shapes to represent the delivery path.

Abstract: Methods for providing a highly assisted driving (HAD) service include: (a) transmitting telematics sensor data from a vehicle to a remote first server; (b) transmitting at least a portion of the telematics sensor data from the remote first server to a remote second server, wherein the remote second server is configured to execute a HAD application using received telematics sensor data, and wherein the HAD application is configured to output a HAD service result; and (c) transmitting the HAD service result from the remote second server to a client. Apparatuses for providing a HAD service are described.

Abstract: Systems, apparatuses, and methods are provided for determining the geographic location of an end-user device (e.g., vehicle, mobile phone, smart watch, etc.). An end-user device may collect a depth map at a location in a path network. Feature geometries may be obtained from a fingerprint database in proximity to the location in the path network. The depth map may be oriented with the feature geometries of the fingerprint. Control points from an extracted feature geometry in the depth map may be compared with control points within the fingerprint. Match rates may be calculated based on the comparison, and a geographic location of the end-user device may be determined when an overall match rate exceeds a minimum threshold value.

Abstract: Systems, apparatuses, and methods are provided for developing a fingerprint database for and determining the geographic location of an end-user device (e.g., vehicle, mobile phone, smart watch, etc.) with the database. A fingerprint database may be developed by receiving a depth map for a location in a path network, and then identifying physical structures within the depth map. The depth map may be divided, at each physical structure, into one or more horizontal planes at one or more elevations from a road level. Two-dimensional feature geometries may be extracted from the horizontal planes. At least a portion of the extracted feature geometries may be encoded into the fingerprint database.

Abstract: An approach is provided for generating delivery data models for aerial package delivery. The approach involves determining at least one delivery surface data object to represent one or more delivery surfaces of at least one delivery location, wherein the one or more delivery surfaces represents at least one surface upon which to deliver at least one package. The approach further involves causing, at least in part, a creation of at least one complete delivery data model based, at least in part, on the at least one delivery surface data object to represent the at least one delivery location. The approach further involves causing, at least in part, an encoding of at least one geographic address in the at least one complete delivery data model to cause, at least in part, an association of the at least one complete delivery data model with at least one geographic location.

Abstract: An approach is provided for providing geographic delivery location for aerial package delivery. The approach involves determining building footprint information for at least one building associated with at least one geographic address. The approach also involves determining source data associated with the at least one building, the at least one geographic address, or a combination thereof. The approach further involves processing and/or facilitating a processing of the building footprint information and the source data to determine one or more entrances associated with the at least one building. The approach also involves processing and/or facilitating a processing of the source data associated with the one or more entrances to determine one or more delivery surfaces for the at least one geographic address.

Abstract: Systems, methods, and apparatuses are described for predicting the placement of road signs. A device receives data depicting road signs from multiple vehicles. The device analyzes a detected placement of the road signs and at least one characteristic of a collection of the data. The characteristic describes the road upon which the data was collected, an operation of the vehicle from which the data was collected, or an environment in which the data was collected. The device generates a model that associates values for the detected placement of the road signs with values for the at least one characteristic. The model may be later accessed to interpret subsequent sets of data describing one or more road signs.

Abstract: Systems, apparatuses, and methods are provided for developing a fingerprint database for and determining the geographic location of an end-user device (e.g., vehicle, mobile phone, smart watch, etc.) with the database. A fingerprint database may be developed by receiving a depth map for a location in a path network, and then identifying physical structures within the depth map. The depth map may be divided, at each physical structure, into one or more horizontal planes at one or more elevations from a road level. Two-dimensional feature geometries may be extracted from the horizontal planes. At least a portion of the extracted feature geometries may be encoded into the fingerprint database.

Abstract: A method, apparatus and computer program products are provided for automatically detecting specific locations, i.e. bus stops, stop lights, and/or traffic signals, based on received GPS reports. The method can also be adopted to detect the utilization of the specific locations along the route. One example method includes receiving GPS data from a plurality of buses from along a transit route, and utilizes a machine learning classification strategy that captures the mobility patterns of the GPS equipped buses, at specific locations. The method may then generate mini-clusters, each comprised of a first location point from a first route and one or more subsequent location points located within a predetermined distance of the first location point. The mobility patterns of the mini-clusters within larger clusters are represented as a normalized histogram where the bin values become classification features. A machine learning model is then utilized to determine a location of the specific locations.