Abstract:
A method is provided herein for selecting a combination of a subset of weather stations from among a plurality of weather stations for estimating the weather at a specific location. The method may include: receiving an indication of a plurality of weather stations within a predefined area, where the predefined area includes a first location; determining, for each of the plurality of weather stations, a distance of the weather station from the first location; calculating, for a plurality of different combinations of subsets of the plurality of weather stations, an average distance of the weather stations of each of the plurality of different combinations from the first location; calculating, for each of the different combinations of subsets, an average location relative to the first location; and selecting a combination of a subset of the plurality of weather stations based on the average distance and the average location.
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:
Determination of route completion from wireless network data is presented. A recording is performed of data associated with wireless devices while traveling. The recording is compared to an expected recording of data associated with wireless networks along a route. Execution of the route is then proven based on the comparison.
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, 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:
Apparatuses and methods are provided for determining real time traffic conditions. A candidate road is divided into road segments by perpendicular bisectors. A spatial sliding window is positioned over at least a portion of a road segment, wherein the spatial sliding window corresponds to a front end of the road segment in a direction of travel of the road segment. Real time probe data is received from mobile devices in probe vehicles or on travelers of the at least portion of the road segment within the spatial sliding window. The real time probe data is analyzed, and a computer program assists in determining the real time traffic conditions of the at least portion of the road segment within the spatial sliding window. Based on the analysis, the real time traffic conditions are reported.
Abstract:
Dangerous driving events may be reported by detecting an occurrence of a dangerous event relating to the operation of a vehicle. A notification message of the dangerous event may be generated involving a time of occurrence of the dangerous event, a location of the dangerous event, and an event type of a plurality of event types for the dangerous event. The notification message may then be transmitted to communicate the occurrence dangerous driving event and information related to the dangerous driving event.
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:
Turn restrictions are identified and associated with an intersection. Geographic data is collected over a period of time from mobile devices located near the intersection. A geometric pattern is derived from the geographic data. A comparison between the geometric pattern and predefined geometric patterns associated with turn restrictions is performed. A turn restriction for the intersection is determined based on the comparison.
Abstract:
An apparatus, method and computer program product are provided for predicting tire temperature levels. In one example, the apparatus receives input data indicating attributes of the target vehicle and attributes of target routes for the target vehicle. The apparatus causes a machine learning model to generate output data as a function of the input data, where the output data indicate a subset of the target routes of which the target vehicle can successfully traverse while using the at least one spare tire. The machine learning model is trained to generate the output data as a function of the input data based on training data, where the training data indicate events in which vehicles used spare tires to traverse routes. The training data indicate attributes of the vehicles and attributes of the routes.