Abstract:
An apparatus is configured to perform a method for collaborative localization of multiple devices in a geographic area including receiving global localization data originating with one or more neighboring devices, receiving local localization data originating with a mobile device, determining a first confidence level from the local localization data, determining a second confidence level from the global localization data, and performing, by a processor, a collaborative localization calculation for the mobile device based on the first confidence level and the second confidence level.
Abstract:
A plurality of instances of pre-intersection and post-intersection probe data are received. Each instance of pre-intersection probe data corresponds to traveling along a pre-intersection road segment before traveling through an intersection. Each instance of post-intersection probe data corresponds to traveling along a post-intersection road segment following traveling through the intersection. Instances of pre-intersection probe data are clustered into pre-intersection clusters based on a post-intersection road segment identified by the corresponding instance of post-intersection probe data. Instances of post-intersection probe data are clustered into post-intersection clusters based on the post-intersection road segment identified thereby. A traffic level indicator is determined for each cluster. A traffic level indicator difference is determined for each pair of corresponding pre-intersection and post-intersection clusters. Responsive to determining that at least one traffic level indicator difference is greater than a threshold traffic level indicator difference, the intersection is identified as experiencing a traffic jam.
Abstract:
One or more potential drone and/or flying car (DFC) corridors are identified based on the topology of a road network. Trajectories traveled by vehicles are determined from a plurality of instances of probe data received from a plurality of vehicle apparatuses onboard the vehicles. A volume of traffic for a path through the road network and corresponding to a potential DFC corridor is determined based on the trajectories. A delay metric for the path through the road network and corresponding to the potential DFC corridor is determined based on the trajectories. A traffic metric is then determined for the path based on a combination of the volume of traffic, the delay metric and a measure of the topology of the road network. The one or more potential DFC corridors are ranked by their corresponding traffic metrics.
Abstract:
A method is provided to determine a number of vehicle travel lanes along a road segment. A method may include: receiving probe data from a plurality of probes, where the probe data includes probe data points having location and heading; matching the probe data to a road segment to generate map-matched probe data; analyzing the probe data relative to the road segment to establish a multi-modal distribution of probe data representing a distance of the probe data from a predefined reference position of the road segment; determining a number of vehicle travel lanes of the road segment based on peaks in the established multi-modal distribution being associated with individual lanes; and providing the determined number of vehicle travel lanes and the associated road segment to a map services database for lane-level route guidance.
Abstract:
An instance of probe data that was captured by sensors of a probe apparatus onboard a vehicle is received. Previous instances of probe data captured by the probe apparatus onboard the vehicle are accessed and the instance of probe is analyzed based on the previous instances of probe data. A current traffic state is determined for the vehicle based on the analysis. In an example embodiment, the analysis comprises generating a hidden Markov model based on speed data of the probe data. A Viterbi-path is obtained corresponding to the instance of probe data and the previous instances of probe data. The current traffic state is defined based on the Viterbi-path. The current traffic state may be used to determine traffic information/data for a road segment and/or predict a future traffic state for the vehicle. Traffic management decisions and/or routing decisions for the vehicle may be made based thereon.
Abstract:
A method, apparatus and computer program product are provided to analyze the vehicular speeds along a link that approaches a junction at the lane level. In the context of a method, a plurality of clusters of vehicular speeds are identified from probe data along a first multi-lane link that approaches a junction. For a respective lane of traffic of the first link, the method determines a value associated with the traffic having a respective state of traffic flow from among the different states of traffic flow associated with the clusters of vehicular speeds along the respective lane of traffic of the first link. The method further includes repeatedly determining the value associated with the traffic having a respective state of traffic flow from among the different states of traffic flow associated with the clusters of vehicular speeds for each different lane of traffic of the first link.
Abstract:
A method, apparatus and computer program product are provided in order to identify a bi-modality condition upstream of diverging downstream road segments. In the context of a method, a distribution of speeds associated with a plurality of probe points representative of travel along the road segment upstream of diverging downstream road segments is determined. The method also includes evaluating the distribution so as to cluster the speeds associated with the plurality of probe points into a higher speed cluster associated with a higher speed and a lower speed cluster associated with a lower speed. The method also includes identifying a bi-modality condition upstream of the diverging downstream road segments based upon a relationship between the higher speed and the lower speed. The method further includes determining an extent to the bi-modality condition upstream of the diverging downstream road segments.
Abstract:
In one embodiment, road segments are aggregated for DLR. A plurality of connected road segments and corresponding traffic information for each of the connected road segments are identified. A processor aggregates the connected road segments into a fewer number of dynamic location reference (DLR) segments than the plurality. By testing different possible combinations, road segments with similar congestion are grouped. The processor calculates a traffic value for each of the DLR segments. Each traffic value is a function of the traffic information for the connected road segments of the respective DLR segment. An indicator of the aggregated DLR segment and the traffic value for at least one of the DLR segments is output.