Abstract:
A method and system include identification of road segments with multi-modal traffic patterns. A server receives speed data for a link. The server calculates a quantity of speed clusters from the speed data. The server calculates speed profiles for the quantity of speed clusters. The server identifies one or more modes of transportation for the link based on the quantity of the speed clusters and the speed profiles for the quantity of speed clusters.
Abstract:
In an example embodiment, a plurality of sequences of instances of probe data are received. Each sequence of instances of probe data is captured and provided by a probe apparatus comprising a plurality of sensors and is onboard a vehicle. An instance of probe data comprises location information indicating a location of the corresponding probe apparatus and the instances are ordered by capture time to form the sequence of instances. A travel direction of each probe apparatus is determined based on the corresponding sequence. Each probe apparatus is matched to a lane of a road segment based on the determined travel direction and a predetermined vehicle lane pattern. The vehicle lane pattern comprises at least one reversible lane. Probe apparatuses matched to the at least one reversible lane are identified. An active direction is determined based on the number of identified probe apparatuses corresponding to each travel direction.
Abstract:
A plurality of instances of probe data are received. Each instance is received from a probe apparatus of a plurality of probe apparatuses each comprising a plurality of sensors and being onboard a vehicle. An instance comprises location information indicating a location of the corresponding probe apparatus. For each of one or more instances, a distance parameter is determined based on the location information and a road segment corresponding to the location. A set of distance parameters is defined based on the distance parameter determined for each of the one or more instances. The set of distance parameters is analyzed to identify clusters of probe data. The number of clusters identified is determined and compared to a historical number of clusters. If the number of clusters identified is less than the historical number of clusters, it is determined that there is a lane closure corresponding to the road segment.
Abstract:
Systems, methods, and apparatuses are described for estimating traffic conditions on road segments when no real time traffic data is available. A computing device may access a road topology comprising links from a geographic database. One of the links is selected from road topology. The computing device identifies a subset of the road topology having neighboring links that have an influential conditional probability on the selected link. In one example, the subset of the neighboring links includes parent links for the selected link, child links for the selected link, and parents of child links of the selected link. The computing device generates a traffic estimation model for the selected link using the subset of road topology and historical traffic data for the neighboring links.
Abstract:
An approach is provided for state classification for a travel segment with multi-modal speed profiles. A traffic processing platform processes and/or facilitates a processing of probe data associated with at least one travel segment to determine that probe data indicates a plurality of speed profiles. The plurality of speed profiles represent one or more observed clusters of speed states. The traffic processing platform also determine that the at least one travel segment exhibits a multi-modality with respect to travel speed based, at least in part, on the plurality of speed profiles. The traffic processing platform then determines at least one likely sequence of speed states for traversing the at least one travel segment based, at least in part, on the one or more observed clusters of speed states and state transition probability information, wherein the state transition probability information represents one or more probabilities for transitioning among the plurality of speed states and causes, at least in part, a classification of at least one hidden state of the at least one travel segment based, at least in part, on the at least one likely sequence of speed states.
Abstract:
A method, apparatus and computer program product are provided to identify a split lane traffic location. In a method, a distribution of speeds associated with a plurality of historical probe points representative of travel along a road segment upstream of diverging downstream road segments is determined for each of a plurality of epochs. For each epoch, the distribution is evaluated to cluster the speeds associated with the plurality of historical probe points during the respective epoch into higher and lower speed clusters. For each epoch, it is determined whether a bi-modality condition exists upstream of the diverging downstream road segments based upon a relationship between the higher speed and the lower speed during the respective epoch. A split lane traffic location is then identified based upon a bi-modality frequency with which a bi-modality condition is determined from the historical probe points associated with the plurality of epochs.
Abstract:
Systems, methods, and apparatuses are described for monitoring and visualizing traffic surprises. Traffic data is received for a region of interest comprising one or more routes. A surprise factor may be calculated for one or more routes in the region of interest based on a ratio of historical traffic data and real-time traffic data. A comparison may be performed of the surprise factor to at least one threshold. A surprise traffic message may be generated based on the comparison.
Abstract:
Systems and methods are described for referencing road strands. Speed data for a set of adjoining road segments is identified. Using at least one of the adjoining road segments, a strand database for is accessed to retrieve a predetermined strand of road segments. An aggregate speed value for the predetermined strand of road segments is calculated based on the speed data for the set of adjoining road segments represented by the predetermined strand of road segments. The aggregate speed value is provided as a representative of traffic on the set of adjoining road segments represented by the predetermined strand of road segments.
Abstract:
Systems, methods, and apparatuses are described for estimating traffic conditions on road segments when no real time traffic data is available. A computing device may access a road topology comprising links from a geographic database. One of the links is selected from road topology. The computing device identifies a subset of the road topology having neighboring links that have an influentual conditional probability on the selected link. In one example, the subset of the neighboring links includes parent links for the selected link, child links for the selected link, and parents of child links of the selected link. The computing device generates a traffic estimation model for the selected link using the subset of road topology and historical traffic data for the neighboring links.
Abstract:
An approach is provided for using pedestrian probe data for ridesharing. The approach involves, for example, receiving pedestrian probe data from a search zone associated with a designated location. The pedestrian probe data is collected, for instance, from one or more location sensors of at least one device associated with at least one pedestrian. The approach also involves processing the pedestrian probe data to determine one or more pedestrian paths terminating at the designated location. The approach further involves identifying at least one common origin, at least one common destination, or a combination thereof of the one or more pedestrian paths and providing the least one common origin, the at least one common destination, or a combination thereof as an output.