Mining trajectory for spatial temporal analytics

1. A computer-implemented method, comprising:

generating, by a processing device, a trajectory database from time-stamped global positioning system (GPS) sample points;

computing transit points for each trajectory in the trajectory database, each transit point computed from a respective time-stamped GPS sample point, wherein computing the transit points includes computing a connectivity among all point transit clusters and clustering transit points located in similar network locations of the trajectory graph, whereby the centroids of transit point clusters form a node for the transit graph;

grouping the transit points into individual transit clusters, and constructing a temporal transit graph based on the transit clusters to define an aggregated trajectory of traffic patterns, the transit graph capturing the shortest paths among the transit points;

determining a common route of at least two vehicles whose GPS sampling intervals are different based on performing a trajectory alignment of the transit points with respect to a road network;

when two consecutive GPS points do not locate on the same or adjacent road segments, connecting the consecutive GPS points by the shortest path and performing a temporal interpolation to generate modified time stamps corresponding to the connected GPS points; and

indexing and storing the transit graph in a spatial-temporal database for online analytic processing, the online analytic processing comprising receiving spatial-temporal queries on the transit graph via a user interface,

wherein the GPS sample points that are collected from GPS logs of a plurality of vehicles in a street network table to define traffic patterns.

2. The computer-implemented method of claim 1 , wherein the transit points divide each trajectory into a number of sub-trajectories, each sub-trajectory being an exact shortest path between each transit point.

3. The computer-implemented method of claim 1 , wherein the generating of the trajectory database further comprises:

removing corrupted GPS sample points; and

aligning qualified GPS sample points to a road network.

4. The computer-implemented method of claim 1 , wherein the constructing of the temporal transit graph further comprises:

color coding the transit graph based on a number of routes passed on each transit edge of the transit graph.

5. The computer-implemented method of claim 1 , wherein the online analytic processing comprises receiving spatial-temporal queries on the transit graph via a user interface.

6. The computer-implemented method of claim 1 , wherein the temporal transit graph is constructed offline and the online analytics processing occurs online.

7. A computer program product, comprising:

a computer readable storage medium having program code embodied therewith, the program code executable by a processing device for:

generating, by the processing device, a trajectory database from time-stamped global positioning system (GPS) sample points;

computing transit points for each trajectory in the trajectory database, each transit point computed from a respective time-stamped GPS sample point, wherein computing the transit points includes computing a connectivity among all point transit clusters and clustering transit points located in similar network locations of the trajectory graph, whereby the centroids of transit point clusters form a node for the transit graph;

grouping the transit points into individual transit clusters, and constructing a temporal transit graph based on the transit clusters to define an aggregated trajectory of traffic patterns, the transit graph capturing the shortest paths among the transit points;

determining a common route of at least two vehicles whose GPS sampling intervals are different based on performing a trajectory alignment of the transit points with respect to a road network;

when two consecutive GPS points do not locate on the same or adjacent road segments, connecting the consecutive GPS points by the shortest path and performing a temporal interpolation to generate modified time stamps corresponding to the connected GPS points; and

indexing and storing the transit graph in a spatial-temporal database for online analytic processing, the online analytic processing comprising receiving spatial-temporal queries on the transit graph via a user interface,

wherein the GPS sample points that are collected from GPS logs of a plurality vehicles in a street network table define the traffic patterns.

8. The computer program product of claim 7 , wherein the transit points divide each trajectory into a number of sub-trajectories, each sub-trajectory being an exact shortest path between each transit point.

9. The computer program product of claim 7 , wherein the generating of the trajectory database further comprises:

removing corrupted GPS sample points; and

aligning qualified GPS sample points to a road network.

10. The computer program product of claim 7 , wherein the constructing of the temporal transit graph further comprises:

computing a connectivity among all point transit clusters; and

color coding the transit graph based on a number of routes passed on each transit edge of the transit graph.

11. The computer program product of claim 7 , wherein the online analytic processing comprises receiving spatial-temporal queries on the transit graph via a user interface.

12. The computer program product of claim 7 , wherein the temporal transit graph is constructed offline and the online analytics processing occurs online.