METHOD AND APPARATUS FOR AUTOMATED SERVICE SCHEDULE DERIVATION AND UPDATING

• US 20140244326A1
• Filed: 02/28/2013
• Published: 08/28/2014
• Est. Priority Date: 02/28/2013
• Status: Active Grant

• Current Assignee: HERE Global B.V. (Nokia Corporation)
• Original Assignee: Navteq B.V.
• Inventors: Modica, Leo, Stenneth, Leon
• Granted Patent: US 9,659,495 B2
• Time in Patent Office: Days
• US Class Current: 705/7.13
• CPC Class Codes: G01C 21/34 Route searching; Route guidance
• CPC Class Codes: G01C 21/3423 Multimodal routing, i.e. combining two or more modes of transportation, where the modes can be any of, e.g. driving, walking, cycling, public transport
• CPC Class Codes: G01C 21/3446 Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
• CPC Class Codes: G01S 19/42 Determining position
• CPC Class Codes: G06Q 10/06311 Scheduling, planning or task assignment for a person or group
• CPC Class Codes: G06Q 10/1097 Task assignment
• CPC Class Codes: G08G 1/012 from other sources than vehicle or roadside beacons, e.g. mobile networks
• CPC Class Codes: G08G 1/123 indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, tramstransmission of navigation instructions to vehicles G08G1/0968

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.

Claims

1. A method comprising:

causing reception of location data, the location 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.

2. The method of claim 1 further comprising determining a number of weekday trips;

and generating a weekday service schedule.

3. The method of claim 1 further comprising determining a number of weekend trips;

and generating a weekend service schedule.

4. The method of claim 1 further comprising determining a location of one or more bus stops as a function of the location data.

5. The method of claim 1 further comprising calculating the mean arrival time by factoring only a first location point received for each trip at the bus stop.

6. The method of claim 1 further comprising re-partitioning the temporal data associated with each of the location points according to the calculated mean arrival time.

7. The method of claim 6 further comprising re-calculating the mean arrival time in accordance with the re-partitioned clusters.

8. An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least:

receive location data, the location data comprised of a plurality of location points and associated temporal data;

aggregate the location data by route and direction to determine a trip count;

receive at least one bus stop location;

partition the associated temporal data into a number of clusters in accordance with the trip count;

calculate a mean arrival time at the at least one bust stop for each cluster; and

generate at least one service schedule for the at least one bus stop, wherein the mean arrival time of each cluster represents the service schedule.

9. An apparatus according to claim 8, wherein the at least one memory and the computer program code are further configured to, with the processor, cause the apparatus to determine a number of weekday trips;

and generate a weekday service schedule.

10. An apparatus according to claim 8, wherein the at least one memory and the computer program code are further configured to, with the processor, cause the apparatus to determine a number of weekend trips;

and generate a weekend service schedule.

11. An apparatus according to claim 8, wherein the at least one memory and the computer program code are further configured to, with the processor, cause the apparatus to:

determine a location of one or more bus stops as a function of the location data.

12. An apparatus according to claim 8, wherein the at least one memory and the computer program code are further configured to, with the processor, cause the apparatus to calculate the mean arrival time by factoring only a first location point received for each trip at the bus stop.

13. An apparatus according to claim 8, wherein the at least one memory and the computer program code are further configured to, with the processor, cause the apparatus to re-partition the temporal data associated with each of the location points according to the calculated mean arrival time.

14. An apparatus according to claim 13, wherein the at least one memory and the computer program code are further configured to, with the processor, cause the apparatus to re-calculate the mean arrival time in accordance with the re-partitioned clusters.

15. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code portions stored therein, the computer-executable program code portions comprising program code instructions for:

causing reception of location data, the location 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.

16. A computer program product according to claim 15, wherein the computer-executable program code portions further comprise program code instructions for determining a number of weekday trips;

and generating a weekday service schedule.

17. A computer program product according to claim 15, wherein the computer-executable program code portions further comprise program code instructions for determining a number of weekend trips;

and generating a weekend service schedule.

18. A computer program product according to claim 15, wherein the computer-executable program code portions further comprise program code instructions for determining a location of one or more bus stops as a function of the location data.

19. A computer program product according to claim 15, wherein the computer-executable program code portions further comprise program code instructions for calculating the mean arrival time by factoring only a first location point received for each trip at the bus stop.

20. A computer program product according to claim 15, wherein the computer-executable program code portions further comprise program code instructions for re-partitioning the temporal data associated with each of the location points according to the calculated mean arrival time.

21. A computer program product according to claim 20, wherein the computer-executable program code portions further comprise program code instructions for re-calculating the mean arrival time in accordance with the re-partitioned clusters.