LARGE SCALE DEMAND RESPONSIVE TRANSIT FRAMEWORK

• US 20150100238A1
• Filed: 10/03/2013
• Published: 04/09/2015
• Est. Priority Date: 10/03/2013
• Status: Active Grant

• Current Assignee: SAP SE
• Original Assignee: Danqing Cai, Kar Leong Tew, Ziheng Lin
• Inventors: CAI, Danqing, LIN, Ziheng, TEW, Kar Leong, CHIAM, Elliot, LEE, Sak Onn
• Granted Patent: US 9,043,151 B2
• Time in Patent Office: Days
• US Class Current: 701/537
• CPC Class Codes: G01C 21/34 Route searching; Route guidance
• CPC Class Codes: G01C 21/3415 Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
• 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: G08G 1/127 to a central station ; Indicators in a central station
• CPC Class Codes: G08G 1/133 within the vehicle ; Indicators inside the vehicles or at stops

Abstract

Described herein is a descriptive framework to facilitate large scale demand responsive transit. In accordance with one aspect of the framework, one or more trip requests from one or more commuter devices are received. A trip request indicates at least one start location and at least one end location. In addition, vehicle information is received from one or more available vehicles. The vehicle information indicates at least one current location of a vehicle. An adaptive route for the vehicle may be planned based on the one or more trip requests and the vehicle information. Update information of the adaptive route may be communicated to the vehicle and the one or more commuter devices.

Claims

1. A computer-implemented method of facilitating large scale demand responsive transit, comprising:

receiving one or more trip requests from one or more commuter devices, wherein a trip request indicates at least one start location and at least one end location;

receiving vehicle information from one or more vehicles, wherein the vehicle information indicates at least one current location of a vehicle;

planning, by a processor, an adaptive route for the vehicle based on the one or more trip requests, the vehicle information and at least one dynamic constraint that includes road avoidance in response to detection of an event;

generating, by the processor, an evaluation score of the adaptive route, wherein the evaluation score is based on one or more score factors; and

if the one or more score factors meet pre-defined criteria, communicating update information of the adaptive route to the vehicle and the one or more commuter devices.

2. A computer-implemented method of facilitating large scale demand responsive transit, comprising:

receiving one or more trip requests from one or more commuter devices, wherein a trip request indicates at least one start location and at least one end location;

receiving vehicle information from one or more available vehicles, wherein the vehicle information indicates at least one current location of a vehicle;

planning, by a processor, an adaptive route for the vehicle based on the one or more trip requests and the vehicle information; and

communicating, by the processor, update information of the adaptive route to the vehicle and the one or more commuter devices, wherein the update information comprises an identifier of the vehicle, the adaptive route information, estimated arrival time of the vehicle, number of passengers on-board the vehicle, an interior image of the vehicle, an exterior image of the vehicle, or a combination thereof.

3. The method of claim 2 further comprising presenting, via a dashboard rendered at the one or more commuter devices, the update information.

5. The method of claim 2 wherein receiving the one or more trip requests comprises collecting the one or more trip requests from the one or more commuter devices at regular time intervals.

6. The method of claim 2 wherein receiving the vehicle information from the one or more vehicles comprises receiving, at regular time intervals, the vehicle information from one or more telematics devices installed in the one or more vehicles.

7. The method of claim 6 wherein the vehicle information further comprises number of passengers on-board the vehicle.

8. The method of claim 2 further comprising:

changing the adaptive route in response to receiving one or more additional trip requests; and

communicating update information of the changed route to the vehicle and the one or more commuter devices.

9. The method of claim 2 wherein planning the adaptive route for the vehicle further comprises planning the adaptive route based on one or more pre-defined constraints.

10. The method of claim 9 wherein the one or more pre-defined constraints comprise at least one static constraint.

11. The method of claim 9 wherein the one or more pre-defined constraints comprise at least one dynamic constraint.

12. The method of claim 2 further comprising aggregating the one or more trip requests into formatted request data and storing the formatted request data for future retrieval.

13. The method of claim 2 further comprising sorting available vehicles by travel distances in ascending order and planning the adaptive route of the vehicles based on the order.

14. The method of claim 2 wherein planning the adaptive route for the vehicle comprises performing a minimum accumulated travel distance technique.

15. The method of claim 2 further comprising generating an evaluation score of the adaptive route based on one or more score factors.

16. The method of claim 15 wherein the one or more score factors comprise accumulated travel distance, accumulated travel time, accumulated commuter waiting time, average commuter waiting time, or a combination thereof.

17. The method of claim 15 further comprising:

if at least one of the one or more score factors does not meet a pre-defined criterion, planning another adaptive route for a next available vehicle based on the one or more trip requests and vehicle information of the next available vehicle.

4. (canceled)

18. A non-transitory computer-readable medium having stored thereon program code, the program code executable by a computer to:

receive one or more trip requests from one or more commuter devices, wherein a trip request indicates at least one start location and at least one end location;

receive vehicle information from one or more available vehicles, wherein the vehicle information indicates at least one current location of a vehicle;

plan an adaptive route for the vehicle based on the one or more trip requests, the vehicle information and at least one dynamic constraint that includes road avoidance in response to detection of an event; and

communicate update information of the adaptive route to the vehicle and the one or more commuter devices.

19. A system for facilitating large scale demand responsive transit, comprising:

a non-transitory memory device for storing computer-readable program code; and

a processor in communication with the memory device, the processor being operative with the computer-readable program code to perform the steps of

receive one or more trip requests from one or more commuter devices, wherein a trip request indicates at least one start location and at least one end location;

receive vehicle information from one or more available vehicles, wherein the vehicle information indicates at least one current location of a vehicle;

plan an adaptive route for the vehicle based on the one or more trip requests and the vehicle information; and

communicate update information of the adaptive route to the vehicle and the one or more commuter devices, wherein the update information comprises an identifier of the vehicle, the adaptive route information, estimated arrival time of the vehicle, number of passengers on-board the vehicle, an interior image of the vehicle, an exterior image of the vehicle, or a combination thereof.

20. The system of claim 19 wherein the one or more commuter devices comprise at least one mobile device or bus-stop panel.