Real-time prediction and correction of scheduled service bunching

• US 9,858,542 B2
• Filed: 07/31/2013
• Issued: 01/02/2018
• Est. Priority Date: 07/31/2013
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Calabrese, Francesco, Nair, Rahul, Pinelli, Fabio
• Primary Examiner(s): Gart, Matthew
• Assistant Examiner(s): Swartz, Stephen S
• Application Number:
  US13/956,153
• Publication Number:
  US 20150039363A1
• Time in Patent Office: 1,616 Days
• CPC Class Codes: G06Q 10/06311 Scheduling, planning or task assignment for a person or group
• CPC Class Codes: G06Q 10/06312 Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083

Abstract

A method includes: a computer receiving historical data from at least one service vehicle; the computer receiving network definitions for the least one service vehicle; the computer receiving dynamic data from the at least one service vehicle; and the computer developing predictions and corrective actions to prevent service bunching, based upon the historical data, the network definitions, and the dynamic data.

Claims

1. A method comprising:

a service network controller receiving historical data from at least one service bus vehicle from a fleet of service bus vehicles;

the service network controller receiving network definitions of service routes for the least one service bus vehicle from the fleet of service bus vehicles;

the service network controller receiving dynamic data from the at least one service bus vehicle from the fleet of service bus vehicles;

the service network controller receiving passenger model data when the passenger uses a card upon boarding the least one service bus vehicle from the fleet of service bus vehicles; and

the service network controller developing route predictions and corrective actions to prevent service bunching for the fleet of service bus vehicles, based upon the historical data, the network route definitions, and the dynamic data, wherein the service bus vehicles operate on roads such that one of the corrective actions may include to skip a road bus stop.

2. The method according to claim 1, wherein the predictions are potential future bus service bunching events for the fleet of service bus vehicles along a network of scheduled route services with associated accuracy metrics.

3. The method according to claim 1, wherein another one of the corrective actions optimizing route plans to prevent predicted bus service bunching for the fleet of service bus vehicles along a network of scheduled services.

4. The method according to claim 1, wherein the historical data includes past performance of at least one service bus vehicle from the fleet of service bus vehicles.

5. The method according to claim 1, wherein the dynamic data is real time data from the at least one service bus vehicle from the fleet of service bus vehicles.

6. The method according to claim 3, further comprising the service network controller sending the optimized route plans to the at least one service bus vehicle from the fleet of service bus vehicles.

7. The method according to claim 6, wherein the optimized route plans is a bus vehicle control plan for the at least one service bus vehicle from the fleet of service bus vehicles.

8. The method according to the claim 3, further comprising to the service network controller sending the optimized route plans to a network infrastructure to prevent bunching for the fleet of service bus vehicles.