Method of operating a vehicle redistribution system based upon predicted ride demands

• US 6,453,298 B2
• Filed: 09/19/2001
• Issued: 09/17/2002
• Est. Priority Date: 07/10/1998
• Status: Expired due to Fees

• Current Assignee: Honda Giken Kogyo Kabushiki Kaisha (Honda Motor Company)
• Original Assignee: Honda Giken Kogyo Kabushiki Kaisha (Honda Motor Company)
• Inventors: Nakamura, Kazuhiro, Murakami, Hiroshi, Yano, Shunji, Uehara, Yuji
• Primary Examiner(s): Choi, Kyle J.
• Assistant Examiner(s): ROBERTSON, DAVID
• Application Number:
  US09/955,130
• Publication Number:
  US 20020019760A1
• Time in Patent Office: 363 Days
• Field of Search: 705/5, 705/6, 705/10, 705/7, 705/8, 705/13, 701/117, 701/22, 455/456, 340/988, 700/100-104
• US Class Current: 705/7.25
• CPC Class Codes: G06Q 10/047 Optimisation of routes or paths, e.g. travelling salesman problem
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G08G 1/20 Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles

Abstract

A vehicle allocation system oversees the operation of a plurality of auto-piloted vehicles, used to transport passengers between major ports such as airports, train stations, shopping malls, etc. The vehicle allocation system establishes a search time interval and predicts passenger demands and the status of the monitored vehicles within the search time interval. A predetermined number of vehicles are assigned to each of the ports in an area. Each port includes a parking lot or queue to accommodate waiting vehicles and a terminal which notifies a host computer of the number of currently available vehicles, passenger demands for vehicles, vehicle destination information, arrival information and so forth. The host computer has a memory storing predicted demand data based upon past demand history. The host computer calculates any excess or deficiency of vehicles in the ports on the basis of the predicted demand data and the information obtained from the terminals within the search time interval. On the basis of the result of such calculation, vehicles are reallocated from ports having an excess of vehicles to ports lacking sufficient vehicles.

Claims

1. A method of operating a vehicle redistribution system for predicting ride demands based on ride demands generated at a plurality of ports in an area, as well as, based upon statistical ride demand data at the plurality of ports, in order to redistribute vehicles from a port having surplus vehicles to a port lacking vehicles, said method comprising the steps of:

predicting total ride demand data on a daily basis from the statistical ride demand data;

selecting a number of total vehicles to be deployed within the area by computing the number of total vehicles using a formula;

total vehicles=number of all ports in the area times number of predicted ride demands per average travel time between ports, wherein the number of predicted ride demands per average travel time between ports is tabulated on a daily basis.

2. The method according to claim 1, wherein the average travel time between ports is an average of vehicle travel times between ports during redistribution of vehicles.

3. The method according to claim 2, wherein the average travel time between ports is acquired by computing a weighted average of vehicle travel times between ports, the weighted average computation being carried out in accordance with frequencies of port-to-port trips based on said statistical ride demand data.

4. The method according to claim 1, wherein the average travel time between ports is acquired by computing a weighted average of vehicle travel times between ports, the weighted average computation being carried out in accordance with frequencies of port-to-port trips based on said statistical ride demand data.