Data processing: financial – business practice – management – or co – Automated electrical financial or business practice or... – Health care management
Reexamination Certificate
2001-09-19
2002-09-17
Choi, Kyle J. (Department: 2163)
Data processing: financial, business practice, management, or co
Automated electrical financial or business practice or...
Health care management
C701S117000, C705S013000
Reexamination Certificate
active
06453298
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates generally to a vehicle distribution system and, more particularly, to a vehicle distribution system for providing a stable supply or distribution of vehicles to a plurality of ports within an area so as to keep up with ride demands at each of the ports.
2. Description of the Relevant Art
Where vehicles need to be distributed among a plurality of ports within an area in response to ride demands generated at each of the ports, some ports may lack vehicles to meet their ride demands while others may have excess vehicles. In such a case, a vehicle distribution system may be devised to reallocate or redistribute surplus vehicles between ports to replenish shortages of vehicles at other ports.
According to the background art, one vehicle distribution system is designed to deal with vehicle shortages on a posterior basis. In other words, vehicles are reallocated when a shortage occurs and not in anticipation of a predicted shortage. It takes time to move surplus vehicles from one port to another. Therefore, if a new ride demand occurs while vehicle redistribution is under way, or if some vehicles left ports on their way to other ports before a redistribution process is initiated, a surplus or shortage of vehicles may occur again at any port upon completion of the redistribution. Such occurrences can cause passengers to be left wait on vehicles for extended periods of time, such that a preferred minimum waiting time for passengers cannot be observed in the face of varying ride demands.
One solution to the above deficiency may be for vehicles to be redistributed on the basis of predicted ride demand data. Illustratively, a system may be devised to distribute vehicles according to predicted ride demand data based on the number of existing vehicles at each of the ports, on the ride demands currently generated at the port in question, and on past statistical ride demand data regarding the port.
One example of that system is a vehicle demand predicting system disclosed in Laid-Open Japanese Patent Application No. Hei 9-153098. This vehicle demand predicting system utilizes the statistical data as raw data. This means that if the raw data differ from actual ride demands, the system is significantly affected by such variances. The result can be a vehicle distribution system of poor accuracy, with a large number of vehicles redistributed unproductively (as will be discussed in detail with reference to FIGS.
14
and
15
). If the system redistributes vehicles while predicting ride demands using statistical data, the redistribution process should preferably be carried out with a minimum of wastefully redistributed vehicles, even if actual ride demands deviate from the statistical data.
SUMMARY OF THE INVENTION
It is therefore an object of the present invention to provide a vehicle distribution system capable of minimizing wastefully redistributed vehicles in the face of actual ride demand fluctuations.
These and other objects of the invention are fulfilled by providing a method of operating a vehicle allocation system for allocating a first number of vehicles amongst a second number of vehicle ports where passengers demand the services of one or more vehicles, said method comprising the steps of: acquiring past vehicle demand data based upon past passenger transportation activity; forming predictive vehicle demand data, based upon the past vehicle demand data; storing the predictive vehicle demand data; detecting a number of available vehicles at each of the ports; sensing current vehicle demand data representing passengers actually seeking transportation at each of the ports; reading vehicle destination and arrival data of vehicles starting or in transit to one of the ports; predicting the number of arriving vehicles at each of the ports based upon the vehicle destination and arrival data; determining whether a given port has a deficiency or an excess of vehicles by analyzing the current vehicle demand data, the predictive vehicle demand data, the number of available vehicles, and the number of arriving vehicles, for a predetermined period of time; and reallocating vehicles from a port determined to have an excess of vehicles to a port determined to have a deficiency of vehicles.
These and other objects of the invention are also fulfilled by providing 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 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 daily basis.
Furthermore, these and other objects of the invention are fulfilled by providing a vehicle distribution system for distributing vehicles among a plurality of ports within an area in response to ride demands generated at each of said ports, said vehicle distribution system comprising: predicted ride demand data storing means for storing predicted ride demand data established on the basis of statistical ride demand data regarding all ports; vehicle count detecting means for detecting an existing vehicle count at each of said ports; demand detecting means for detecting ride demand information including a current ride demand count and destination information regarding each of said ports; arriving vehicle predicting means for predicting arrivals of vehicles at each port from other ports as a predicted arriving vehicle count based on said destination information; surplus and shortage computing means for computing either a surplus or a shortage of vehicles at each of said ports by comparing, within a range of search represented by a predetermined period of time at each port, said current ride demand count and said predicted ride demand data, with said existing vehicle count and said predicted arriving vehicle count; and vehicle redistributing means for redistributing vehicles from a port having surplus vehicles to a port lacking vehicles on the basis of results of the computation indicating either said surplus or said shortage of vehicles.
Other objects and further scope of applicability of the present invention will become apparent from the detailed description given hereinafter. However, it should be understood that the detailed description and specific examples, while indicating preferred embodiments of the invention, are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art from this detailed description.
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Bernard, Martin J. Charging, Smart, and Queuing Infrasture Requirements for Station Cars. North American EV Infrastructure Conference and Exposition, Atlanta, GA, Nov. 17-19, 1999.*
Ridgeway, Mathew D. Projecting Bicyle Demand: An application of travel demand modeling techniques to bicyles. Fehr & Peers Associates: Lafayette, CA, Jun. 1995.*
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Barth et al. Si
Murakami Hiroshi
Nakamura Kazuhiro
Uehara Yuji
Yano Shunji
Birch & Stewart Kolasch & Birch, LLP
Choi Kyle J.
Honda Giken Kogyo Kabushiki Kaisha
Robertson D.
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