METHOD TO CONTROL VEHICLE FLEETS TO DELIVER ON-DEMAND TRANSPORTATION SERVICES

• US 20180096606A1
• Filed: 09/30/2016
• Published: 04/05/2018
• Est. Priority Date: 09/30/2016
• Status: Active Grant

• Current Assignee: NEC Corporation
• Original Assignee: NEC Europe Ltd (NEC Corporation)
• Inventors: Moreira-Matias, Luis, Saadallah, Amal, Khiari, Jihed
• Granted Patent: US 10,192,448 B2
• Time in Patent Office: Days
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G05D 1/0291 Fleet control monitoring fleets in traffic control systems for road vehicles G08G1/127, G08G1/127
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: G07B 15/00 Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points handling coins or valuable papers, e.g. banknotes, G07D; apparatus for vending or hiring articles or services activated by coins, credit cards, paper currency or the like G07F7/00, G07F17/00
• CPC Class Codes: G07C 5/08 Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
• CPC Class Codes: G08G 1/202 Dispatching vehicles on the basis of a location, e.g. taxi dispatching
• CPC Class Codes: G08G 1/205 Indicating the location of the monitored vehicles as destination, e.g. accidents, stolen, rental

Abstract

A method for providing dispatching services for an on-demand transportation (ODT) service includes determining that a predictive assignment message should be transmitted to a vehicle, generating, in response to the determining that a predictive assignment should be transmitted to a vehicle, the predictive assignment message, and transmitting, to the vehicle, the predictive assignment message. Generating the predictive assignment message uses one or more prediction models computed from historical and real-time ODT service data.

Claims

1. A method for providing dispatching services for an on-demand transportation (ODT) service, the method comprising:

determining that a predictive assignment message should be transmitted to a vehicle;

generating, in response to the determining that a predictive assignment should be transmitted to a vehicle, the predictive assignment message; and

transmitting, to the vehicle, the predictive assignment message,

wherein generating the predictive assignment message uses one or more prediction models computed from historical ODT service data and real-time ODT service data.

2. The method of claim 1, further comprising:

receiving, from the vehicle, a response to the predictive assignment message,

wherein the response to the predictive assignment messages includes one of an acceptance of the predictive assignment or a denial of the predictive assignment.

3. The method of claim 1, further comprising:

receiving, from a user, a request for an ODT service; and

assigning, based at least in part on a location of the user and a location included in the predictive assignment message, the requested ODT service to the vehicle.

4. The method of claim 1, further comprising:

receiving, from a plurality of users during a current time interval, a plurality of requests for ODT services; and

updating, according to the plurality of requests for ODT services, the real-time ODT service data.

5. The method of claim 4, wherein the plurality of requests for ODT services each includes a starting location for the requested ODT service.

6. The method of claim 1, wherein determining that a predictive assignment message should be transmitted to a vehicle comprises at least one of:

determining that a drop-off message has been received from the vehicle, or

determining that a predetermined duration of time has elapsed since the latter of a previous predictive assignment message has been transmitted to the vehicle or a pick-up message has been received from the vehicle.

7. The method of claim 6, wherein the drop-off message includes one or more of a timestamped GPS location, a vehicle fuel level, or a vehicle battery life.

8. The method of claim 1, wherein the one or more prediction models computed from historical ODT service data and real-time ODT service data include one or more time-varying Poisson models and one or more time-series analysis models.

9. The method of claim 8, wherein the one or more time-varying Poisson models include at least one of a Poisson model or a weighted Poisson model.

10. The method of claim 9, wherein the one or more time-series analysis models include at least one of an autoregressive integrated moving average (ARIMA) model or a vector autoregression (VAR) models.

11. The method of claim 8, wherein generating the predictive assignment message uses an ensemble of prediction models including a time-varying Poisson model selected from the one or more time-varying Poisson models and a time-series analysis model selected from the one or more time-series analysis models.

12. The method of claim 11, wherein the ensemble of prediction models provides a weighting of the selected time-varying Poisson model and a weighting of the selected time-series analysis model.

13. The method of claim 11, wherein the selected time-varying Poisson model has a least residuals from among the one or more time-varying Poisson models and wherein the selected time-series analysis model has a least residuals from among the one or more time-series analysis models.

14. The method of claim 1, wherein the vehicle is an autonomously driven vehicle.

15. A system for providing dispatching services for an on-demand transportation (ODT) service, the system comprising:

a central ODT dispatcher server operable to;

determine that a predictive assignment message should be transmitted to a vehicle;

generate, in response to the determining that a predictive assignment should be transmitted to a vehicle, the predictive assignment message; and

transmit, to the vehicle, the predictive assignment message,

wherein generating the predictive assignment message uses one or more prediction models computed from historical ODT service data and real-time ODT service data.

16. A computer readable medium having stored thereon a set of processor executable instructions for executing a method for providing dispatching services for an on-demand transportation (ODT) service, the processor executable instructions comprising instructions for:

determining that a predictive assignment message should be transmitted to a vehicle;

generating, in response to the determining that a predictive assignment should be transmitted to a vehicle, the predictive assignment message; and

transmitting, to the vehicle, the predictive assignment message,

wherein generating the predictive assignment message uses one or more prediction models computed from historical ODT service data and real-time ODT service data.