Method to control vehicle fleets to deliver on-demand transportation services
First Claim
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1. A method for automatically distributing vehicles capable of performing on-demand transportation (ODT) services, 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 is performed using at least two prediction models,wherein each of the at least two prediction models is generated based, at least in part, on historical ODT service data,wherein the at least two prediction models include one or more time-varying Poisson models and one or more time-series analysis models.
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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.
21 Citations
20 Claims
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1. A method for automatically distributing vehicles capable of performing on-demand transportation (ODT) services, the method comprising:
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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 is performed using at least two prediction models, wherein each of the at least two prediction models is generated based, at least in part, on historical ODT service data, wherein the at least two prediction models include one or more time-varying Poisson models and one or more time-series analysis models. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. A system for automatically distributing vehicles capable of performing on-demand transportation (ODT) services, the system comprising:
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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 is performed using at least two prediction models, wherein each of the at least two prediction models is generated based, at least in part, on historical ODT service data, wherein the at least two prediction models include one or more time-varying Poisson models and one or more time-series analysis models.
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20. A non-transitory computer readable medium having stored thereon a set of processor executable instructions for executing a method for automatically distributing vehicles capable of performing on-demand transportation (ODT) services, the processor executable instructions comprising instructions for:
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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 is performed using at least two prediction models, wherein each of the at least two prediction models is generated based, at least in part, on historical ODT service data, wherein the at least two prediction models include one or more time-varying Poisson models and one or more time-series analysis models.
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Specification