SYSTEMS AND METHODS OF PREDICTING ESTIMATED TIMES OF ARRIVAL BASED ON HISTORICAL INFORMATION

1 . A method comprising:

at a system hosting a first fleet dispatching service for one or more fleets of vehicles:

receiving historical information that includes information for a plurality of trips made by a fleet of vehicles, wherein the information includes an actual time of arrival for each of the plurality of trips;

for each trip of the plurality of trips:

predicting, using services provided by the first fleet dispatching service, an estimated time of arrival based on conditions at a time of the trip; and

computing a difference between the estimated time of arrival and the actual time of arrival for the trip;

generating a statistical model based on the computed differences;

receiving a first trip request for a first trip; and

dispatching a first vehicle for the first trip request, using the services provided by the first fleet dispatching service, based at least in part on the statistical model.

2 . The method of claim 1 , wherein:

dispatching the first vehicle for the first trip request based at least in part on the statistical model includes generating an estimated time of arrival for the first trip and updating the estimated time of arrival for the first trip using the statistical model; and

the method further comprises:

providing the updated estimated time of arrival for the first trip.

3 . The method of claim 2 , further comprising:

receiving a second trip request for a second trip; and

dispatching a second vehicle for the second trip request based at least in part on the statistical model, including generating an estimated time of arrival for the second trip and updating the estimated time of arrival for the second trip using the statistical model, wherein:

updating the estimated time of arrival for the first trip using the statistical model includes adjusting the estimated time of arrival for the first trip by a first amount of time; and

updating the estimated time of arrival for the second trip using the statistical model includes adjusting the estimated time of arrival for the second trip by a second amount of time that is different from the first amount of time.

4 . The method of claim 2 , wherein:

updating the estimated time of arrival for the first trip using the statistical model includes adjusting the estimated time of arrival for the first trip by a first amount of time; and

the first amount of time is determined based on one or more of: a driver of the first vehicle, a vehicle type of the first vehicle, and the fleet to which the first vehicle belongs.

5 . The method of claim 1 , wherein dispatching the first vehicle for the first trip request based at least in part on the statistical model includes:

modifying a dispatch model using the statistical model; and

dispatching the first vehicle for the first trip request using the modified dispatch model.

6 . The method of claim 1 , wherein:

the historical information is an event log; and

the event log includes, for each trip of the plurality of trips: a pick-up location, a drop-off location, and a time of trip.

7 . The method of claim 1 , wherein the conditions at the time of the trip include:

a state of the road network at the time of the trip;

traffic at the time of the trip; and

user-defined constraints for the fleet of vehicles at the time of the trip.

8 . The method of claim 1 , wherein the plurality of trips were dispatched by a second fleet dispatching service that is different from the first fleet dispatching service.

9 . The method of claim 1 , the method further comprising:

receiving new data that includes information for a second plurality of trips, the information including an actual time of arrival for each of the second plurality of trips;

for each trip of the second plurality of trips:

predicting an estimated time of arrival; and

computing a difference between the estimated time of arrival and the actual time of arrival for the trip;

updating the statistical model based on the computed differences;

receiving a third trip request; and

dispatching a third vehicle for the third trip request based at least in part on the updated statistical model.

10 . The method of claim 9 , wherein the second plurality of trips were dispatched by the first fleet dispatching service.

11 . The method of claim 1 , wherein the dispatched vehicle is a vehicle of the fleet of vehicles.

12 . The method of claim 1 , wherein the statistical model is a linear regression generated based on the computed differences.

13 - 14 . (canceled)

15 . A computer system, comprising:

one or more processors; and

memory storing instructions that, when executed by the one or more processors, cause the one or more processors to:

receive historical information that includes information for a plurality of trips made by a fleet of vehicles, wherein the information includes an actual time of arrival for each of the plurality of trips;

for each trip of the plurality of trips:

predict, using services provided by the first fleet dispatching service, an estimated time of arrival based on conditions at a time of the trip; and

compute a difference between the estimated time of arrival and the actual time of arrival for the trip;

generate a statistical model based on the computed differences;

receive a first trip request for a first trip; and

dispatch a first vehicle for the first trip request, using the services provided by the first fleet dispatching service, based at least in part on the statistical model.

16 . The computer system of claim 1 , wherein:

dispatching the first vehicle for the first trip request based at least in part on the statistical model includes generating an estimated time of arrival for the first trip and updating the estimated time of arrival for the first trip using the statistical model; and

wherein the instructions further cause the one or more processors to provide the updated estimated time of arrival for the first trip.

17 . The computer system of claim 16 , wherein the instructions further cause the one or more processors to:

receive a second trip request for a second trip; and

dispatch a second vehicle for the second trip request based at least in part on the statistical model, including generating an estimated time of arrival for the second trip and updating the estimated time of arrival for the second trip using the statistical model, wherein:

updating the estimated time of arrival for the first trip using the statistical model includes adjusting the estimated time of arrival for the first trip by a first amount of time; and

updating the estimated time of arrival for the second trip using the statistical model includes adjusting the estimated time of arrival for the second trip by a second amount of time that is different from the first amount of time.

18 . The computer system of claim 16 , wherein:

updating the estimated time of arrival for the first trip using the statistical model includes adjusting the estimated time of arrival for the first trip by a first amount of time; and

the first amount of time is determined based on one or more of: a driver of the first vehicle, a vehicle type of the first vehicle, and the fleet to which the first vehicle belongs.

19 . The computer system of claim 15 , wherein dispatching the first vehicle for the first trip request based at least in part on the statistical model includes:

modifying a dispatch model using the statistical model; and

dispatching the first vehicle for the first trip request using the modified dispatch model.

20 . The computer system of claim 15 , wherein the instructions further cause the one or more processors to:

receive new data that includes information for a second plurality of trips, the information including an actual time of arrival for each of the second plurality of trips;

for each trip of the second plurality of trips:

predict an estimated time of arrival; and

compute a difference between the estimated time of arrival and the actual time of arrival for the trip;

update the statistical model based on the computed differences;

receive a third trip request; and

dispatch a third vehicle for the third trip request based at least in part on the updated statistical model.

21 . A non-transitory computer readable storage medium storing instructions that, when executed by a computer system having one or more processors, cause the one or more processors to:

receive historical information that includes information for a plurality of trips made by a fleet of vehicles, wherein the information includes an actual time of arrival for each of the plurality of trips;

for each trip of the plurality of trips:

predict, using services provided by the first fleet dispatching service, an estimated time of arrival based on conditions at a time of the trip; and

compute a difference between the estimated time of arrival and the actual time of arrival for the trip;

generate a statistical model based on the computed differences;

receive a first trip request for a first trip; and

dispatch a first vehicle for the first trip request, using the services provided by the first fleet dispatching service, based at least in part on the statistical model.

22 . The non-transitory computer readable storage medium of claim 21 , wherein the instructions cause the one or more processors to:

receive new data that includes information for a second plurality of trips, the information including an actual time of arrival for each of the second plurality of trips;

for each trip of the second plurality of trips:

predict an estimated time of arrival; and

compute a difference between the estimated time of arrival and the actual time of arrival for the trip;

update the statistical model based on the computed differences;

receive a third trip request; and

dispatch a third vehicle for the third trip request based at least in part on the updated statistical model.