Dynamically generating and updating multipliers for a transportation matching system using machine learning
This disclosure covers machine-learning methods, non-transitory computer readable media, and systems that generate a multiplier that efficiently and effectively provides on-demand transportation services for a geographic area. The methods, non-transitory computer readable media, and systems dynamically adjust the multiplier with machine learners to maintain a target estimated time of arrival for a provider device to fulfill a request received from a requestor device. In some embodiments, the methods, non-transitory computer readable media, and systems generate a multiplier report comprising a representation of a geographic area and an indication of the multiplier to facilitate inflow and outflow of provider devices within and without the geographic area.
1. A method comprising:
receiving, from a requestor client device, a first query for transportation corresponding to a geographic area during a first time period;
generating, utilizing one or more machine learners, a first set of parameters defining a first number of transportation requests that can be processed for the geographic area at the first time period;
determining, for display on the requestor client device and based on the first set of parameters, a first price estimate for transportation accounting for a first multiplier for the geographic area;
receiving, from one or more requestor client devices, one or more second queries for transportation corresponding to the geographic area during a second time period;
generating, utilizing the one or more machine learners, a second set of parameters defining a second number of transportation requests that can be processed for the geographic area at the second time period; and
determining, for display on the one or more requestor client devices and based on the second set of parameters, a second price estimate for transportation accounting for a second multiplier for the geographic area.
2. The method of claim 1 , wherein:
receiving the first query for transportation corresponding to the geographic area comprises receiving a first transportation request for transportation from a pickup location; and
receiving a second query for transportation of the one or more second queries corresponding to the geographic area comprises receiving a second transportation request for transportation from the pickup location.
3. The method of claim 1 , wherein:
receiving the first query for transportation corresponding to the geographic area comprises receiving a first transportation request for transportation to a destination; and
receiving a second query for transportation of the one or more second queries corresponding to the geographic area comprises receiving a second transportation request for transportation to the destination.
4. The method of claim 1 , wherein the first time period and the second time period are separated by a one-minute to a five-minute interval.
5. The method of claim 1 , further comprising:
applying a smoothing parameter to the first multiplier; and
determining a price change from the first price estimate to the second price estimate based on the smoothing parameter applied to the first multiplier.
6. The method of claim 1 , wherein receiving, from the one or more requestor client devices, the one or more second queries for transportation comprises receiving, from the requestor client device, a second query for transportation corresponding to the geographic area during the second time period.
7. The method of claim 1 , further comprising:
determining a number of previous transportation requests and a number of previously available transportation vehicles for a geographic region comprising the geographic area during prior time periods; and
generating, utilizing the one or more machine learners, the first set of parameters defining the first number of transportation requests based on the number of previous transportation requests and the number of previously available transportation vehicles.
8. A system comprising:
at least one processor; and
at least one non-transitory computer readable storage medium storing instructions that, when executed by the at least one processor, cause the system to:
receive, from a requestor client device, a first query for transportation corresponding to a geographic area during a first time period;
generate, utilizing one or more machine learners, a first set of parameters defining a first number of transportation requests that can be processed for the geographic area at the first time period;
determine, for display on the requestor client device and based on the first set of parameters, a first price estimate for transportation accounting for a first multiplier for the geographic area;
receive, from one or more requestor client devices, one or more second queries for transportation corresponding to the geographic area during a second time period;
generate, utilizing the one or more machine learners, a second set of parameters defining a second number of transportation requests that can be processed for the geographic area at the second time period; and
determine, for display on the one or more requestor client devices and based on the second set of parameters, a second price estimate for transportation accounting for a second multiplier for the geographic area.
9. The system of claim 8 , further comprising instructions that, when executed by the at least one processor, cause the system to:
receive the first query for transportation corresponding to the geographic area by receiving a first transportation request for transportation from a pickup location; and
receive a second query for transportation of the one or more second queries corresponding to the geographic area by receiving a second transportation request for transportation from the pickup location.
10. The system of claim 8 , further comprising instructions that, when executed by the at least one processor, cause the system to:
receive the first query for transportation corresponding to the geographic area by receiving a first transportation request for transportation to a destination; and
receive a second query for transportation of the one or more second queries corresponding to the geographic area by receiving a second transportation request for transportation to the destination.
11. The system of claim 8 , wherein the first time period and the second time period are separated by a one-minute to a five-minute interval.
12. The system of claim 8 , further comprising instructions that, when executed by the at least one processor, cause the system to:
apply a smoothing parameter to the first multiplier; and
determine a price change from the first price estimate to the second price estimate based on the smoothing parameter applied to the first multiplier.
13. The system of claim 8 , further comprising instructions that, when executed by the at least one processor, cause the system to receive, from the one or more requestor client devices, the one or more second queries for transportation by receiving, from the requestor client device, a second query for transportation corresponding to the geographic area during the second time period.
14. The system of claim 8 , further comprising the instructions that, when executed by the at least one processor, cause the system to:
determine a number of previous transportation requests and a number of previously available transportation vehicles for a geographic region comprising the geographic area during prior time periods; and
generating, utilizing the one or more machine learners, the second set of parameters defining the second number of transportation requests based on the number of previous transportation requests and the number of previously available transportation vehicles.
15. A non-transitory computer readable medium storing instructions thereon that, when executed by at least one processor, cause a system to:
receive, from a requestor client device, a first query for transportation corresponding to a geographic area during a first time period;
generate, utilizing one or more machine learners, a first set of parameters defining a first number of transportation requests that can be processed for the geographic area at the first time period;
determine, for display on the requestor client device and based on the first set of parameters, a first price estimate for transportation accounting for a first multiplier for the geographic area;
receive, from one or more requestor client devices, one or more second queries for transportation corresponding to the geographic area during a second time period;
generate, utilizing the one or more machine learners, a second set of parameters defining a second number of transportation requests that can be processed for the geographic area at the second time period; and
determine, for display on the one or more requestor client devices and based on the second set of parameters, a second price estimate for transportation accounting for a second multiplier for the geographic area.
16. The non-transitory computer readable medium of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the system to:
receive the first query for transportation corresponding to the geographic area by receiving a first transportation request for transportation from a pickup location; and
receive a second query for transportation of the one or more second queries corresponding to the geographic area by receiving a second transportation request for transportation from the pickup location.
17. The non-transitory computer readable medium of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the system to:
receive the first query for transportation corresponding to the geographic area by receiving a first transportation request for transportation to a destination; and
receive a second query for transportation of the one or more second queries corresponding to the geographic area by receiving a second transportation request for transportation to the destination.
18. The non-transitory computer readable medium of claim 15 , wherein the first time period and the second time period are separated by a one-minute to a five-minute interval.
19. The non-transitory computer readable medium of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the system to:
apply a smoothing parameter to the first multiplier; and
determine a price change from the first price estimate to the second price estimate based on the smoothing parameter applied to the first multiplier.
20. The non-transitory computer readable medium of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the system to receive, from the one or more requestor client devices, the one or more second queries for transportation by receiving, from the requestor client device, a second query for transportation corresponding to the geographic area during the second time period.