Trip anomaly detection system

• US 10,301,867 B2
• Filed: 10/03/2018
• Issued: 05/28/2019
• Est. Priority Date: 06/17/2015
• Status: Active Grant

• Current Assignee: Uber Technologies, Inc.
• Original Assignee: Uber Technologies, Inc.
• Inventors: Truong, Michael, Purdy, David, Mawas, Rami
• Primary Examiner(s): Shayanfar, Ali
• Application Number:
  US16/150,656
• Publication Number:
  US 20190048642A1
• Time in Patent Office: 237 Days
• CPC Class Codes: B60N 2/002 Seats provided with an occupancy detection means mounted therein or thereon detection means responsive to presence or absence of children B60N2/266
• CPC Class Codes: B60R 11/04 Mounting of cameras operative during drive; Arrangement of controls thereof relative to the vehicle
• CPC Class Codes: E05F 15/70 with automatic actuation
• CPC Class Codes: E05Y 2400/44 Sensors therefore E05Y2400/322, E05Y2400/33, E05Y2400/55, E05Y2400/56, E05Y2400/852 take precedence
• CPC Class Codes: E05Y 2400/45 Control modes
• CPC Class Codes: E05Y 2900/548 Trunk lids
• CPC Class Codes: G01C 21/005 with correlation of navigation data from several sources, e.g. map or contour matching G01C21/30 takes precedence
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments
• 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 1/0212 with means for defining a desired trajectory involving a plurality of land vehicles G05D1/0287
• CPC Class Codes: G05D 1/0276 using signals provided by a source external to the vehicle involving a plurality of vehicles G05D1/0287; automatically controlling vehicle speed responsive to externally generated signals B60K31/0058
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 10/083 Shipping
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: G08G 1/0104 Measuring and analyzing of parameters relative to traffic conditions
• CPC Class Codes: H04L 63/1425 Traffic logging, e.g. anomaly detection
• CPC Class Codes: H04L 67/30 Profiles
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/023 using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• CPC Class Codes: H04W 4/029 : Location-based management or tracking services
• CPC Class Codes: H04W 4/40 : for vehicles, e.g. vehicle-to-pedestrians [V2P]
• CPC Class Codes: H04W 4/90 : Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS]
• CPC Class Codes: H04W 76/50 : for emergency connections

Abstract

An anomaly detection system is provided in connection with a transport service. The anomaly detection system can monitor progress of the transport service using received location data from driver and/or user mobile devices. During the progress of the transport service, the anomaly detection system can determine a probable anomaly by determining that a geographic position of the driver'"'"'s vehicle has remained static for a period of time exceeding a threshold period of time, and in response to determining the probable anomaly, transmit a notification message to at least one of the driver and user mobile devices.

Claims

1. A computing system comprising:

one or more processors; and

one or more memory resources storing instructions that, when executed by the one or more processors, cause the computing system to;

assign a driver of a vehicle to provide a transport service for a user, wherein the driver operates a driver mobile device and the user operates a user mobile device;

receive, over one or more networks, location data from a location-aware resource of the driver mobile device or a location-aware resource of the user mobile device;

monitor progress of the transport service using the received location data;

during the progress of the transport service, determine a probable anomaly by determining, using the location-aware resource of the driver mobile device or the location-aware resource of the user mobile device, that a geographic position of the vehicle has remained static for a period of time exceeding a threshold period of time; and

in response to determining the probable anomaly, transmit, over the one or more networks, a notification message to at least one of the driver mobile device or the user mobile device, wherein the notification message includes a warning message or a status query.

2. The computing system of claim 1, wherein the executed instructions further cause the computing system to:

raise or lower the threshold period of time based on a reputation factor of the driver, wherein the reputation factor includes (i) a complaint history of the driver, and (ii) reputation indicators of the driver received or retrieved from third-party resources.

3. The computing system of claim 1, wherein the executed instructions further cause the computing system to:

raise or lower the threshold period of time based on a comparison between a user profile of the user and a driver profile of the driver, the user profile comprising one or more user preferences, and the driver profile comprising reputation data for the driver.

4. The computing system of claim 1, wherein the executed instructions further cause the computing system to:

utilize environmental data for a region including the geographic position of the vehicle to raise or lower the threshold period of time.

5. The computing system of claim 4, wherein the environmental data includes traffic data, police report data, local news, and crime data.

6. The computing system of claim 1, wherein the notification message transmitted to the user mobile device includes the status query.

7. The computing system of claim 6, wherein the executed instructions further cause the computing system to:

in response to the status query, receive an indication of a negative condition from the user mobile device; and

in response to receiving the indication, transmit a driver directive to the driver mobile device indicating the negative condition.

8. The computing system of claim 1, wherein the executed instructions further cause the computing system to:

provide a selectable emergency feature on a graphical user interface of the user mobile device; and

receive a user selection of the selectable emergency feature.

9. The computing system of claim 1, wherein the location-aware resource of the driver mobile device and the location-aware resource of the user mobile device are global positioning system receivers.

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

assign a driver of a vehicle to provide a transport service for a user, wherein the driver operates a driver mobile device and the user operates a user mobile device;

receive, over one or more networks, location data from a location-aware resource of the driver mobile device or a location-aware resource of the user mobile device;

monitor progress of the transport service using the received location data;

during the progress of the transport service, determine a probable anomaly by determining, using the location-aware resource of the driver mobile device or the location-aware resource of the user mobile device, that a geographic position of the vehicle has remained static for a period of time exceeding a threshold period of time; and

in response to determining the probable anomaly, transmit, over the one or more networks, a notification message to at least one of the driver mobile device or the user mobile device, wherein the notification message includes a warning message or a status query.

11. The non-transitory computer-readable medium of claim 10, wherein the executed instructions further cause the computing system to:

raise or lower the threshold period of time based on a reputation factor of the driver, wherein the reputation factor includes (i) a complaint history of the driver, and (ii) reputation indicators of the driver received or retrieved from third-party resources.

12. The non-transitory computer-readable medium of claim 10, wherein the executed instructions further cause the computing system to:

raise or lower the threshold period of time based on a comparison between a user profile of the user and a driver profile of the driver, the user profile comprising one or more user preferences, and the driver profile comprising reputation data for the driver.

13. The non-transitory computer-readable medium of claim 10, wherein the executed instructions further cause the computing system to:

utilize environmental data for a region including the geographic position of the vehicle to raise or lower the threshold period of time.

14. The non-transitory computer-readable medium of claim 13, wherein the environmental data includes traffic data, police report data, local news, and crime data.

15. The non-transitory computer-readable medium of claim 10, wherein the notification message transmitted to the user mobile device includes the status query.

16. The non-transitory computer-readable medium of claim 15, wherein the executed instructions further cause the computing system to:

in response to the status query, receive an indication of a negative condition from the user mobile device; and

in response to receiving the indication, transmit a driver directive to the driver mobile device indicating the negative condition.

17. The non-transitory computer-readable medium of claim 10, wherein the executed instructions further cause the computing system to:

provide a selectable emergency feature on a graphical user interface of the user mobile device; and

receive a user selection of the selectable emergency feature.

18. The non-transitory computer-readable medium of claim 10, wherein the location-aware resource of the driver mobile device and the location-aware resource of the user mobile device are global positioning system receivers.

19. A computer-implemented method for detecting transport service anomalies, the method performed by one or more processors of a computing system and comprising:

assigning a driver of a vehicle to provide a transport service for a user, wherein the driver operates a driver mobile device and the user operates a user mobile device;

receiving, over one or more networks, location data from a location-aware resource of the driver mobile device or a location-aware resource of the user mobile device;

monitoring progress of the transport service using the received location data;

during the progress of the transport service, determining a probable anomaly by determining, using the location-aware resource of the driver mobile device or the location-aware resource of the user mobile device, that a geographic position of the vehicle has remained static for a period of time exceeding a threshold period of time; and

in response to determining the probable anomaly, transmitting, over the one or more networks, a notification message to at least one of the driver mobile device or the user mobile device, wherein the notification message includes a warning message or a status query.

20. The computer-implemented method of claim 19, wherein the location-aware resource of the driver mobile device and the location-aware resource of the user mobile device are global positioning system receivers.