Trip anomaly detection system

Patent metadata

Field	Value
Publication number	US-2016373473-A1
Application number	US-201514742273-A
Country	US
Kind code	A1
Filing date	Jun 17, 2015
Priority date	Jun 17, 2015
Publication date	Dec 22, 2016
Grant date	—

Abstract

An anomaly detection system is provided in connection with a transport service. The anomaly detection system can construct routine route profiles for individual users of the transport service using historical route data. The anomaly detection system can monitor a current route traveled by a user. The anomaly detection system can further identify a matching routine route profile of the respective user. The anomaly detection system can utilize the matching routine route profile to identify a probable anomaly in the current route. In response to detecting the probable anomaly, the anomaly detection system can enable a safety protocol to perform a number of actions.

First claim

What is claimed is:

1 . An anomaly detection system for a transport service comprising:
one or more processors; and one or more memory resources storing instructions that, when executed by the one or more processors, cause the anomaly detection system to:
using historical route data, construct routine route profiles for users of the transport service;
monitor a current route traveled by a respective one of the users;
identify a matching routine route profile of the respective user;
determine a probable anomaly in the current route based on the matching routine route profile; and
in response to determining the probable anomaly, perform one more actions in accordance with a safety protocol.

2 . The anomaly detection system of claim 1 , wherein the executed instructions further cause the anomaly detection system to, prior to monitoring the current route:
receive a pick-up request from the respective user; and select a driver to service the pick-up request.

3 . The anomaly detection system of claim 2 , wherein the pick-up request includes a destination, and wherein the executed instructions cause the anomaly detection system to identify the matching routine route profile prior to monitoring the current route, and based on an initial location of the respective user and the destination.

4 . The anomaly detection system of claim 1 , wherein the executed instructions cause the anomaly detection system to identify the matching routine route profile during the current route traveled by the user.

5 . The anomaly detection system of claim 1 , wherein the executed instructions cause the anomaly detection system to determine the probable anomaly by performing a real-time probabilistic calculation comprising a number of probability factors collectively exceeding an anomaly threshold.

6 . The anomaly detection system of claim 5 , wherein the probability factors comprise the current route entering a flagged region.

7 . The anomaly detection system of claim 6 , wherein the executed instructions cause the anomaly detection system to determine the flagged region based on one or more of third-party crime data, or the flagged region being identified in a user profile of the respective user.

8 . The anomaly detection system of claim 5 , wherein the probability factors comprise (i) a divergence factor between the matching routine route profile and the current route, and (ii) a reputation factor of the selected driver.

9 . The anomaly detection system of claim 8 , wherein the reputation factor of the selected driver comprises (i) a complaint history of the selected driver, and (ii) reputation indicators of the selected driver pulled from third-party resources.

10 . The anomaly detection system of claim 2 , wherein the executed instructions cause the anomaly detection system to select the driver based on (i) a proximity between the respective user and the selected driver, and (ii) a comparison between a user profile of the respective user and a driver profile of the selected driver, the driver profile comprising reputation data.

11 . The anomaly detection system of claim 10 , wherein the executed instructions cause the anomaly detection system of perform the comparison by (i) identifying one or more factors for the respective user comprising one or more of an age, a gender, or user preferences in the user profile, and (ii) determining a reputation score for the selected driver based on the reputation data in the driver profile of the selected driver.

12 . The anomaly detection system of claim 1 , wherein the executed instructions cause the anomaly detection system to construct the routine route profiles by, for each of the users, (i) collecting the historical route data, and (ii) identifying common route shapes in the historical route data.

13 . The anomaly detection system of claim 12 , wherein each of the routine route profiles include a common start point and a common end point, and wherein each of the routine route profiles comprises a plurality of distinct routes, comprising the common route shapes, between the common start point and the common end point.

14 . The anomaly detection system of claim 1 , wherein an initial action of the safety protocol comprises transmitting a status query to a mobile device of the respective user, and wherein a subsequent action in the safety protocol comprises contacting an emergency authority to report the probable anomaly.

15 . The anomaly detecting system of claim 14 , wherein the executed instructions further cause the anomaly detection system to:
in response to the status query, receiving an indication of a negative condition from the mobile device of the respective user; and in response to receiving the indication, transmit a driver directive to a mobile device of the selected driver indicating an emergency condition.

16 . The anomaly detection system of claim 14 , wherein the executed instructions cause the anomaly detection system to monitor the current route traveled by the respective user by receiving location data from global positioning system (GPS) resources of the mobile device of the respective user.

17 . The anomaly detection system of claim 1 , wherein the executed instructions further cause the anomaly detection system to:
compare the current route traveled by the respective user to a route inputted by the selected driver into a mapping resource of a mobile device of the selected driver.

18 . The anomaly detection system of claim 1 , wherein the executed instructions further cause the anomaly detection system to:
provide a selectable emergency feature on a graphical user interface for the respective user during the current route; wherein a user selection of the selectable emergency feature triggers the probable anomaly.

19 . A non-transitory computer readable medium storing instructions that, when executed by one or more processors of an anomaly detection system, cause the anomaly detection system to:
using historical route data, construct routine route profiles for users of the transport service; monitor a current route traveled by a respective one of the users; identify a matching routine route profile of the respective user; determine a probable anomaly in the current route based on the matching routine route profile; and in response to determining the probable anomaly, perform one more actions in accordance with a safety protocol.

20 . A computer-implemented method for detecting route anomalies, the method performed by one or more processors of an anomaly detection system and comprising:
using historical route data, constructing routine route profiles for users of the transport service; monitoring a current route traveled by a respective one of the users; identifying a matching routine route profile of the respective user; determining a probable anomaly in the current route based on the matching routine route profile; and in response to determining the probable anomaly, performing one more actions in accordance with a safety protocol.

Assignees

• Uber Technologies Inc

Inventors

• Truong Michael
• Purdy David
• Mawas Rami

Classifications

• E05Y2900/548

  Trunk lids · CPC title

• H04L67/306

  User profiles · CPC title

• G08G1/0104

  Measuring and analyzing of parameters relative to traffic conditions · CPC title

• G06Q10/083

  Shipping · CPC title

• H04W4/023

  using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds · CPC title