System and methods for assessment of rideshare trip

• US 10,697,784 B1
• Filed: 07/19/2017
• Issued: 06/30/2020
• Est. Priority Date: 07/19/2017
• Status: Active Grant

• Current Assignee: BlueOwl, LLC (State Farm)
• Original Assignee: BlueOwl, LLC (State Farm)
• Inventors: Li, Kaming
• Primary Examiner(s): Higa, Brendan Y
• Application Number:
  US15/653,884
• Time in Patent Office: 1,077 Days
• CPC Class Codes: G01C 21/3438 Rendez-vous, i.e. searching a destination where several users can meet, and the routes to this destination for these users; Ride sharing, i.e. searching a route such that at least two users can share a vehicle for at least part of the route
• CPC Class Codes: G01C 21/3484 Personalized, e.g. from learned user behaviour or user-defined profiles
• CPC Class Codes: G01C 21/3492 employing speed data or traffic data, e.g. real-time or historical traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968
• CPC Class Codes: G06Q 10/025 Coordination of plural reservations, e.g. plural trip segments, transportation combined with accommodation
• CPC Class Codes: G06Q 10/047 Optimisation of routes or paths, e.g. travelling salesman problem
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/063112 Skill-based matching of a person or a group to a task
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: G06Q 50/47 Passenger ride requests, e.g. ride-hailing
• CPC Class Codes: G08G 1/202 Dispatching vehicles on the basis of a location, e.g. taxi dispatching
• CPC Class Codes: H04L 67/00 Network arrangements or protocols for supporting network services or applications user-to-user messaging H04L51/00; network arrangements, protocols or services for supporting real-time applications in data packet communications networks H04L65/00
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04W 4/027 using movement velocity, acceleration information
• CPC Class Codes: H04W 4/40 for vehicles, e.g. vehicle-to-pedestrians [V2P]

Abstract

Techniques are disclosed for objectively assessing the driving performance of rideshare drivers and/or vehicles. The techniques include collecting data from various sources to aggregate trip data for several drivers and passengers over several ridesharing trips. This data may include telematics data collected from several passengers and/or drivers during each of their respective ridesharing trips, which indicates various aspects associated with operation of the vehicle. Each driver may then be correlated to his own set of trip data, such that a driving assessment may be made for each individual driver. When a new user subsequently requests a ride via a ridesharing provider, this driver assessment may be made available to the user, thereby providing the user with an objective assessment of the driver prior to the start of the scheduled ride.

Claims

1. A rideshare assessment server, comprising:

a communication unit configured to receive, via a computer network,

(i) information indicative of a plurality of historic ridesharing trips associated with a driver of a vehicle, and (ii) sensor data indicating one or more aspects associated with operation of the vehicle during each of the plurality of historic ridesharing trips when rideshare passengers were being driven by the driver, the sensor data collected via a plurality of mobile computing devices, each of the plurality of mobile computing devices being associated with a respective one of the rideshare passengers; and

a processor configured to correlate the sensor data that is collected via the plurality of mobile computing devices, over each of the plurality of historic ridesharing trips, to the driver and to determine an objective driver assessment for the driver based on the correlated sensor data indicating the one or more aspects associated with operation of the vehicle during each of the plurality of historic ridesharing trips,

wherein the processor is configured to determine the objective driver assessment by at least determining (i) a day driver assessment, and (ii) a night driver assessment based on time periods associated with the plurality of historic ridesharing trips,

wherein the communication unit is further configured to receive, via the computer network, information indicative of a scheduled ride with the driver and, in response to receipt of the scheduled ride, to transmit, via the computer network, one of the day driver assessment or the night driver assessment, based upon a time when the information indicative of the requested scheduled ride was received.

2. The rideshare assessment server of claim 1, wherein each of the plurality of historic ridesharing trips corresponds to a ridesharing trip requested by the respective one of the rideshare passengers, the request transmitted the mobile computing device associated with the respective one of the rideshare passengers to an external computing device associated with a ridesharing provider.

3. The rideshare assessment server of claim 1, wherein each of the rideshare passengers is associated with a different respective one of the plurality of historic ridesharing trips.

4. The rideshare assessment server of claim 1, wherein the sensor data includes one or more of velocity data, acceleration data, cornering data, and braking data.

5. A computer-implemented method for assessing driving performance, the method comprising:

receiving, by one or more processors, sensor data collected via a plurality of mobile computing devices during each of a series of historic ridesharing trips when rideshare passengers were being driven by a driver, each of the plurality of mobile computing devices being associated with a respective one of the rideshare passengers;

correlating, by the one or more processors, the sensor data to the driver associated with each of the series of historic ridesharing trips,

wherein the sensor data, when correlated to the driver, indicates one or more aspects of vehicle operation during each of the series of historic ridesharing trips when the rideshare passengers were being driven by the driver;

determining, by the one or more processors, an objective driver assessment of the driver based on the sensor data correlated to the driver by at least determining, by the one or more processors, (i) a day driver assessment, and (ii) a night driver assessment based on time periods associated with the series of historic ridesharing trips;

receiving, by the one or more processors, information indicative of a requested scheduled ride with the driver, the information identifying the driver; and

transmitting, by the one or more processors, one of the day driver assessment or the night driver assessment, based upon a time when the information indicative of the requested scheduled ride was received.

6. The computer-implemented method of claim 5, wherein determining the objective driver assessment further comprises:

determining, by the one or more processors, a subset of the series of historic ridesharing trips that are similar to the scheduled ride based on one or more of (i) an expected distance of the scheduled ride, (ii) a time associated with the start of the scheduled ride, and (iii) an expected duration of the scheduled ride.

7. The computer-implemented method of claim 6, further comprising:

determining, by the one or more processors, the objective driver assessment based on the subset of the series of historic ridesharing trips.

8. The computer-implemented method of claim 5, wherein the sensor data includes one or more of velocity data, acceleration data, cornering data, and braking data.

9. The computer-implemented method of claim 5, wherein determining the objective driver assessment further comprises:

determining, by the one or more processors, a first distance threshold from an origin of the scheduled ride and a second distance threshold from a destination of the scheduled ride;

determining, by the one or more processors, a subset of the series of historic ridesharing trips with at least one of an origin or a destination within the first distance threshold or the second distance threshold, respectively; and

determining, by the one or more processors, the objective driver assessment based on the subset of the series of historic ridesharing trips.

10. The computer-implemented method of claim 5, further comprising:

determining, by the one or more processors, whether the objective driver assessment satisfies a threshold score; and

in response to the objective driver assessment not satisfying the threshold, transmitting, by the one or more processors, a signal to cancel the scheduled ride.

11. The computer-implemented method of claim 10, wherein the signal to cancel the ride is received by a computing system associated with a ridesharing provider and causes the requested scheduled ride to be canceled.

12. The computer-implemented method of claim 10, wherein the signal to cancel the scheduled ride is received by a mobile computing device associated with a user requesting the scheduled ride, and causes the mobile computing device to provide a notification to the user to cancel the scheduled ride.

13. The computer-implemented method of claim 5, wherein determining the objective driver assessment further comprises:

comparing, by the one or more processors, the acceleration of the vehicle during one or more times during the series of historic ridesharing trips to one or more acceleration thresholds; and

determining, by the one or more processors, the objective driver assessment based on the comparisons.

14. The computer-implemented method of claim 5, wherein determining the objective driver assessment further comprises:

comparing, by the one or more processors, the velocity of the vehicle during one or more times during the series of historic ridesharing trips to one or more velocity thresholds; and

determining, by the one or more processors, the objective driver assessment based on the comparisons.

15. The computer-implemented method of claim 5, wherein determining the objective driver assessment further comprises:

determining, by the one or more processors, one or more durations of time associated with when the driver was driving in excess of a posted speed limit during the series of historic ridesharing trips; and

determining, by the one or more processors, the objective driver assessment based on the one or more durations of time.

16. A mobile computing device associated with a rideshare passenger, comprising:

a communication unit configured to receive, from one or more external computing devices associated with a ridesharing provider, information indicative of a start and an end of a rideshare trip, the information including an identification of a driver corresponding to the rideshare trip;

a sensor array configured to capture sensor data corresponding to movement of a vehicle in accordance with the start of a rideshare trip, and to stop capturing sensor data in accordance with the end of the rideshare trip, such that the sensor data is captured while the rideshare passenger is in the vehicle during the rideshare trip, wherein the mobile computing device is configured to determine the start and the end of the rideshare trip based on the received information indicative of the start and the end of the rideshare trip; and

a processor configured to calculate an objective driver assessment of the driver based on (i) the captured sensor data, and (ii) the information indicative of the start and the end of the rideshare trip,

wherein the communication unit is further configured to transmit data including the objective driver assessment to the one or more external computing devices associated with the ridesharing provider.

17. The mobile computing device of claim 16, wherein the sensor data includes one or more of velocity data, acceleration data, cornering data, and braking data.

18. The mobile computing device of claim 16, wherein the data transmitted by the communication unit includes one or more of a pickup location, a drop-off location, a duration of the rideshare trip, and route data.