Geospatial data based assessment of driver behavior

• US 8,510,200 B2
• Filed: 03/15/2012
• Issued: 08/13/2013
• Est. Priority Date: 12/02/2011
• Status: Active Grant

• Current Assignee: Spireon Incorporated (Solera Holdings Incorporated)
• Original Assignee: Spireon Incorporated (Solera Holdings Incorporated)
• Inventors: Pearlman, Richard Frank, Walsh, Sean Michael, Schantz, Daris Amon, Gertz, Steve
• Primary Examiner(s): Ebersman, Bruce I
• Application Number:
  US13/421,571
• Publication Number:
  US 20130141249A1
• Time in Patent Office: 516 Days
• Field of Search: None
• US Class Current: 705/36.R
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: G09B 19/14 Traffic procedures, e.g. traffic regulations
• CPC Class Codes: H04Q 2209/86 Performing a diagnostic of the sensing device
• CPC Class Codes: H04Q 9/00 Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom

Abstract

A method of geospatial data based assessment driver behavior to improve driver safety and efficiency is disclosed. A method of a server device may comprise determining that a telemetry data is associated with a vehicle communicatively coupled with the server device and comparing the telemetry data with a driver objective data. A variance between the telemetry data and the driver objective data may then be determined. A performance score may be generated upon comparison of the variance to a threshold limit and/or the driver objective data. The performance score may be published along with other performance scores of other drivers in other vehicles also communicatively coupled with the server device to a reporting dashboard module. Elements of game theory may be implemented to create a team driving challenge and/or a driver performance program to generate the performance score to improve driver safety and efficiency for commercial fleets.

Claims

1. A method of a server device, comprising:

determining, through the server device, telemetry data is associated with a vehicle of a plurality of vehicles communicatively coupled in contact with the server device;

comparing, through a processor of the server device communicatively coupled to a memory, the telemetry data with driver objective data associated with a driver of the vehicle;

determining, through the processor, a total variance between the telemetry data and the driver objective data,

wherein determining the total variance between the telemetry data and the driver objective data further comprises executing an algorithm by the processor,

wherein the algorithm, comprises;

calculating differences between the vehicle'"'"'s telemetry data to speed limit data, engine idling duration data, vehicle acceleration data, and vehicle deceleration data of the driver objective data,

dividing the calculated differences by their respective driver objective data to obtain percentage values, and

adding the percentage values to obtain the total variance;

generating, through the processor, a performance score of the driver indicative of an efficiency rating associable with the driver, based on the total variance; and

displaying, through a dashboard display of the vehicle through a reporting module, the performance score of the driver, along with performance scores of other drivers driving the plurality of vehicles,

wherein;

the speed limit data is a posted speed limit at a particular geospatial location surrounding a present location of the vehicle as determined through a mapping data source of the server device and calculating the difference between the vehicle'"'"'s telemetry data to the speed limit data comprises calculating the difference between the vehicle'"'"'s average speed and the posted speed limit,

the engine idling duration data is a predetermined and preferred amount of time an engine of a vehicle is idle in the geospatial vicinity surrounding the present location of the vehicle and calculating the difference between the vehicle'"'"'s telemetry data to the engine idling duration data comprises calculating the difference between the vehicle'"'"'s engine idling duration time and the predetermined and preferred amount of time,

the vehicle acceleration data is a predetermined and preferred average acceleration rate of a vehicle in the geospatial vicinity surrounding the present location of the vehicle and calculating the difference between the vehicle'"'"'s telemetry data to the vehicle acceleration data comprises calculating the difference between the vehicle'"'"'s average acceleration rate and the predetermined and preferred average acceleration rate, and

the vehicle deceleration data is a predetermined and preferred average deceleration rate of a vehicle in the geospatial vicinity surrounding the present location of the vehicle and calculating the difference between the vehicle'"'"'s telemetry data to the vehicle deceleration data comprises calculating the difference between the vehicle'"'"'s average deceleration rate and the predetermined and preferred average deceleration rate.

2. The method of claim 1, further comprising comparing the performance score associated with the driver to the plurality of performance scores associated with the other drivers.