DRIVER PERFORMANCE METRIC

• US 20160362118A1
• Filed: 08/25/2016
• Published: 12/15/2016
• Est. Priority Date: 08/31/2011
• Status: Abandoned Application

• Current Assignee: Pulsar Informatics, Inc.
• Original Assignee: Pulsar Informatics, Inc.
• Inventors: Mollicone, Daniel Joseph, Kan, Kevin Gar Wah, Biondo, Damian Marcus, Mott, Christopher Grey
• Application Number:
  US15/247,816
• Publication Number:
  US 20160362118A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60W 2050/046 involving external transmission of data to or from the vehicle, e.g. via telemetry, satellite, Global Positioning System [GPS]
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 40/09 Driving style or behaviour
• 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 1/0238 using obstacle or wall sensors G05D1/0246 and G05D1/0289 take precedence; lidar systems designed for anti-collision purposes G01S17/93
• 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: G07C 5/0816 Indicating performance data, e.g. occurrence of a malfunction
• CPC Class Codes: G08G 1/16 Anti-collision systems road vehicle drive control systems for predicting or avoiding probable or impending collision otherwise than by control of a particular sub-unit B60W30/08
• CPC Class Codes: G09B 19/167 Control of land vehicles

Abstract

Systems and methods for quantifiable assessment of vehicle driver performance based upon objective standards are disclosed. The physical and/or control states of a vehicle are monitored by sensors during a driving trip. Measurement data, optionally comprising a measurement signal, is composed from parameters selected from the measured physical and/or control states. The measurement data is then compared to reference data, optionally comprising a reference signal, comprising the same or similar physical and control state parameters, for the same or analogous driving trip or portion thereof, including discrete driving tasks, as determined by one or more of: a known driver of specific attributes, a population average, or an autonomous driving algorithm. A driver performance level may be determined as one or more characteristic metrics of a driving task, according to one or more path metrics of a driving task, or as a signal distance metric between the reference and measurement signals.

Claims

1. A method, using a computer, for assessing driver performance relative to a standard of performance, the method comprising:

receiving, at a computer, a vehicle location state from a vehicle location sensor, the vehicle location state representing the geographical location of the vehicle;

identifying, with the computer, a road segment corresponding to the received vehicle location state, the identified road segment comprising a road segment type and one or more road segment parameters, the road segment type representing a category to which the road segment belongs, and the one or more road segment parameters comprising numeric values corresponding to geometric characteristics of the road segment;

receiving measurement data at the computer from one or more of;

a steering sensor, an accelerator sensor, a brake sensor, a clutch sensor, gearing sensor, a turn signal sensor, a hazard light sensor, a windshield-wiper sensor, an entertainment-system sensor, a parking-brake sensor, fuel-gauge sensor, throttle-angle sensor, an engine-speed sensor, a turbine-speed sensor, an engine-torque sensor, a driven-wheel speed sensor, a drive-wheel speed sensor, a fuel-flow sensor, fuel-injection system sensor, and an engine-piston firing period sensor, a vehicle position sensor, a vehicle orientation sensor, a vehicle speed sensor, a vehicle acceleration sensor, sensors for determining or more time derivatives of the vehicle'"'"'s orientation, a lane-position sensor, and a collision-risk sensor;

the measurement data indicative of one or more vehicle state parameters corresponding to a driver operating the vehicle on at least a portion of the identified road segment;

receiving, from an automated driving unit, reference data at the computer, the reference data comprising one or more vehicle state parameters corresponding to target values of the one or more vehicle state parameters comprising the received measurement data;

determining, at the computer, at least one driver performance level based at least in part on the received measurement data and the received reference data, the driver performance level indicative of an assessment of the driver operating the vehicle relative to the standard of performance for at least a portion of the identified road segment; and

invoking, with the computer, one or more alert events based upon the determined driver performance levels.

2. A method according to claim 1, wherein the invoked alert event comprises one or more of:

activating a light in a cabin of the vehicle, activating a sound in cabin of the vehicle, providing haptic feedback to a driver of the vehicle, opening or closing a window of the vehicle, and increasing or decreasing the volume of a sound system in the vehicle.

3. A method according to claim 1, wherein the invoked alert event comprises one or more of:

activating an autonomous driving mode of the vehicle, decreasing the speed of a vehicle, activating a braking system of the vehicle, and immobilizing the vehicle.

4. A method according to claim 1, wherein the invoked alert event comprises one or more of:

notifying a dispatcher, notifying law enforcement, notifying a regulatory agency, notifying a first responder, altering a delivery schedule for freight on the vehicle, altering a driving schedule for a driver of the vehicle, altering a sleep schedule for a driver of the vehicle.

5. A method according to claim 1 wherein receiving the measurement data at a computer comprises receiving a measurement signal at the computer, the measurement signal being comprised of one or more time series functions of vehicle state parameters corresponding to a driver operating a vehicle.

6. A method according to claim 1 wherein receiving reference data at the computer comprises receiving a reference signal at the computer, the reference signal comprising one or more time series functions of vehicle state parameters corresponding to target values of the one or more vehicle state parameters comprising the received measurement data.

7. A method according to claim 1, further comprising

identifying one or more driving tasks, based at least in part on the received vehicle location state and the received measurement data;

wherein receiving the reference data is based at least in part on the road segment and the identified one or more driving tasks.

8. A method according to claim 1 wherein at least one of the one or more driving tasks is characterized by one or more of:

a start time, a start location, an end time, an end location, one or more intermediate locations, one or more road segment parameters, and one or more environmental factors.

9. A method according to claim 1 wherein the one or more road segment parameters comprise one or more of:

a radius of curvature, a speed limit, a number of driving lanes comprising the roadway, a width of a driving lane comprising the roadway, a geographic location, and a measure of straightness of the roadway.

10. A method according to claim 1 further comprising:

receiving, at the computer, environmental-factor data comprising one or more of;

the presence of another vehicle, the presence of a pedestrian, the presence of an obstacle in the roadway, a climate condition, and a temperature.

11. A method according to claim 10 further comprising:

identifying one or more driving tasks based at least in part on the received environmental-factor data, the driving tasks being indicative of a portion of the identified road segment with a common environmental factor;

wherein selecting the reference data is based at least in part on the identified driving tasks.

12. A method according to claim 1, wherein at least one of the one or more driving tasks comprising the driving trip is associated with a driving-task classification.

13. A method according to claim 12 wherein the driving task classification comprises one or more of:

a straightaway, a straightway with a fixed obstacle, a straightaway with another vehicle moving in a fixed direction, a straightaway with another vehicle moving in an unpredictable pattern, a straightaway with two or more vehicles moving in a fixed direction, a straightaway with two or more vehicles moving in an unpredictable pattern, a curve with an approximately constant radius of curvature, a curve with an approximately constant radius of curvature and with a fixed obstacle in the roadway, a curve with an approximately constant radius of curvature with another vehicle moving in a fixed direction, a curve with an approximately constant radius of curvature with another vehicle moving in an unpredictable pattern, a curve with an approximately constant radius of curvature with two or more vehicles moving in a fixed direction, and a curve with an approximately constant radius of curvature with two or more vehicles moving in an unpredictable pattern.

14. A method according to claim 12 wherein at least one of the one or more driving tasks comprising the driving trip is classified as a curve;

wherein the received reference data comprises at least in part one or more of;

a radius of curvature, lane tracking data, and steering wheel deviation data; and

wherein the determined driver performance level comprises at least in part one or more of;

a radius-of-curvature deviation metric, a lane tracking metric, and a steering-wheel deviation metric.

15. A method, using a computer, for assessing driver performance relative to a standard of performance, the method comprising:

receiving, at a computer, a vehicle location state from a vehicle location sensor, the vehicle location state representing the geographical location of the vehicle;

identifying, with the computer, a road segment corresponding to the received vehicle location state, the identified road segment comprising a road segment type and one or more road segment characteristics, the road segment type representing a category to which the road segment belongs, and the one or more road segment characteristics identifying parameters of the road segment specific to the road segment type;

receiving, from at least one vehicle state sensor, measurement data at the computer, the measurement data indicative of one or more vehicle state parameters corresponding to a driver operating the vehicle on at least a portion of the identified road segment;

receiving, from a driver population module, driver-population data comprising vehicle state data corresponding to how one or more driver drivers navigated the identified road segment;

creating, with the computer, reference data based at least in part on the received driver-population data, the reference data indicative of one or more vehicle state parameters corresponding to a standard of performance for the vehicle on at least a portion of the identified road segment;

determining, at the computer, at least one driver performance level based at least in part on the received measurement data and the received reference data, the driver performance level indicative of an assessment of the driver operating the vehicle relative to the standard of performance for at least a portion of the identified road segment; and

invoking, with the computer, one or more alert events based upon the determined driver performance levels.

16. A method according to claim 15 where in creating the reference data based at least in part on the received driver-population data comprises calculating a statistical measure of received driver-population data corresponding to one or more drivers.

17. A method according to claim 16 wherein calculating the statistical measure comprises calculating a mean value of the received driver-population data corresponding to the one or more drivers.