RECORDING, MONITORING, AND ANALYZING DRIVER BEHAVIOR

• US 20170148350A1
• Filed: 02/07/2017
• Published: 05/25/2017
• Est. Priority Date: 12/11/2012
• Status: Active Grant

• Current Assignee: Abalta Technologies, Inc.
• Original Assignee: Abalta Technologies, Inc.
• Inventors: Stankoulov, Pavel
• Granted Patent: US 9,898,936 B2
• Time in Patent Office: Days
• CPC Class Codes: B60W 2420/408 Radar; Laser, e.g. lidar
• CPC Class Codes: B60W 2540/30 Driving style
• CPC Class Codes: B60W 2552/05 Type of road, e.g. motorways, local streets, paved or unpaved roads
• CPC Class Codes: B60W 2555/60 Traffic rules, e.g. speed limits or right of way
• CPC Class Codes: B60W 2756/10 Involving external transmission of data to or from the vehicle
• CPC Class Codes: B60W 40/09 Driving style or behaviour
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: G09B 19/167 Control of land vehicles
• CPC Class Codes: G09B 29/003 Maps

Abstract

A system adapted to monitor, record and analyze driver performance is described. The system includes: a vehicle sensor module adapted to receive data from a set of sensors that each measure a driving characteristic associated with a vehicle; a map data access module adapted to retrieve, from a map database, map data elements indicating various features associated with at least one path of the vehicle; and a driver behavior engine adapted to receive information from the vehicle sensor module and the map data access module, and to monitor and evaluate driver performance based on the received information.

Claims

1. A system that monitors, records and analyzes driver performance, the system comprising a server having:

a map data access module that retrieves, from a map database, map data elements indicating various features associated with at least one path of at least one vehicle, wherein the at least one path comprises a set of previously-defined segments, each segment having a set of associated points, wherein each associated point comprises a set of associated attributes, each set of associated attributes comprising a set of fixed attributes, wherein each fixed attribute has an unchanging value for each set of associated points;

a communication module that receives information from at least one vehicle, the received information comprising data from a set of sensors that each measure a driving characteristic associated with a vehicle;

a driver behavior engine that monitors and evaluates driver performance based on the received information by;

generating a plurality of sets of evaluation curves based on the retrieved set of map data elements; and

calculating mathematical differences between each evaluation curve from each set of evaluation curves and each of a plurality of corresponding performance curves generated at least partly based on the set of measured driving characteristics, wherein the mathematical differences are quantified at least partly by determining a geometrical area between each evaluation curve from each set of evaluation curves and each corresponding performance curve from the plurality of corresponding performance curves, wherein the sets of evaluation curves and the plurality of corresponding performance curves are associated with a particular driver and a particular trip.

2. The system of claim 1, wherein the vehicle sensor module receives data from at least one of:

at least one global navigation satellite system (GNSS) sensor,

at least one inertial sensor, and

at least one radar sensor.

3. The system of claim 1, wherein the received information is transferred over a wireless connection.

4. The system of claim 1, wherein the information is received, the evaluation curves are generated, and the mathematical differences are calculated in real time during operation of the at least one vehicle.

5. The system of claim 1, wherein the information is received, the evaluation curves are generated, and the mathematical differences are calculated during or after operation of the at least one vehicle.

6. The system of claim 1, wherein the driver behavior engine, based at least partly on the calculated mathematical difference, identifies at least one of an event, error, warning, and score and the communication module sends the at least one of an event, error, warning, and score to the at least one vehicle in real time during operation of the at least one vehicle.

7. The system of claim 1, wherein the driver behavior engine, based at least partly on the calculated mathematical difference, identifies at least one of an event, error, warning, and score during or after operation of the at least one vehicle.

8. The system of claim 1 further comprising a path prediction engine that receives data from the vehicle sensor module and the map data access module and identifies a set of candidate links ahead of the vehicle in order to determine a set of potential paths available to the vehicle based at least partly on the received data, wherein:

each potential path in the set of potential paths is associated with a particular probability, and

each candidate link in the set of candidate links is associated with at least one potential path from the set of potential paths.

9. The system of claim 1 further comprising an event logging engine that receives data from the vehicle sensor module and records the received data to a database.

11. The automated method of claim 8 further comprising receiving, at the vehicle sensor module, data from at least one of:

at least one global navigation satellite system (GNSS) sensor,

at least one inertial sensor, and

at least one radar sensor.

12. The automated method of claim 8 further comprising receiving, at a path prediction engine, data from the vehicle sensor module and the map data access module and identifying a set of candidate links ahead of the vehicle in order to determine a set of potential paths available to the vehicle based at least partly on the received data, wherein:

each potential path in the set of potential paths is associated with a particular probability, and

each candidate link in the set of candidate links is associated with at least one potential path from the set of potential paths.

13. The automated method of claim 8 further comprising receiving, at an event logging engine, data from the vehicle sensor module and recording the received data to a database.

14. The automated method of claim 8 further comprising determining, at a warning module, whether data received from the vehicle sensor module exceeds any warning threshold.

10. An automated method of evaluating driver performance, the method comprising:

retrieving, from a map database, at a map data access module, map data elements indicating various features associated with at least one path of at least one vehicle, wherein the at least one path comprises a set of previously-defined segments, each segment having a set of associated points, wherein each associated point comprises a set of associated attributes, each set of associated attributes comprising a set of fixed attributes, wherein each fixed attribute has an unchanging value for each set of associated points;

receiving, at a communication module, information from at least one vehicle, the received information comprising data from a set of sensors that each measure a driving characteristic associated with a vehicle;

monitoring and evaluating, at a server-based driver behavior engine, driver performance based on the received information;

retrieving, at the server-based driver behavior engine, a plurality of sets of evaluation curves based on the retrieved set of map data elements; and

calculating, at the server-based driver behavior engine, mathematical differences between each evaluation curve from each set of evaluation curves and each of a plurality of corresponding performance curves generated at least partly based on the set of measured driving characteristics, wherein the mathematical differences are quantified at least partly by determining a geometrical area between each evaluation curve from each set of evaluation curves and each corresponding performance curve from the plurality of corresponding performance curves, wherein the sets of evaluation curves and the plurality of corresponding performance curves are associated with a particular driver and a particular trip.

15. An automated method of analyzing a geographic area, the method comprising:

retrieving map data associated with the geographic area;

identifying a set of links associated with the retrieved map data;

identifying a set of nodes associated with the retrieved map data, wherein each node from the set of nodes comprises a node identifier and a set of connected link identifiers; and

storing data elements associated with each link in the set of links and data elements associated with each node in the set of nodes.

16. The automated method of claim 15, wherein each data element associated with each link in the set of links comprises:

a unique link identifier;

a plurality of link attributes, wherein;

each and every link attribute from the plurality of link attributes is unchanging over a length of the link, and

the plurality of link attributes comprises at least one of a functional class, road type, posted speed limit, speed category, and the length of the link;

a from-node identifier associated with a first node from the set of nodes; and

a to-node identifier associated with a second node from the set of nodes.

17. The automated method of claim 15 further comprising generating a set of evaluation curves based at least partly on the identified set of links and the identified set of nodes.

18. The automated method of claim 17, wherein each link in the set of links comprises a plurality of points and each curve from the set of evaluation curves comprises a plurality of corresponding points, wherein the value of each corresponding point for a particular evaluation curve from the set of evaluation curves may be different than values of adjacent corresponding points.

19. The automated method of claim 18, wherein each evaluation curve from the set of evaluation curves comprises a plurality of interpolated points between the corresponding points.

20. The automated method of claim 15 further comprising identifying a set of driving restriction data elements associated with the retrieved map data.