Motor vehicle artificial intelligence expert system dangerous driving warning and control system and method

• US 10,814,784 B2
• Filed: 09/06/2019
• Issued: 10/27/2020
• Est. Priority Date: 09/27/2016
• Status: Active Grant

• Current Assignee: Robert D. Pedersen
• Original Assignee: Robert D. Pedersen
• Inventors: Pedersen, Robert D.
• Primary Examiner(s): McNally, Kerri L
• Assistant Examiner(s): Tran, Thang D
• Application Number:
  US16/563,427
• Publication Number:
  US 20190389381A1
• Time in Patent Office: 417 Days
• Field of Search: 340905
• CPC Class Codes: B60Q 9/008 for anti-collision purposes
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/048 Fuzzy inferencing
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G06V 20/597 Recognising the driver's state or behaviour, e.g. attention or drowsiness
• CPC Class Codes: G08G 1/0116 from roadside infrastructure, e.g. beacons
• CPC Class Codes: G08G 1/012 from other sources than vehicle or roadside beacons, e.g. mobile networks
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/048 with provision for compensation of environmental or other condition, e.g. snow, vehicle stopped at detector
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096741 where the source of the transmitted information selects which information to transmit to each vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station
• CPC Class Codes: G08G 1/096783 where the origin of the information is a roadside individual element
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes
• CPC Class Codes: G08G 1/167 Driving aids for lane monitoring, lane changing, e.g. blind spot detection
• CPC Class Codes: G08G 1/205 Indicating the location of the monitored vehicles as destination, e.g. accidents, stolen, rental
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 2021/02166 Microphone arrays; Beamforming
• CPC Class Codes: G10L 21/0232 : Processing in the frequency domain
• CPC Class Codes: G10L 25/78 : Detection of presence or absence of voice signals switching of direction of transmission by voice frequency in two-way loud-speaking telephone systems H04M9/10
• CPC Class Codes: H04B 5/26 : using coils
• CPC Class Codes: H04B 5/73 : for taking measurements, e.g. using sensing coils
• CPC Class Codes: H04B 5/77 : for interrogation
• CPC Class Codes: H04B 7/0617 : for beam forming
• CPC Class Codes: H04M 1/724098 : Interfacing with an on-board device of a vehicle for hands-free speaking in vehicles H04M1/6075
• CPC Class Codes: H04M 1/72454 : according to context-related or environment-related conditions
• CPC Class Codes: H04M 1/72463 : to restrict the functionality of the device
• CPC Class Codes: H04R 1/406 : microphones
• CPC Class Codes: H04R 2201/403 : Linear arrays of transducers
• CPC Class Codes: H04R 2499/13 : Acoustic transducers and sound field adaptation in vehicles
• CPC Class Codes: H04R 3/005 : for combining the signals of two or more microphones specially adapted for hearing aids H04R25/407
• CPC Class Codes: H04W 4/023 : using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• CPC Class Codes: H04W 4/40 : for vehicles, e.g. vehicle-to-pedestrians [V2P]
• CPC Class Codes: H04W 4/80 : Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
• CPC Class Codes: H04W 4/90 : Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS]

Abstract

Specifically programmed, integrated motor vehicle dangerous driving warning and control system and methods comprising at least one specialized communication computer machine including electronic artificial intelligence expert system decision making capability further comprising one or more motor vehicle electronic sensors for monitoring the motor vehicle and for monitoring activities of the driver and/or passengers including activities related to the use of cellular telephones and/or other wireless communication devices and further comprising electronic communications transceiver assemblies for communications with external sensor networks for monitoring dangerous driving situations, weather conditions, roadway conditions, pedestrian congestion and motor vehicle traffic congestion conditions to derive warning and/or control signals for warning the driver of dangerous driving situations and/or for controlling the motor vehicle driver use of a cellular telephone and/or other wireless communication devices.

Claims

1. An artificial intelligence expert system motor vehicle dangerous driving warning and control system comprising:

an electronic, specifically programmed, specialized device control communication computer machine including artificial intelligence expert system decision making capability;

multiple vehicle sensors generating motor vehicle driving warning and control system input signals;

integration of said artificial intelligence expert system motor vehicle dangerous driving warning and control system with a telematics system of said motor vehicle;

a vehicle camera sensor for generation of input signals derived from monitoring a vehicle driver and/or passenger activities wherein said signals may indicate danger to said vehicle, driver and/or passengers;

a vehicle lane tracking sensor for generation of input signals indicative of motor vehicle lane violations and/or swerving or excessive lane changing;

a vehicle electronic communication transceiver for receiving input signals from external sources including navigation information;

wherein said artificial intelligence expert system motor vehicle dangerous driving warning and control system further comprises artificial intelligence expert system decision making capability based on at least two of said input signals including signals from said vehicle camera sensor monitoring the vehicle driver and said vehicle lane tracking sensor to derive driver warning and/or control signals;

further wherein artificial intelligence expert system decision making is based on expert input with multiple propositional expert system instructions defining multiple ranges of degrees of danger for selected vehicle input signals; and

said artificial intelligence expert system decision making provides an integrated composite degree of danger driver warning index based on degree of danger input parameters for said selected vehicle input signals, including said vehicle camera sensor input signals for monitoring said vehicle driver and said vehicle lane tracking sensor input signals for monitoring said vehicle lane violations or excessive lane changing.

2. The system of claim 1 wherein vehicle sensors comprise camera and image analysis software for monitoring said motor vehicle driver'"'"'s eyes and position of the driver to verify driver attention to driving said vehicle.

3. The system of claim 1 wherein vehicle sensors comprise camera and image analysis software for generating warning signals responsive to lack of the driver paying attention to the road when using a hand-held device.

4. The system of claim 1 wherein vehicle sensors comprise a GPS (Global Positioning System) receiver for tracking changes in location and movements of the motor vehicle.

5. The system of claim 1 wherein vehicle sensors comprise one or more of camera sensors, proximity sensors, road tracking sensors, erratic driving behavior sensors, location sensors, weather sensors and/or other sensors used to monitor motor vehicle status and driving conditions.

6. The system of claim 1 further comprising one or more cameras, radar, and/or lidar vehicle sensors mounted on the motor vehicle for detecting dangerous driving conditions including situations wherein the motor vehicle is following vehicles in front too closely, vehicles behind the motor vehicle are following too closely, or motor vehicles being present in a “

blind spot”

on said motor vehicle driver or passenger side of a moving motor vehicle.

7. The system of claim 1 wherein said vehicle lane tracking sensors comprise lidar sensors.

8. The system of claim 1 wherein said vehicle sensors comprise radar sensors.

9. The system of claim 1 wherein said vehicle lane tracking sensors comprise cameras.

10. The system of claim 1 wherein said system artificial intelligence expert system motor vehicle dangerous driving warning and control system comprises maps for verifying that the motor vehicle is traveling on established highways or roadways.

11. The system of claim 1 wherein said artificial intelligence expert system decision making is based on at least one interior vehicle sensor output combined with said vehicle lane tracking sensor outputs for derivation of said integrated composite degree of danger driver warning index.

12. The system of claim 1 wherein said integration of said integrated motor vehicle dangerous driving warning and control system and the telematics system of said motor vehicle includes sharing of vehicle operational telematics display with vehicle dangerous driving warning and control system output signals informing the driver of driving situations and warnings.

13. The system of claim 1 wherein said camera for monitoring activities or situations involving the driver is positioned in front of the driver.

14. The system of claim 1 wherein said integrated composite degree of danger driver warning is an audible warning.

15. A method of operating an artificial intelligence expert system motor vehicle dangerous driving warning and control system comprising:

the step of storing in memory of an electronic, specifically programmed, specialized device control communication computer machine artificial intelligence expert system decision making instructions;

the step of generating motor vehicle driving warning and control system input signals from multiple vehicle sensors;

the step of integration of said artificial intelligence expert system motor vehicle dangerous driving warning and control system and a telematics system of said motor vehicle;

the step of generating sensor signals from one or more interior vehicle sensors including at least one camera sensor for monitoring a motor vehicle driver and/or passenger activities wherein said signals may indicate danger to said vehicle, driver and/or passengers;

the step of generating sensor signals from one or more vehicle motion sensors including one or more vehicle lane tracking sensors, said sensor signals indicative of lane violations and/or of motor vehicle swerving or excessive lane changing;

the step of communicating via a vehicle transceiver with external sources to receive information signal inputs including navigation information;

the step of said artificial intelligence expert system motor vehicle dangerous driving warning and control system using said artificial intelligence expert system decision making capability based on at least two of said signal inputs including inputs from at least one camera monitoring said vehicle driver and at least one lane tracking sensor to derive driver warning and/or control signals;

the step of basing artificial intelligence expert system decisions on expert input with multiple propositional expert system program instructions defining multiple ranges of degrees of danger for selected of said motor vehicle sensor signal inputs, and

the step of said artificial intelligence expert system providing an integrated composite degree of danger driver warning index based at least on degree of danger input parameters for said selected motor vehicle sensor inputs, including said camera sensor signal inputs for monitoring said vehicle driver and said vehicle lane tracking sensor signal inputs for monitoring said vehicle lane violations or excessive lane changing.

16. The method of claim 15 further comprising the step of monitoring said vehicle driver'"'"'s eyes and position of driver to verify driver attention to driving said vehicle.

17. The method of claim 15 further comprising the step of tracking changes in location and movements of the motor vehicle using a GPS (Global Positioning System) receiver.

18. The method of claim 15 further comprising the step of using one or more of camera sensors, proximity sensors, road tracking sensors, erratic driving behavior sensors, location sensors, weather sensors and/or other sensors used to monitor motor vehicle status and driving conditions.

19. The method of claim 15 further comprising the step of using external cameras, radar, and/or lidar sensors mounted on the motor vehicle for detecting dangerous driving conditions including situations when the motor vehicle is following vehicles in front too closely, vehicles behind the motor vehicle are following too closely, or motor vehicles being present in a “

blind spot”

on said motor vehicle driver or passenger side of a moving motor vehicle.

20. The method of claim 15 further comprising the step of using electronic roadway maps with artificial intelligence expert system motor vehicle dangerous driving warning and control system operations.