GNSS/IMU positioning, communication, and computation platforms for automotive safety applications

• US 9,099,003 B2
• Filed: 12/06/2013
• Issued: 08/04/2015
• Est. Priority Date: 07/15/2010
• Status: Active Grant

• Current Assignee: Uatc, LLC (Uber Technologies, Inc.)
• Original Assignee: George C. Dedes, Kyriakos C. Mouskos
• Inventors: Mouskos, Kyriakos C., Dedes, George C.
• Primary Examiner(s): CHEUNG, CALVIN K
• Application Number:
  US14/099,271
• Publication Number:
  US 20140100713A1
• Time in Patent Office: 606 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: B60T 2201/08 Lane monitoring; Lane Keeping Systems
• CPC Class Codes: B60T 2210/36 Global Positioning System [GPS]
• CPC Class Codes: G01C 21/165 combined with non-inertial navigation instruments
• CPC Class Codes: G01C 21/3697 Output of additional, non-guidance related information, e.g. low fuel level G01C21/3679 takes precedence
• CPC Class Codes: G08G 1/163 involving continuous checking
• CPC Class Codes: G08G 1/164 Centralised systems, e.g. external to vehicles

Abstract

A GNSS/IMU safety sensor platform is disclosed consisting of data fusion Processors, GNSS Acquisition and Tracking Processors, MEMS IMU sensors, one or multiple accelerometers able to provide orientation information, optional V2V communication modules, and optional V2I communication modules. The data fusion processors provide interface ports to GNSS/IMU processors, odometers, video (Visual/Infrared) cameras installed in the vehicle, V2V relative positioning sensors (laser, radar or any other distance measuring), and V2V and V2I communication modules. The data fusion processors are interfaced to a driver warning system and optionally to the vehicle controls for providing safety warning messages to drivers, or for automatic control of the vehicle for preventing and reducing accidents.

Claims

1. An automotive safety system comprising:

a central data fusing processor;

a global navigation satellite system (GNSS) signal tracking and acquisition device on a host vehicle;

an Inertial Measurement Unit (IMU) sensor on the host vehicle; and

a GNSS/IMU integration processor on the host vehicle configured to receive data from the GNSS signal tracking and acquisition device and the (IMU) sensor and transmit integrated data to the central data fusing processor.

2. The system of claim 1, wherein the IMU sensor is one or more accelerometers distributed over the host vehicle.

3. The system of claim 1, wherein the central data fusing processor resides inside a remote server located within an internet cloud infrastructure.

4. The system of claim 1, wherein the central data fusing processor is configured to optimally combine at least two of the integrated data, host vehicle accelerometer measurements, host vehicle radar measurements, host vehicle video data, host vehicle compass measurements, or host vehicle inclinometer measurements to improve position and orientation estimation of the host vehicle.

5. The system of claim 1, wherein the central data fusing processor is configured to optimally combine position and orientation information of the host vehicle with vehicle dynamics theory for different types of vehicles to estimate impending accidents and issue warnings to a driver of the host vehicle or automatically invoke host vehicle controls in order to avoid accidents.

6. The system of claim 1, wherein the central data fusing processor is configured to predict one or more impending accidents, issue warning messages to a driver of the host vehicle, and issue commands automatically to the vehicle controls to avoid impending accidents for which the driver has not enough time to respond.

7. An automotive safety system comprising:

a central data fusing processor;

a Vehicle-2-Vehicle (V2V) communication module;

a Vehicle-2-Infrastructure (V2I) communication module;

a global navigation satellite system (GNSS) signal tracking and acquisition device on a host vehicle;

an Inertial Measurement Unit (IMU) sensor on the host vehicle; and

a GNSS/IMU integration processor on the host vehicle configured to receive data from the GNSS signal tracking and acquisition device and the IMU sensor and transmit integrated data to the central data fusing processor.

8. The system of claim 7, wherein the IMU sensor is one or more accelerometers distributed over the host vehicle.

9. The system of claim 7, wherein the central data fusing processor is configured to predict one or more impending accidents, issue warning messages to a driver of the host vehicle, and issue commands automatically to the vehicle controls to avoid impending accidents for which the driver has not enough time to respond.

10. The system of claim 7, wherein the central data fusing processor resides inside a remote server located within an internet cloud infrastructure.

11. The system of claim 7, wherein the host vehicle is part of a network and the central data fusing processor, the V2V communication module, and the V2I communication module are configured to issue one or more warnings to other vehicles in the network.

12. The system of claim 7, wherein the host vehicle is part of a network and the central data fusing processor is configured to issue one or more warnings to a driver of the host vehicle from one or more other vehicles in the network.

13. The system of claim 7, wherein the host vehicle is part of a network and the central data fusing processor is configured to optimally combine GNSS measurements from other vehicles in the network with corresponding measurements of the host vehicle to estimate relative position of the host vehicle with respect to other vehicles in the network.

14. The system of claim 7, wherein the host vehicle and other vehicles are part of a network and the central data fusing processor is configured to optimally combine the relative position, speed and orientation of the host vehicle with respect to other vehicles in the network using vehicle dynamics theory for different type of vehicles to compute the real-time trajectories of the host vehicle and other vehicles in the network and predict one or more impending accidents.

15. A method of processing automotive safety information comprising:

receiving, by a global navigation satellite system/inertial measurement unit (GNSS/IMU) integration processor on a host vehicle, data from a GNSS signal tracking and acquisition device on the host vehicle;

receiving, by the GNSS/IMU integration processor, data from at least one of an IMU sensor or distributed accelerometers on the host vehicle; and

transmitting, from the GNSS/IMU integration processor, integrated data to a central data fusing processor.

16. The method of claim 15, further comprising:

estimating optimally in real-time, by the central data fusing processor, position and orientation of the host vehicle using the integrated data.

17. The method of claim 16, further comprising:

receiving, by the central data fusing processor, data from a Vehicle-2-Vehicle (V2V) communication module;

receiving, by the central fusing processor, data from a Vehicle-2-Infrastructure (V2I) communication module; and

estimating optimally in real-time, by the central data fusing processor, relative position of the host vehicle with respect to neighboring vehicles using the integrated data and one or more of data from the V2V communication module or data from the V2I communication module.

18. The method of claim 17, further comprising:

predicting, by the central data fusing processor, one or more impending accidents; and

transmitting, by the central data fusing processor, one or more warnings to one or more of the V2V communication module or the V2I communication module.

19. The method of claim 17, further comprising:

receiving, by the central data fusing processor, one or more warnings from one or more of the V2V communication module or the V2I communication module; and

transmitting, by the central data fusing processor, at least one of all or selected warning messages to a driver of the host vehicle or commands to host vehicle controls to avoid one or more impending accidents.

20. The method of claim 17, further comprising:

combining optimally, by the central data fusing processor, data from one or more of the V2V communication module or the V2I communication module comprising at least two of other vehicle IMU measurements, other vehicle radar measurements, other vehicle video image measurements, other vehicle compass measurements, other vehicle inclinometer measurements, or other vehicle sensor measurements to compute relative position and relative orientation of the host vehicle with respect to one or more other vehicles.