System and method for modeling advanced automotive safety systems

• US 9,358,924 B1
• Filed: 05/07/2010
• Issued: 06/07/2016
• Est. Priority Date: 05/08/2009
• Status: Active Grant

• Current Assignee: Eagle Harbor Holdings, L.L.C., AutoBrilliance, LLC (Jeffrey M. Gross)
• Original Assignee: Eagle Harbor Holdings, L.L.C.
• Inventors: Preston, Dan Alan, Preston, Joseph David, Schofield, Kenneth, Manos, Thomas August
• Primary Examiner(s): Chen, Xi D
• Application Number:
  US12/776,137
• Time in Patent Office: 2,223 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: B60Q 9/00 Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00 , e.g. haptic signalling
• CPC Class Codes: G01V 11/002 Details, e.g. power supply systems for logging instruments, transmitting or recording data, specially adapted for well logging, also if the prospecting method is irrelevant means for transmitting well survey signals E21B47/12; signal transmission systems in general G08C; transmission in general H04B
• CPC Class Codes: G01V 13/00 Manufacturing, calibrating, cleaning, or repairing instruments or devices covered by groups G01V1/00 – G01V11/00
• CPC Class Codes: G06F 30/15 Vehicle, aircraft or watercraft design
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30

Abstract

A system and methods are disclosed for providing integrated software development environment for the design, verification and validation of advanced automotive safety systems. The system allows automotive software to be developed on a host computer using a collection of computer programs running simultaneously as processes and synchronized by a central process. The software disclosed uses separate synchronized processes, permitting signals from disparate sources to be generated by a simulation running on the host computer or from actual sensors and data bus signals coming from and going to actual vehicle hardware which is connected to their bus counterparts in the host computer on a real-time basis. The methods provide a data model that first extends the capabilities of the physical data model and then translates, gates, optimizes, fuses, filters and manages the physical representation of the logical model into a state estimation of the situation around the vehicle.

Claims

1. A state estimation method for vehicle sensors, comprising:

mounting a plurality of object detection sensors to a platform;

logging into a memory sensor data, wherein the memory comprises any hard disk, Read Only Memory (ROM), Dynamic Random Access (RAM) memory, or any combination of different memory devices;

connecting a controller to the plurality of object detection sensors, wherein the controller comprises at least one of a processor, a micro-controller, and a programmable logic device, and wherein the controller is operatively configured for;

receiving sensor reports from the object detection sensors,

determining a first mean value of a first object detection sensor report from a first object detection sensor detecting an object in a first detection, wherein the first mean value is an average value of the central tendency of a one-sigma probability error distribution of the first object detection sensor report in units of cross range and down range values, and wherein the one-sigma probability distribution of the first object detection sensor represents measurement errors and are represented in the same units of cross range and down range as variance of a the detected object,

logging into the memory the first mean value and first variance of the first detected object'"'"'s first detection from the first object detection sensor, wherein the logged first mean value and first variance of the detected object are stored values,

determining a second mean value of a second object detection sensor report from a second object detection sensor detecting the object in a second detection, wherein the second mean value is an average value of the central tendency of a one-sigma probability error distribution of the second object detection sensor report in units of cross range and down range values, and wherein the one-sigma probability distribution of the second object detection sensor represents measurement errors and are represented in the same units of cross range and down range as variance of a second detected object,

logging into the memory the second mean value and the second variance of the object in the second object detection, wherein the logged second mean value and second variance of the object from the second detection are stored values,

a third detection of the object by the first and second sensor,

transmitting the measured value of the third detection of the object from the first and second object detection sensors to the controller,

responsive to receiving the measured values of the third detection of the object, retrieve from the memory the stored values from the first and second object detection sensors,

determining a covariance value of the third detection of the object, using the retrieved stored values,

using the measured values of the third detection of the object, and the determined covariance value, use a filter to make a first estimate of state of the third detection of the object, wherein the first estimate of state is the result of combining the first sensor report with the second sensor report, and the first estimate of state includes at least one of position, velocity and acceleration of the third detection of the object, and

logging the first estimate of state and determined covariance value into the memory.

2. The method according to claim 1 wherein the object detection sensors include emitting and non-emitting non-contact sensors.

3. The method according to claim 1 wherein the data structure of the object detection sensor reports includes latency of the report.

4. The method of claim 1 wherein the structure of the sensor characterization system is a variable structure using interacting multiple models.

5. The method of claim 1 wherein the object detection sensor report comprises at least one of object kinematics or object attributes of the reported object.

6. The method of claim 1 wherein the sensor characterization system uses one of a track oriented or a measurement oriented data association process.

7. A sensor system, comprising:

a plurality of object detection sensors mounted to a platform;

a memory for logging sensor data, wherein the memory comprises any hard disk, Read Only Memory (ROM), Dynamic Random Access (RAM) memory, or any combination of different memory devices;

a controller connected to the plurality of object detection sensors, wherein the controller comprises at least one of a processor, a micro-controller, and a programmable logic device, and wherein the controller is operatively configured for;

receiving sensor reports from the object detection sensors,

determining a first mean value of a first object detection sensor report from a first object detection sensor detecting an object in a first detection, wherein the first mean value is an average value of the central tendency of a one-sigma probability error distribution of the first object detection sensor report in units of cross range and down range values, and wherein the one-sigma probability distribution of the first object detection sensor represents measurement errors and are represented in the same units of cross range and down range as variance of a the detected object,

logging into the memory the first mean value and first variance of the detected object'"'"'s first detection from the first object detection sensor, wherein the logged first mean value and first variance of the detected object are stored values,

determining a second mean value of a second object detection sensor report from a second object detection sensor detecting the object in a second detection, wherein the second mean value is an average value of the central tendency of a one-sigma probability error distribution of the second object detection sensor report in units of cross range and down range values, and wherein the one-sigma probability distribution of the second object detection sensor represents measurement errors and are represented in the same units of cross range and down range as variance of a second detected object,

logging into the memory the second mean value and the second variance of the object in the second detection, wherein the logged second mean value and second variance of the object from the second detection are stored values,

a third detection of the object by the first and second sensor,

transmitting the measured value of the third detection of the object from the first and second object detection sensors to the controller,

responsive to receiving the measured values of the third detection of the object, retrieve from the memory the stored values from the first and second object detection sensor,

determining a covariance value of the third detection of the object, using the retrieved stored values,

using the measured values of the third detection of the object, and the determined covariance value, use a filter to make a first estimate of state of the third detection of the object, wherein the first estimate of state is the result of combining the first sensor report with the second sensor report, and the first estimate of state includes at least one of position, velocity and acceleration of the third detection of the object, and

logging the first estimate of state and determined covariance value into the memory.

8. The system according to claim 7, wherein the object detection sensors include emitting and non-emitting non-contact sensors.

9. The system according to claim 7, wherein the data structure of the object detection sensor reports includes latency of the report.

10. The system of claim 7, wherein the structure of the sensor characterization system is a variable structure using interacting multiple models.

11. The system of claim 7, wherein the object detection sensor reports comprise at least one of object kinematics or object attributes of the reported object.

12. The system of claim 7, wherein the sensor characterization system uses one of a track oriented or a measurement oriented data association process.