US7034742B2
Expired / Lapsed
US
⏱️ 0.0 years remaining
Road curvature estimation and automotive target state estimation system
Assignee: Joyson Safety Systems Acquisition LLC
•
Filing: 2003-07-15
•
Granted: 2006-04-25
•
Expires: 2023-07-15
Abstract
Abstract A first Kalman filter estimates true measures of yaw rate and vehicle speed from associated noisy measures thereof generated by respective sensors in a host vehicle, and a second Kalman filter estimates therefrom parameters of a clothoid model of road curvature. Measures of range, range rate, and azimuth angle from a target state estimation subsystem, e.g. a radar system, are processed by an extended Kalman filter to provide an unconstrained estimate of the state of a target vehicle. Associated road constrained target state estimates are generated for one or more roadway lanes, and are compared—either individually or in combination—with the unconstrained estimate. If a constrained target state estimate corresponds to the unconstrained estimate, then the state of the target vehicle is generated by fusing the unconstrained and constrained estimates; and otherwise is given by the unconstrained estimate alone.
Inventors
- 👤 Shan Cong
- 👤 Shi Shen
- 👤 Lang Hong
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-10-25 03:59
CPC Classifications
G; G01; G01S; G01S13/00; G01S13/88; G01S13/93; G01S13/931; B; B60; B60K; B60K31/00; B60K31/0008; B60K31/0066; B60K31/12; G01S13/02; G01S13/50; G01S13/58; G01S13/66; G01S13/72; G01S13/723; G01S13/86; B60T; B60T2210/00; B60T2210/20; B60T2210/24; B60T2260/00; B60T2260/08; B60W; B60W50/00; B60W2050/0001; B60W2050/0043; B60W2050/0052; B60W2520/00; B60W2520/14; B60W2552/00; B60W2552/20; B60W2552/30; B60W2554/00; B60W2554/40; B60W2554/404; B60W2554/4041; B60W2554/4042; B60W2554/4043; B60W2554/80; B60W2554/803; B60W2554/804; G01S2013/932; G01S2013/9325; G01S2013/9327; G01S2013/93271
Claims Analysis
Total Claims: 23
Claim 1
Independent Claim
228 words
A method of estimating a state of a target vehicle on a roadway, comprising: a. generating an estimate of a curvature of the roadway; b. estimating an unconstrained state and associated covariance thereof of the target vehicle; c. establishing at least one prospective constraint of the target vehicle, wherein at least one prospective constraint is responsive to said estimate of the curvature of the roadway; d. estimating at least one constrained state and associated covariance thereof of the target vehicle corresponding to said at least one prospective constraint of the target vehicle; e. determining a most likely state of the target vehicle, wherein said most likely state of the target vehicle is selected from said unconstrained state of the target vehicle and said at least one constrained state of the target vehicle; and f. if said at least one constrained state of the target vehicle is the most likely state, then fusing the unconstrained state and covariance thereof of the target vehicle with the associated constrained state and covariance of said most likely state and outputting at least one of the fused state and the associated fused covariance thereof of the target as the estimated state or covariance of the target; otherwise outputting at least one of the unconstrained state and the associated unconstrained covariance thereof of the target as the estimated state or covariance of the target.
Claim 2
Independent Claim
228 words
A method of estimating a state of a target vehicle on a roadway, comprising: a. generating an estimate of a curvature of the roadway; b. estimating an unconstrained state and associated covariance thereof of the target vehicle; c. establishing at least one prospective constraint of the target vehicle, wherein at least one prospective constraint is responsive to said estimate of the curvature of the roadway; d. estimating at least one constrained state and associated covariance thereof of the target vehicle corresponding to said at least one prospective constraint of the target vehicle; e. determining a most likely state of the target vehicle, wherein said most likely state of the target vehicle is selected from said unconstrained state of the target vehicle and said at least one constrained state of the target vehicle; and f. if said at least one constrained state of the target vehicle is the most likely state, then fusing the unconstrained state and covariance thereof of the target vehicle with the associated constrained state and covariance of said most likely state and outputting at least one of the fused state and the associated fused covariance thereof of the target as the estimated state or covariance of the target; otherwise outputting at least one of the unconstrained state and the associated unconstrained covariance thereof of the target as the estimated state or covariance of the target.
Claim 3
Dependent Claim
112 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 1 , wherein the operation of estimating the curvature of the roadway comprises: a. generating a speed measurement by measuring a longitudinal speed of a host vehicle traveling on the roadway; b. generating a yaw rate measurement by measuring or determining a yaw rate of said host vehicle; and c. estimating at least one curvature parameter, wherein said at least one curvature parameter is representative of a curvature of the roadway, and the operation of estimating at least one curvature parameter is responsive to said speed measurement and is responsive to said yaw rate measurement.
Claim 4
Dependent Claim
53 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 2 , wherein said at least one curvature parameter comprises at least one parameter of a clothoid model of curvature, and said Clothoid model of curvature is referenced to a coordinate system of said host vehicle.
Claim 5
Dependent Claim
57 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 3 , wherein said at least one curvature parameter comprises first and second parameters of a clothoid model, wherein said first parameter is a constant, and said second parameter is a sensitivity of curvature to a distance along the roadway.
Claim 6
Dependent Claim
44 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 2 , wherein the operation of estimating at least one curvature parameter comprises processing said measurements of speed and yaw rate with at least one Kalman filter.
Claim 7
Dependent Claim
81 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 5 , wherein said at least one Kalman filter comprises first and second Kalman filters, said first Kalman filter is adapted to estimate a first set of state variables from said speed measurement and from said yaw rate measurement, and said second Kalman filter is adapted to estimate said at least one curvature parameter from said estimate of said first set of state variables.
Claim 8
Dependent Claim
38 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 6 , wherein said first set of state variables comprises vehicle velocity, vehicle acceleration, vehicle yaw rate and vehicle yaw acceleration.
Claim 9
Dependent Claim
83 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 1 , wherein the operation of estimating an unconstrained state and associated covariance of the target vehicle comprise: a. measuring a range, a range rate and an azimuth of the target vehicle relative to a host vehicle; and b. estimating said unconstrained state of the target vehicle from said measurements of the range, range rate and azimuth of the target vehicle relative to the host vehicle.
Claim 10
Dependent Claim
46 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 1 , further comprising the operation of transforming said unconstrained state of the target vehicle to a coordinate system corresponding to said estimate of the curvature of the roadway.
Claim 11
Dependent Claim
50 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 1 , wherein said at least one prospective constraint of the target vehicle is applied to a lateral position of the target vehicle, and a longitudinal position of the target vehicle is unconstrained.
Claim 12
Dependent Claim
50 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 1 , wherein said at least one prospective constraint of the target vehicle comprises a plurality of prospective constraints, and at least two different prospective constraints correspond to different lanes of the roadway.
Claim 13
Dependent Claim
158 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 1 , wherein the operation of determining the most likely state of the target vehicle comprises: a. determining at least one likelihood value, wherein said a least one likelihood value corresponds to said at least one prospective constraint of the target vehicle being active and said at least one likelihood value is responsive to a corresponding at least one distribution function evaluated at a value corresponding to said unconstrained state of the target vehicle; b. determining a probability of a first constrained state of the target vehicle, wherein said probability is responsive to said at least one likelihood value; c. testing at least one hypothesis that said unconstrained state of the target vehicle corresponds to said first constrain state, and d. identifying a most likely state of the target vehicle responsive to the operation of testing said at least one hypothesis.
Claim 14
Dependent Claim
91 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 12 , wherein the operation of determining the most likely state of the target vehicle comprises establishing at least one a priori probability of a transition from a first state to a second state of the target vehicle, wherein said first and second states can be either the same or different states, and, said probability of said first constrained state of the target vehicle is responsive to said at least one a priori probability.
Claim 15
Dependent Claim
40 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 12 , wherein said at least one distribution function is responsive to said covariance of the particular constrained state of the target vehicle.
Claim 16
Dependent Claim
46 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 12 , wherein said at least one constrained state comprises a plurality of constrained states, and said first constrained state comprises a combination of said plurality of constrained states.
Claim 17
Dependent Claim
39 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 12 , wherein said first constrained state comprises a most likely of said at least one constrained state of the target vehicle.
Claim 18
Dependent Claim
37 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 12 , wherein said first constrained state comprises one of said at least one constrained state of the target vehicle.
Claim 19
Dependent Claim
42 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 12 , wherein the operation of testing at least one hypothesis is responsive to the most recent estimates of said state of the target vehicle.
Claim 20
Dependent Claim
99 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 12 , wherein the operation of testing at least one hypothesis comprises identifying a particular constrained state of the target vehicle corresponding to a most likely of said at least one constrained state of the target vehicle, calculating a value of a function responsive to a difference between said strained state and said particular constrained state, and comparing said value of said function with a threshold, whereby said hypothesis is satisfied if said value of said function is less than said threshold.
Claim 21
Dependent Claim
38 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 19 , wherein said threshold is responsive to the particular constraint associated with said particular constrained state of the target vehicle.
Claim 22
Dependent Claim
42 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 20 , wherein said threshold is relatively lower for said particular constrained state corresponding to an increased threat by the target vehicle to host vehicle.
Claim 23
Dependent Claim
66 words
A method of estimating a state of a target vehicle on a roadway as recited in claim 21 , wherein said particular constrained state corresponding to an increased threat by the target vehicle to the host vehicle is selected from the target vehicle moving in the same lane as the host vehicle, and the target vehicle changing lanes to said same lane as the host vehicle.
References Cited (Backward Citations)
US2709804A
Cited
US3177485A
Cited
US3603994A
Cited
US3699573A
Cited
US3725918A
Cited
US3869601A
Cited
US3971018A
Cited
US4623966A
Cited
US5343206A
Cited
US5170440A
Cited
US5051751A
Cited
US5307289A
Cited
US5138321A
Cited
US5471214A
Cited
US5202691A
Cited
US5530651A
Cited
US5598164A
Cited
US5314037A
Cited
US5406289A
Cited
US5402129A
Cited
US6275773B1
Cited
US20020022927A1
Cited
US5983161A
Cited
US6226389B1
Cited
US5633642A
Cited
US5959574A
Cited
US5537119A
Cited
US5684473A
Cited
US5631639A
Cited
US5594414A
Cited
US5627768A
Cited
US5668739A
Cited
US5587929A
Cited
US5689264A
Cited
US5710565A
Cited
US5657251A
Cited
US5955967A
Cited
US5703593A
Cited
US5751211A
Cited
US6300865B1
Cited
US5959552A
Cited
US5948043A
Cited
US6134509A
Cited
US6070121A
Cited
US6282478B1
Cited
US6275231B1
Cited
US5926126A
Cited
US6370475B1
Cited
US6405132B1
Cited
US6292752B1
Cited
US6085151A
Cited
US6393376B1
Cited
US6198426B1
Cited
US6161071A
Cited
US6343253B1
Cited
US6265991B1
Cited
US20020044080A1
Cited
US6420997B1
Cited
US6470272B2
Cited
US20020049539A1
Cited
US6675094B2
Cited
US6643588B1
Cited
US20030218563A1
Cited
USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2009-04-24 | 2009-10-24 | 2010-04-25 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2013-04-24 | 2013-10-24 | 2014-04-25 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2017-04-24 | 2017-10-24 | 2018-04-25 | $7700.00 | Window Closed / Lapsed |