Systems and methods to enhance early detection of performance induced risks for an autonomous driving vehicle

US11554783B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-11554783-B2
Application numberUS-202016849821-A
CountryUS
Kind codeB2
Filing dateApr 15, 2020
Priority dateApr 15, 2020
Publication dateJan 17, 2023
Grant dateJan 17, 2023

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  1. Title

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  2. Abstract

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  5. First independent claim

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Abstract

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Systems and methods of adjusting zone associated risks of a coverage zone covered by one or more sensors of an autonomous driving vehicle (ADV) operating in real-time are disclosed. As an example, the method includes defining a performance limit detection window associated with a first sensor based on a mean time between failure (MTBF) lower limit of the first sensor and a MTBF upper limit of the first sensor. The method further includes determining whether an operating time of the ADV operating in autonomous driving (AD) mode is within the performance limit detection window associated with the first sensor. The method further includes in response to determining that the operating time of the ADV operating in AD mode is within the performance limit detection window of the first sensor, adjusting a zone associated risk of the coverage zone to a performance risk of a second sensor.

First claim

Opening claim text (preview).

What is claimed is: 1. A computer-implemented method of adjusting zone associated risks of a coverage zone covered by a plurality of sensors of an autonomous driving vehicle (ADV) operating in real-time, comprising: defining a performance limit detection window associated with a first sensor based on a mean time between failure (MTBF) lower limit of the first sensor and a MTBF upper limit of the first sensor; determining whether an operating time of the ADV operating in autonomous driving (AD) mode is within the performance limit detection window associated with the first sensor; and in response to determining that the operating time of the ADV operating in AD mode is within the performance limit detection window of the first sensor, adjusting a zone associated risk of the coverage zone to a performance risk of a second sensor. 2. The method of claim 1 , further comprising: determining the MTBF lower limit of the first sensor based on a MTBF distribution associated with the first sensor; and determining the MTBF upper limit of the first sensor based on the MTBF distribution associated with the first sensor. 3. The method of claim 2 , wherein the MTBF lower limit of the first sensor is a worst case MTBF of the first sensor, and the MTBF upper limit of the first sensor is a nominal performance MTBF of the first sensor. 4. The method of claim 1 , further comprising: in response to determining that the operating time of the ADV operating in AD mode is within the performance limit detection window of the first sensor, determining whether performance limitation of the first sensor is confirmed; in response to determining that the performance limitation of the first sensor is confirmed, determining that the coverage zone is only covered by the second sensor and determining whether the performance limitation of the first sensor is temporary; and in response to determining that the performance limitation of the first sensor is temporary, adjusting the zone associated risk of the coverage zone to the performance risk of the second sensor. 5. The method of claim 4 , further comprising: in response to determining that the performance limitation of the first sensor is not temporary, determining whether the zone is covered by the second sensor; and in response to determining that the zone is not covered by the second sensor, declaring the zone as a no coverage zone. 6. The method of claim 1 , further comprising: defining a performance limit detection window associated with the second sensor based on a MTBF lower limit of the second sensor and a MTBF upper limit of the second sensor. 7. The method of claim 4 , further comprising: adjusting the zone associated risk of the coverage zone to a combined performance risk of the first and second sensors subsequent to adjusting the zone associated risk of the coverage zone to the performance risk of the second sensor. 8. The method of claim 6 , further comprising: determining whether the operating time of the ADV operating in AD mode is within the performance limit detection window associated with the second sensor; in response to determining that the operating time of the ADV operating in AD mode is within the performance limit detection window of the second sensor, ensuring the second sensor is operating as intended based on additional diagnostics and determining that the coverage zone is only covered by the first sensor. 9. A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations, the operations comprising: defining a performance limit detection window associated with a first sensor based on a mean time between failure (MTBF) lower limit of the first sensor and a MTBF upper limit of the first sensor; determining whether an operating time of an autonomous driving vehicle (ADV) operating in autonomous driving (AD) mode is within the performance limit detection window associated with the first sensor; and in response to determining that the operating time of the ADV operating in AD mode is within the performance limit detection window of the first sensor, adjusting a zone associated risk of a coverage zone to a performance risk of a second sensor. 10. The non-transitory machine-readable medium of claim 9 , wherein the operations further comprise: determining the MTBF lower limit of the first sensor based on a MTBF distribution associated with the first sensor; and determining the MTBF upper limit of the first sensor based on the MTBF distribution associated with the first sensor. 11. The non-transitory machine-readable medium of claim 10 , wherein the MTBF lower limit of the first sensor is a worst case MTBF of the first sensor, and the MTBF upper limit of the first sensor is a nominal performance MTBF of the first sensor. 12. The non-transitory machine-readable medium of claim 9 , wherein the operations further comprise: in response to determining that the operating time of the ADV operating in AD mode is within the performance limit detection window of the first sensor, determining whether performance limitation of the first sensor is confirmed; in response to determining that the performance limitation of the first sensor is confirmed, determining that the coverage zone is only covered by the second sensor and determining whether the performance limitation of the first sensor is temporary; and in response to determining that the performance limitation of the first sensor is temporary, adjusting the zone associated risk of the coverage zone to the performance risk of the second sensor. 13. The non-transitory machine-readable medium of claim 12 , wherein the operations further comprise: in response to determining that the performance limitation of the first sensor is not temporary, determining whether the zone is covered by the second sensor; and in response to determining that the zone is not covered by the second sensor, declaring the zone as a no coverage zone. 14. The non-transitory machine-readable medium of claim 9 , wherein the operations further comprise: defining a performance limit detection window associated with the second sensor based on a MTBF lower limit of the second sensor and a MTBF upper limit of the second sensor. 15. The non-transitory machine-readable medium of claim 12 , wherein the operations further comprise: adjusting the zone associated risk of the coverage zone to a combined performance risk of the first and second sensors subsequent to adjusting the zone associated risk of the coverage zone to the performance risk of the second sensor. 16. The non-transitory machine-readable medium of claim 14 , wherein the operations further comprise: determining whether the operating time of the ADV operating in AD mode is within the performance limit detection window associated with the second sensor; in response to determining that the operating time of the ADV operating in AD mode is within the performance limit detection window of the second sensor, ensuring the second sensor is operating as intended based on additional diagnostics and determining that the coverage zone is only covered by the first sensor. 17. A data processing system, comprising: a processor; and a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations, the operations including: defining a performance limit detection window associated with a first sensor based on a mean time between failure (MTBF) lower limit of the first sensor and a MTBF upper limit of th

Assignees

Inventors

Classifications

  • Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads · CPC title

  • G01S13/931Primary

    of land vehicles · CPC title

  • Details of control systems ensuring comfort, safety or stability not otherwise provided for · CPC title

  • of land vehicles · CPC title

  • Combination of radar systems with cameras · CPC title

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What does patent US11554783B2 cover?
Systems and methods of adjusting zone associated risks of a coverage zone covered by one or more sensors of an autonomous driving vehicle (ADV) operating in real-time are disclosed. As an example, the method includes defining a performance limit detection window associated with a first sensor based on a mean time between failure (MTBF) lower limit of the first sensor and a MTBF upper limit of t…
Who is the assignee on this patent?
Baidu Usa Llc
What technology area does this patent fall under?
Primary CPC classification G01S13/931. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Jan 17 2023 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 10 related publications on this page (citations in our corpus or others sharing the same primary CPC).