Ning L Qu

US Patent:

20210331700, Oct 28, 2021

Filed:

Apr 22, 2020

Appl. No.:

16/855283

Inventors:

- Sunnyvale CA, US
Ning QU - Fremont CA, US

International Classification:

B60W 60/00
G06K 9/00

Abstract:

Systems and methods of determining a risk distribution associated with a multiplicity of coverage zones covered by a multiplicity of sensors of an autonomous driving vehicle (ADV) are disclosed. The method includes for each coverage zone covered by at least one sensor of the ADV, obtaining MTBF data of the sensor(s) covering the coverage zone. The method further includes determining a mean time between failure (MTBF) of the coverage zone based on the MTBF data of the sensor(s). The method further includes computing a performance risk associated with the coverage zone based on the determined MTBF of the coverage zone. The method further includes determining a risk distribution based on the computed performance risks associated with the multiplicity of coverage zones.

US Patent:

20210323561, Oct 21, 2021

Filed:

Apr 15, 2020

Appl. No.:

16/849821

Inventors:

- Sunnyvale CA, US
Ning QU - Fremont CA, US

International Classification:

B60W 50/00

Abstract:

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.

US Patent:

20210316755, Oct 14, 2021

Filed:

Apr 9, 2020

Appl. No.:

16/844562

Inventors:

- Sunnyvale CA, US
Ning QU - Fremont CA, US

International Classification:

B60W 60/00
B60W 50/04
B60W 30/09

Abstract:

In one embodiment, method for real-time monitoring of a safety redundancy autonomous driving system operating within a predefined risk tolerable boundary includes calculating a zone failure risk score for each of predetermined zones based on a sensor failure risk score associated with each of sensors mounted on the ADV. The predetermined zones being defined based on a sensor layout of the sensors. A sensor capability coverage of the ADV is determined based on the zone failure risk score associated with each of the predetermined zones. A drivable area of the ADV is determined based on the sensor capability coverage in view of map data associated with a current location of the ADV. A trajectory is planned based on the drivable area to autonomously drive the ADV to navigate a driving environment surrounding the ADV.

US Patent:

20210284108, Sep 16, 2021

Filed:

Mar 11, 2020

Appl. No.:

16/815734

Inventors:

- Sunnyvale CA, US
NING QU - FREMONT CA, US

International Classification:

B60T 7/22
G06K 9/00
B60W 30/18
B60W 60/00
B60W 10/18

Abstract:

In one embodiment, a method for performing an obstacle detection for an ADV includes detecting an obstacle by a primary ADS and a secondary ADS using an obstacle detection algorithm based on sensor data provided by sensors on the ADV. In response to detecting the obstacle, a first controlled stop distance and a second controlled stop distance are calculated by the primary ADS and secondary ADS respectively based on a speed and a deceleration capability of the ADV. The first and second controlled stop distances between the primary ADS and secondary ADS are exchanged to determine a third controlled stop distance which is the maximum of the two. In response to determining that the ADV reaches within the third controlled distance between the ADV and the obstacle, a controlled stop operation is activated by the primary ADS to decelerate the ADV based on the third controlled stop distance.

US Patent:

20210284200, Sep 16, 2021

Filed:

Mar 11, 2020

Appl. No.:

16/815266

Inventors:

- Sunnyvale CA, US
Ning Qu - Fremont CA, US

International Classification:

B60W 60/00
G05D 1/00

Abstract:

In one embodiment, method for determining capability boundary of a safety redundancy of an autonomous driving vehicle (ADV) includes obtaining a sensor layout associated with the ADV representing a system having a plurality of sensors mounted on a plurality of locations of the ADV. A zone failure risk of one or more sensors within the predetermined zones is estimated based on statistical operational data of the one or more sensors for each of the plurality of predetermined zones. An overall failure risk of the sensors is determined based on the zone failure risks of the predetermined zones based on relative locations of the sensors across the predetermined zones. A dynamic risk adjustment is determined based on the overall failure risk of the sensors, the dynamic risk adjustment representing a reliability of a sensor system associated with the ADV for estimating a safety of autonomous driving of the ADV.

US Patent:

20210107498, Apr 15, 2021

Filed:

Oct 9, 2019

Appl. No.:

16/597710

Inventors:

- Sunnyvale CA, US
Ning QU - Fremont CA, US

International Classification:

B60W 50/08
G08G 1/01

Abstract:

In one embodiment, a method of transitioning from autonomous driving (AD) to manual driving (MD) mode for an autonomous driving vehicle (ADV) is disclosed. The method includes determining whether AD-to-MD transition is allowed in a current location of the ADV. The method further includes determining whether a current driving scenario is safe for the AD-to-MD transition. The method further includes in response to determining that the AD-to-MD transition is allowed in the current location and the current driving scenario is safe for the AD-to-MD transition, enabling the AD-to-MD transition. The method further includes determining whether there is a request for the AD-to-MD transition. The method further includes in response to determining there is the request, computing a current vehicle motion trajectory of the ADV. The method further includes comparing the current vehicle motion trajectory with a motion trajectory derived from inputs of a driver of the ADV. The method further includes determining whether to confirm the AD-to-MD transition based on the comparison.

US Patent:

20210112094, Apr 15, 2021

Filed:

Oct 15, 2019

Appl. No.:

16/653711

Inventors:

- Sunnyvale CA, US
NING QU - Fremont CA, US

International Classification:

H04L 29/06
G01C 21/34
B60W 50/02
B60W 50/04
G06K 9/00

Abstract:

Systems and methods are disclosed for an ADV to leverage pre-defined static objects along a planned route of travel to detect and counter attacks that attempt to change the destination or the planned route. The ADV may detect updates to the static objects if the planned route is changed. Based on the updated static objects, the ADV determines if there is an abnormal re-routing of the planned route or if there is a new route due to a suspicious destination change. The ADV may also leverage the static objects to detect spoofing attacks against the sensor system. The ADV may evaluate if sensors of the sensor system are able to detect and identify the static objects to identify an impaired sensor. The ADV may perform cross-check on the ability of the sensors to detect and identify dynamic objects to gain confidence that the impaired sensor is due to spoofing attacks.

US Patent:

20200391729, Dec 17, 2020

Filed:

Jun 13, 2019

Appl. No.:

16/440983

Inventors:

- Sunnyvale CA, US
Ning QU - Sunnyvale CA, US

International Classification:

B60W 30/09
B60W 30/095
B60W 50/029
G05D 1/02
G05D 1/00

Abstract:

According to one embodiment, a motion trajectory boundary is obtained based on a trajectory that has been planned to drive an ADV for a next time period. A safe driving area boundary is determined for the ADV based on perception data perceiving a driving environment surrounding the ADV. The motion trajectory boundary and the safe drivable area boundary are projected onto a map such as an HD map. A relative location of the ADV within the map relative to the motion trajectory and the safe drivable area boundary is determined. A fail-safe action or a fail operational action may be performed based on the relative location of the ADV in view of the motion trajectory boundary and the safe drivable area boundary.