# US 11,442,450 B2 · Method for determining passable area in planning a path of autonomous driving vehicles

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 11,442,450 B2
- Document ID: US11442450B2
- Status: Granted
- Kind: B2
- Application number: 16/711,118
- Filed: 2019-12-11
- Published: 2021-06-17
- Granted: 2022-09-13
- Earliest claimed: 2019-12-11
- Assignees: Baidu USA LLC; Baidu.Com Times Technology (Beijing) Co., Ltd.
- Applicants: Baidu USA LLC; Baidu.com Times Technology (Beijing) Co., Ltd.
- Inventors: Dongchun Yao; Fan Zhu; Leibing Lv; Xin Xu; Ning Yu
- Web page: https://patentgrep.com/patent/US11442450B2

## CPC

- G01C 21/3407: {specially adapted for specific applications}
- G05D 1/0088: {characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours (using knowledge based models G06N5/00)}
- B60W 30/09: Taking automatic action to avoid collision, e.g. braking and steering
- B60W 30/12: Lane keeping
- G01C 21/3492: {employing speed data or traffic data, e.g. real-time or historical (traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968)}
- G05D 1/0214: {in accordance with safety or protection criteria, e.g. avoiding hazardous areas (monitoring the location of vehicles within a certain area, e.g. forbidden or allowed areas, in traffic control systems for road vehicles G08G1/13)}
- G06V 20/58: Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
- G06V 20/588: {Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road}
- G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S)
- G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING

## Abstract

According to one embodiment, in response to determining that an obstacle blocks at least a portion of a current lane in which an ADV is driving, an obstacle boundary of the obstacle is determined based on the size and shape of the obstacle. A lane configuration is determined based on map data of a map corresponding to a road associated with the lanes. A passing lane boundary that can be utilized by the ADV is determined based on the lane configuration of the road and the obstacle boundary of the obstacle. A passable area is calculated within the passing lane boundary based on a size of the ADV. The passable area is utilized by the ADV to pass the obstacle without collision. Thereafter, a trajectory is planned within the passable area boundary to control the ADV to pass the obstacle.

## Claims

### Claim 1

A computer-implemented method of operating an autonomous driving vehicle (ADV), the computer-implemented method comprising:
in response to determining that an obstacle is blocking at least a portion of a current lane in which an ADV is driving, determining an obstacle boundary of the obstacle;
determining a lane configuration of a road within which the current lane is located based on map data of a map corresponding to the road, wherein the lane configuration comprises a number of lanes within the road and a lane type of each of the number of lanes;
determining a passing lane boundary of a passing lane that can be utilized by the ADV based on the lane configuration of the road and the obstacle boundary of the obstacle;
calculating a passable area boundary within the passing lane boundary based on a size of the ADV, wherein the passable area boundary is utilized by the ADV to pass the obstacle without collision; and
planning a trajectory within the passable area boundary to control the ADV to pass the obstacle.

### Claim 2 (depends on 1)

The computer-implemented method of claim 1, further comprising:
determining whether the obstacle is a static obstacle; and
in response to determining that the obstacle is a static obstacle, determining the obstacle boundary based on a size and a shape of the obstacle.

### Claim 3 (depends on 1)

The computer-implemented method of claim 1, further comprising:
determining whether the obstacle is a dynamic obstacle;
in response to determining that the obstacle is a dynamic obstacle, predicting a moving trajectory of the obstacle; and
determining the obstacle boundary based on the moving trajectory of the obstacle.

### Claim 4 (depends on 1)

The computer-implemented method of claim 1, wherein determining the passing lane boundary comprises adjusting a current lane boundary of the current lane by subtracting at least a portion of the obstacle boundary that is within the current lane boundary.

### Claim 5 (depends on 4)

The computer-implemented method of claim 4, wherein determining the passable area boundary within the passing lane boundary comprises reducing a passing lane width of the passing lane based on a vehicle width of the ADV.

### Claim 6 (depends on 5)

The computer-implemented method of claim 5, wherein the passing lane width is reduced by a half of the vehicle width of the ADV.

### Claim 7 (depends on 5)

The computer-implemented method of claim 5, wherein determining the lane boundary that can be utilized by the ADV comprises:
determining whether the lane type of the current lane allows the ADV to enter an adjacent lane in order to pass the obstacle based on a set of traffic rules; and
expanding the passing lane boundary from the current lane boundary of the current lane to the adjacent lane, in response to determining that the adjacent lane can be utilized by the ADV.

### Claim 8 (depends on 7)

The computer-implemented method of claim 7, wherein determining the lane type of the current lane comprises whether a lane line of the current lane includes a dash line, wherein the ADV is allowed to enter the adjacent lane if the lane line includes a dash line.

### Claim 9 (depends on 1)

The computer-implemented method of claim 1, further comprising:
determining a lane curve of the passing lane; and
adjusting the passing lane boundary based on the lane curve of the passing lane and a-a vehicle boundary of the ADV, such that the vehicle boundary of the ADV does not reach a road curb of the road when the ADV drives through the lane curve of the passing lane.

### Claim 10

A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations of operating an autonomous driving vehicle (ADV), the operations comprising:
in response to determining that an obstacle is blocking at least a portion of a current lane in which an ADV is driving, determining an obstacle boundary of the obstacle;
determining a lane configuration of a road within which the current lane is located based on map data of a map corresponding to the road, wherein the lane configuration comprises a number of lanes within the road and a lane type of each of the number of lanes;
determining a passing lane boundary of a passing lane that can be utilized by the ADV based on the lane configuration of the road and the obstacle boundary of the obstacle;
calculating a passable area boundary within the passing lane boundary based on a size of the ADV, wherein the passable area boundary is utilized by the ADV to pass the obstacle without collision; and
planning a trajectory within the passable area boundary to control the ADV to pass the obstacle.

### Claim 11 (depends on 10)

The non-transitory machine-readable medium of claim 10, wherein the operations further comprise:
determining whether the obstacle is a static obstacle; and
in response to determining that the obstacle is a static obstacle, determining the obstacle boundary based on a size and a shape of the obstacle.

### Claim 12 (depends on 10)

The non-transitory machine-readable medium of claim 10, wherein the operations further comprise:
determining whether the obstacle is a dynamic obstacle;
in response to determining that the obstacle is a dynamic obstacle, predicting a moving trajectory of the obstacle; and
determining the obstacle boundary based on the moving trajectory of the obstacle.

### Claim 13 (depends on 10)

The non-transitory machine-readable medium of claim 10, wherein determining the passing lane boundary comprises adjusting a current lane boundary of the current lane by subtracting at least a portion of the obstacle boundary that is within the current lane boundary.

### Claim 14 (depends on 13)

The non-transitory machine-readable medium of claim 13, wherein determining the passable area boundary within the passing lane comprises reducing a passing lane width of the passing lane based on a vehicle width of the ADV.

### Claim 15 (depends on 14)

The non-transitory machine-readable medium of claim 14, wherein the passing lane width is reduced by a half of the vehicle width of the ADV.

### Claim 16 (depends on 14)

The non-transitory machine-readable medium of claim 14, wherein determining the lane boundary that can be utilized by the ADV comprises:
determining whether the lane type of the current lane allows the ADV to enter an adjacent lane in order to pass the obstacle based on a set of traffic rules; and
expanding the passing lane boundary from the current lane boundary of the current lane to the adjacent lane, in response to determining that the adjacent lane can be utilized by the ADV.

### Claim 17 (depends on 16)

The non-transitory machine-readable medium of claim 16, wherein determining the lane type of the current lane comprises whether a lane line of the current lane includes a dash line, wherein the ADV is allowed to enter the adjacent lane if the lane line includes a dash line.

### Claim 18

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:
in response to determining that an obstacle is blocking at least a portion of a current lane in which an autonomous driving vehicle (ADV) is driving, determining an obstacle boundary of the obstacle,
determining a lane configuration of a road within which the current lane is located based on map data of a map corresponding to the road, wherein the lane configuration comprises a number of lanes within the road and a lane type of each of the number of lanes,
determining a passing lane boundary of a passing lane that can be utilized by the ADV based on the lane configuration of the road and the obstacle boundary of the obstacle,
calculating a passable area boundary within the passing lane boundary based on a size of the ADV, wherein the passable area boundary is utilized by the ADV to pass the obstacle without collision, and
planning a trajectory within the passable area boundary to control the ADV to pass the obstacle.

### Claim 19 (depends on 18)

The data processing system of claim 18, wherein the operations further comprise:
determining whether the obstacle is a static obstacle; and
in response to determining that the obstacle is a static obstacle, determining the obstacle boundary based on a size and a shape of the obstacle.

### Claim 20 (depends on 18)

The data processing system of claim 18, wherein the operations further comprise:
determining whether the obstacle is a dynamic obstacle;
in response to determining that the obstacle is a dynamic obstacle, predicting a moving trajectory of the obstacle; and
determining the obstacle boundary based on the moving trajectory of the obstacle.