# US 11,077,878 B2 · Dynamic lane biasing

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- Number: US 11,077,878 B2
- Document ID: US11077878B2
- Status: Granted
- Kind: B2
- Application number: 16/566,821
- Filed: 2019-09-10
- Published: 2020-12-24
- Granted: 2021-08-03
- Earliest claimed: 2018-11-02
- Assignees: Zoox, Inc.
- Applicants: Zoox, Inc.
- Inventors: Janek Hudecek; Victoria Magdalena Dax
- Web page: https://patentgrep.com/patent/US11077878B2

## CPC

- B62D 15/0255: {Automatic changing of lane, e.g. for passing another vehicle}
- B60W 30/09: Taking automatic action to avoid collision, e.g. braking and steering
- B60W 30/095: Predicting travel path or likelihood of collision
- B60W 30/0956: {the prediction being responsive to traffic or environmental parameters}
- B60W 30/18163: {Lane change; Overtaking manoeuvres}
- B60W 60/0015: {specially adapted for safety}
- B60W 60/0027: {using trajectory prediction for other traffic participants}
- B62D 15/0265: {Automatic obstacle avoidance by steering}
- G05D 1/0088: {characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours (using knowledge based models G06N5/00)}
- G05D 1/0212: {with means for defining a desired trajectory (involving a plurality of land vehicles G05D1/0287)}
- 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)}
- G05D 1/0217: {in accordance with energy consumption, time reduction or distance reduction criteria}
- B60W 2554/402: Type
- B60W 2554/801: Lateral distance
- B62D: MOTOR VEHICLES; TRAILERS (steering, or guiding on a desired track, of agricultural machines or implements A01B69/00; wheels, castors, axles, increasing wheel adhesion B60B; vehicle tyres, tyre inflation or tyre changing B60C; connections between vehicles of a train or the like B60D; vehicles for use on rail and road, amphibious or convertible vehicles B60F; suspension arrangements B60G; heating, cooling, ventilating or other air treating devices B60H; windows, windscreens, non-fixed roofs, doors or similar devices, protective coverings for vehicles not in use B60J; propulsion plant arrangements, auxiliary drives, transmissions, controls, instrumentation or dashboards B60K; electric equipment or propulsion of electrically-propelled vehicles B60L; power supply for electrically-propelled vehicles B60M; passenger accommodation not otherwise provided for B60N; adaptations for load transportation or to carry special loads or objects B60P; arrangement of signalling or lighting devices, the mounting or supporting thereof or circuits therefor, for vehicles in general B60Q; vehicles, vehicle fittings or vehicle parts not otherwise provided for B60R; servicing, cleaning, repairing, supporting, lifting, or manoeuvring, not otherwise provided for, B60S; brake arrangements, brake control systems or parts thereof B60T; air-cushion vehicles B60V; motor-cycles, accessories therefor B62J, B62K; testing of vehicles G01M)
- 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
- G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES

## Abstract

Techniques for generating trajectories and drivable areas for navigating a vehicle in an environment are discussed herein. The techniques can include receiving a reference trajectory representing an initial trajectory for a vehicle, such as an autonomous vehicle, to traverse the environment in a first drivable area. An object within a distance threshold can be detected in the environment and a second drivable area can be determined. Further, the techniques can include determining a target trajectory based at least in part on the reference trajectory and/or the second drivable area which can provide a region for the object to traverse the environment, and controlling the autonomous vehicle to traverse the environment based at least in part on the target trajectory.

## Claims

### Claim 1

A system comprising:
one or more processors; and
one or more computer-readable media storing computer-executable instructions that, when executed, cause the system to perform operations comprising:
receiving sensor data from a sensor associated with an autonomous vehicle traversing an environment;
determining a first drivable area for the autonomous vehicle to traverse in the environment, the first drivable area associated with a first width;
determining an object represented in the sensor data;
determining an object type associated with the object;
determining, based at least in part on the object type, a distance threshold of a plurality of distance thresholds, wherein the distance threshold is based at least in part on an object type;
determining a distance between the autonomous vehicle and the object;
determining that the distance is below the distance threshold;
determining, based at least in part on the distance being below the distance threshold, a second drivable area associated with a second width that is less than the first width;
determining a cost associated with the second drivable area;
determining, based at least in part on the cost, a target trajectory; and
controlling, based at least in part on the target trajectory, the autonomous vehicle to traverse the environment.

### Claim 2 (depends on 1)

The system of claim 1, the operations further comprising:
determining a probability that the object will be adjacent to the autonomous vehicle within a period of time; and
determining that the probability meets or exceeds a probability threshold;
wherein determining the second drivable area is further based at least in part on the probability meeting or exceeding the probability threshold.

### Claim 3 (depends on 1)

The system of claim 1, wherein determining the second drivable area is associated with a first time and comprises:
determining, based at least in part on a first velocity associated with the object and a second velocity associated with the autonomous vehicle, a location of the autonomous vehicle at a second time after the first time;
wherein determining, the second drivable area is further based at least in part on the location.

### Claim 4 (depends on 1)

The system of claim 1, the operations further comprising:
determining, based at least in part on a longitudinal displacement, a transition area between the first drivable area and the second drivable area;
wherein determining the target trajectory is further based at least in part on the transition area.

### Claim 5 (depends on 1)

The system of claim 1, wherein the object type comprises one or more of a bicyclist, a pedestrian, a vehicle, a static object, or a dynamic object.

### Claim 6

A method comprising:
receiving sensor data from a sensor associated with a vehicle traversing an environment;
determining a first area for the vehicle to traverse in the environment, the first area associated with a first width;
determining an object represented in the sensor data;
determining a distance between the vehicle and the object;
determining a classification associated with the object;
determining, based at least in part on the classification, a width of a lane bias region of a plurality of widths, wherein the width is based at least in part on a classification;
determining, based at least in part on the classification, a second area associated with a second width that is less than the first width by the width of the lane bias region;
determining, based at least in part on the second area, a cost associated with the vehicle traversing the second area;
determining, based at least in part on the cost, a trajectory; and
controlling the vehicle based at least in part on the trajectory.

### Claim 7 (depends on 6)

The method of claim 6, further comprising:
determining a distance between the object and the vehicle; and
determining, based at least in part on the classification, a distance threshold,
wherein determining the second area is further based at least in part on the distance being less than or equal to the distance threshold.

### Claim 8 (depends on 7)

The method of claim 7, wherein the distance threshold is an upper distance threshold, the method further comprising:
determining, based at least in part on the object, a lower distance threshold; and
determining that the distance meets or exceeds the lower distance threshold;
wherein determining the second area is further based at least in part on determining that the distance meets or exceeds the lower distance threshold.

### Claim 9 (depends on 6)

The method of claim 6, the method further comprising:
determining a probability that the object will be within a distance threshold to the vehicle within a period of time; and
determining that the probability meets or exceeds a probability threshold;
wherein determining the second area is further based at least in part on the probability meeting or exceeding the probability threshold.

### Claim 10 (depends on 6)

The method of claim 6, wherein determining the second area is associated with a first time, the method further comprising:
determining, based at least in part on a first velocity associated with the object and a second velocity associated with the vehicle, a location of the vehicle at a second time after the first time;
wherein determining the second area is further based at least in part on the location.

### Claim 11 (depends on 6)

The method of claim 6, wherein the vehicle is a first vehicle, and the classification comprises at least one of:
a second vehicle;
a pedestrian;
a bicyclist;
an animal;
a static object; or
a dynamic object.

### Claim 12 (depends on 6)

The method of claim 6, wherein determining the classification is based at least in part on the sensor data.

### Claim 13 (depends on 6)

The method of claim 6, further comprising:
determining, based at least in part on a longitudinal displacement associated with the vehicle, a transition area between the first area and the second area;
wherein determining the trajectory is further based at least in part on the transition area.

### Claim 14

A non-transitory computer-readable medium storing instructions executable by one or more processors, wherein the instructions, when executed, cause the one or more processors to perform operations comprising:
receiving sensor data from a sensor associated with a vehicle traversing an environment;
determining a first area on which the vehicle is able to traverse, the first area associated with a first width;
determining an object represented in the sensor data;
determining a classification associated with the object;
determining, based at least in part on the classification, a second area associated with a second width;
determining, based at least in part on the second area, a cost associated with operating the vehicle in the environment;
determining, based at least in part on the cost, a trajectory associated with the vehicle; and
controlling the vehicle based at least in part on the trajectory.

### Claim 15 (depends on 14)

The non-transitory computer-readable medium of claim 14, the operations further comprising:
determining a distance between the vehicle and the object; and
determining, based at least in part on the classification, a distance threshold,
wherein determining the second area is further based at least in part on the distance being less than or equal to the distance threshold.

### Claim 16 (depends on 14)

The non-transitory computer-readable medium of claim 14, the operations further comprising:
determining a distance between the vehicle and the object;
determining an upper distance threshold;
determining, based at least in part on the object, a lower distance threshold;
determining that the distance meets or exceeds the lower distance threshold; and
determining the second area further based at least in part on the distance between the vehicle and the object meeting or exceeding the lower distance threshold.

### Claim 17 (depends on 14)

The non-transitory computer-readable medium of claim 14, the operations further comprising:
determining a probability that the object will be within a distance threshold to the vehicle within a period of time;
determining that the probability meets or exceeds a probability threshold; and
determining the second area further based at least in part on the probability meeting or exceeding the probability threshold.

### Claim 18 (depends on 14)

The non-transitory computer-readable medium of claim 14, wherein determining the second area is associated with a first time, the operations further comprising:
determining, based at least in part on a first velocity associated with the object and a second velocity associated with the vehicle, a location of the vehicle at a second time after the first time;
wherein determining the second area is further based at least in part on the location.

### Claim 19 (depends on 14)

The non-transitory computer-readable medium of claim 14, wherein the vehicle is a first vehicle, and the classification indicates that the object is associated with at least one of:
a second vehicle;
a pedestrian;
a bicyclist;
an animal;
a static object; or
a dynamic object.

### Claim 20 (depends on 14)

The non-transitory computer-readable medium of claim 14, the operations further comprising:
determining, based at least in part on a longitudinal displacement, a transition area between the first area and the second area;
wherein determining the trajectory is further based at least in part on the transition area.