# US 2021/0278843 A1 · Generating simplified object models to reduce computational resource requirements for autonomous vehicles

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

- Number: US 2021/0278843 A1
- Document ID: US20210278843A1
- Status: Published application
- Kind: A1
- Application number: 17/330,601
- Filed: 2021-05-26
- Published: 2021-09-09
- Earliest claimed: 2019-04-10
- Assignees: Waymo LLC
- Applicants: Waymo LLC
- Inventors: Dong Li; Fang Da
- Web page: https://patentgrep.com/patent/US20210278843A1

## CPC

- B60W 30/0956: {the prediction being responsive to traffic or environmental parameters}
- G05D 1/0088: {characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours (using knowledge based models G06N5/00)}
- B60W 60/001: {Planning or execution of driving tasks}
- G01S 17/931: of land vehicles
- G05D 1/0231: {using optical position detecting means (position-fixing by using electromagnetic waves other than radio waves, e.g. optical position detecting means G01S5/16)}
- G06T 17/00: Three-dimensional [3D] modelling for computer graphics
- B60W 2050/065: {by reducing the computational load on the digital processor of the control computer}
- B60W 2420/408: Radar; Laser, e.g. lidar
- G06T 2210/12: Bounding box
- G06T 2210/56: Particle system, point based geometry or rendering
- 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
- G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL

## Abstract

Aspects of the disclosure relate to controlling a vehicle using a simplified model of an object. In one example, sensor data including a plurality of data points corresponding to surfaces of the object in the vehicle's environment may be received from one or more sensors of the vehicle. A first model may be determined using a subset of the plurality of data points. A set of secondary data points may be identified from the plurality of data points using a point on the vehicle. The set of secondary data points may be filtered from the subset of the plurality data points to determine a second model, wherein the second model is a simplified version of the first model. The vehicle may be controlled in an autonomous driving mode based on the second model.

## Claims

### Claim 1

A method of controlling a vehicle using a simplified model of an object, the method comprising:
receiving, by one or more computing devices from one or more sensors of the vehicle, sensor data including a plurality of three-dimensional data points corresponding to surfaces of the object in the vehicle's environment;
determining, by the one or more computing devices, a first model representative of the object using only two-dimensional data points of the plurality of three-dimensional data points;
generating, by the one or more computing devices, a second model representative of the object by removing data points of the first model corresponding to surfaces that were occluded from the one or more sensors of the vehicle when the sensor data was captured; and
controlling, by the one or more computing devices, the vehicle in an autonomous driving mode based on the second model.

### Claim 2 (depends on 1)

The method of claim 1, wherein the plurality of three-dimensional data points are received from a LIDAR sensor of the vehicle.

### Claim 3 (depends on 1)

The method of claim 1, wherein the first model is determined by ignoring a height dimension of the plurality of three-dimensional data points.

### Claim 4 (depends on 1)

The method of claim 1, wherein the first model is determined by projecting the plurality of three-dimensional data points onto a two-dimensional plane.

### Claim 5 (depends on 1)

The method of claim 1, wherein each of the first model and the second model are two-dimensional representations of the object.

### Claim 6 (depends on 1)

The method of claim 1, wherein determining the first model includes determining a convex hull from the two-dimensional data points.

### Claim 7 (depends on 6)

The method of claim 6, wherein removing data points of the first model includes identifying data points of the convex hull corresponding to a side of the convex hull that are oriented away from the vehicle relative to other data points of the convex hull.

### Claim 8 (depends on 7)

The method of claim 7, wherein removing data points of the first model includes determining a modified convex hull based on the two-dimensional data points and a point on the vehicle.

### Claim 9 (depends on 8)

The method of claim 8, wherein the point on the vehicle is a two-dimensional point.

### Claim 10 (depends on 8)

The method of claim 8, wherein the point on the vehicle is a point on the LIDAR sensor.

### Claim 11 (depends on 8)

The method of claim 8, wherein removing data points of the first model further includes identifying a pair of data points from the modified convex hull using the point on the vehicle.

### Claim 12 (depends on 11)

The method of claim 11, wherein the pair of data points correspond to two data points in the modified convex hull on either side of the point on the vehicle.

### Claim 13 (depends on 11)

The method of claim 11, wherein the pair of data points correspond to two data points in the modified convex hull that are closest to the point on the vehicle.

### Claim 14 (depends on 13)

The method of claim 13, wherein removing data points of the first model includes identifying data points of the modified convex hull or the first model that are located farther from the point on the vehicle than either of the pair of data points.

### Claim 15 (depends on 1)

The method of claim 1, wherein removing data points of the first model includes identifying a pair of data points from the two-dimensional data points using a reference vector originating at a point on the vehicle.

### Claim 16 (depends on 15)

The method of claim 15, wherein the point on the vehicle is a two-dimensional point.

### Claim 17 (depends on 15)

The method of claim 15, wherein the reference vector extends in a direction of one of a heading of the vehicle or an orientation of the vehicle.

### Claim 18 (depends on 15)

The method of claim 15, wherein the reference vector extends in a direction of a direction of traffic of a lane in which the vehicle is traveling.

### Claim 19 (depends on 15)

The method of claim 15, wherein a first of the pair of data points is identified as a data point of the two-dimensional data points that is positioned at a smallest angle relative to the reference angle of the vehicle, and a second of the pair of data points is identified as a data point of the two-dimensional data points that is positioned at a greatest angle relative to the reference angle of the vehicle.

### Claim 20 (depends on 1)

The method of claim 1, wherein controlling the vehicle based on the second model includes passing data of the second model to one or more systems of the vehicle in order to make driving decisions for the vehicle using the second model.