# US 11,079,497 B2 · Vehicle localization based on neural network

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- Number: US 11,079,497 B2
- Document ID: US11079497B2
- Status: Granted
- Kind: B2
- Application number: 16/139,433
- Filed: 2018-09-24
- Published: 2019-03-28
- Granted: 2021-08-03
- Earliest claimed: 2017-09-25
- Assignees: Continental Automotive Systems, Inc.
- Applicants: Continental Automotive Systems, Inc.
- Inventors: Dalong Li; Dominik Froehlich; Ibro Muharemovic
- Web page: https://patentgrep.com/patent/US11079497B2

## CPC

- G01S 19/49: whereby the further system is an inertial position system, e.g. loosely-coupled
- G01C 21/30: Map- or contour-matching
- G01S 19/48: by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
- G01S 19/485: {whereby the further system is an optical system or imaging system}
- G06N 3/0464: Convolutional networks [CNN, ConvNet]
- G06N 3/08: Learning methods
- G06N 3/09: Supervised learning
- G07C 5/008: {communicating information to a remotely located station (transmission systems for measured values G08C)}
- G08G 1/0104: {Measuring and analyzing of parameters relative to traffic conditions}
- G08G 1/0112: {from the vehicle, e.g. floating car data [FCD]}
- G08G 1/161: {Decentralised systems, e.g. inter-vehicle communication}
- G08G 1/22: {Platooning, i.e. convoy of communicating vehicles}
- G01C 22/00: Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers
- G01S 5/0289: {of multiple transceivers, e.g. in ad hoc networks}
- G01S 19/13: Receivers
- G01S 19/38: Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- 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
- 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)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G07C: TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93})

## Abstract

A method for determining a location of a vehicle is provided. The method includes receiving, at data processing hardware, a first set of vehicle system data from one or more vehicles. The method also includes determining, at the data processing hardware, a data model based on the first set of vehicle system data. Additionally, the method includes receiving, at the data processing hardware, a second set of vehicle system data associated with the vehicle. The vehicle being different than the one or more vehicles. The method includes determining, using the data processing hardware, a vehicle location based on the second set of vehicle system data and the data model. The method includes displaying, on a user interface of the vehicle in communication with the data processing hardware, the vehicle location.

## Claims

### Claim 1

A method for determining a location of a vehicle, the method comprising:
providing a data processing hardware, the data processing hardware comprising a trained neural network having a plurality of layers of nonlinear processing units, and memory hardware in communication with the data processing hardware, the memory hardware storing instructions of a processing algorithm;
executing, by the nonlinear processing units in a processing phase, the instructions of the processing algorithm to cause the nonlinear processing units to perform:
receiving, at the data processing hardware, a current vehicle system data associated with the vehicle, the vehicle being different than the training vehicles vehicle, the current set of vehicle system data including GPS location data, vehicle dynamics and image data generated by sensors or cameras mounted to the vehicle;
receiving a trained neural network model, the trained neural network model being part of the trained neural network and being based upon a training set of vehicle data comprising GPS location data, vehicle dynamics and sensor data associated with one or more vehicles during a training phase, the trained neural network model comprising weights and biases associated with the training set of vehicle data;
determining, using the data processing hardware, a vehicle location based on the current set of vehicle system data and the trained neural network model; and
transmitting, from the data processing hardware to a user interface of the vehicle in communication with the data processing hardware, a command to display the vehicle location.

### Claim 2 (depends on 1)

The method of claim 1, wherein the data processing hardware is supported by the vehicle.

### Claim 3 (depends on 1)

The method of claim 1, wherein the data processing hardware is in communication with the vehicle by way of a shared network.

### Claim 4 (depends on 1)

The method of claim 1, wherein the data processing hardware includes a first data processing hardware supported by the vehicle and a second data processing hardware in communication with the first data processing hardware by way of a shared network.

### Claim 5 (depends on 1)

The method of claim 1, wherein the training set of vehicle system data is associated with one or more vehicles captured during a predetermined period of time.

### Claim 6 (depends on 1)

The method of claim 1, wherein the current set of vehicle system data is received in real-time while the vehicle is maneuvering along a road.

### Claim 7

A system for determining a location of a vehicle, the system comprising:
data processing hardware in communication with the user display, the data processing hardware comprising a trained neural network having a plurality of layers of nonlinear processing units;
memory hardware in communication with the data processing hardware, the memory hardware storing instructions of a processing algorithm that when executed by the nonlinear processing units in a processing phase cause the nonlinear processing units to execute a method, the method including:
receiving a current set of vehicle system data associated with the vehicle, the current set of vehicle system data including GPS location data, vehicle dynamics and image data generated by sensors or cameras mounted to the vehicle;
receiving a trained neural network model, the trained neural network model being part of the trained neural network and being based upon a training set of vehicle data comprising GPS location data, vehicle dynamics and sensor data associated with one or more vehicles during a training phase, the trained neural network model comprising weights and biases associated with the training set of vehicle data;
determining a vehicle location based on the current set of vehicle system data and the trained neural network model; and
transmitting to a user interface of the vehicle a command to display the vehicle location.

### Claim 8 (depends on 7)

The system of claim 7, wherein the data processing hardware is supported by the vehicle.

### Claim 9 (depends on 7)

The system of claim 7, wherein the data processing hardware is in communication with the vehicle by way of a shared network.

### Claim 10 (depends on 7)

The system of claim 7, wherein the data processing hardware includes a first data processing hardware supported by the vehicle and a second data processing hardware in communication with the first data processing hardware by way of a shared network.

### Claim 11 (depends on 7)

The system of claim 7, wherein the training set of vehicle system data is associated with training vehicles captured during a predetermined period of time.

### Claim 12 (depends on 7)

The system of claim 7, wherein the current set of vehicle system data is received in real-time while the vehicle is maneuvering along a road.