# US 11,432,452 B2 · Vehicle sink alert system and method

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- Number: US 11,432,452 B2
- Document ID: US11432452B2
- Status: Granted
- Kind: B2
- Application number: 16/259,411
- Filed: 2019-01-28
- Published: 2020-07-30
- Granted: 2022-09-06
- Earliest claimed: 2019-01-28
- Assignees: Deere & Company
- Applicants: Deere & Company
- Inventors: Kirti Balani; Shibinkumar Krishnakumar; Vishal Rane
- Web page: https://patentgrep.com/patent/US11432452B2

## CPC

- A01B 76/00: Parts, details or accessories of agricultural machines or implements, not provided for in groups A01B51/00 - A01B75/00
- A01B 61/00: Devices for, or parts of, agricultural machines or implements for preventing overstrain
- A01B 69/004: {automatic}
- B60C 23/0408: {transmitting the signals by non-mechanical means from the wheel or tyre to a vehicle body mounted receiver}
- B60C 23/0477: {Evaluating waveform of pressure readings}
- G01C 11/025: {by scanning the object}
- G06N 20/00: Machine learning
- G06N 20/10: using kernel methods, e.g. support vector machines [SVM]
- G06Q 50/02: Agriculture; Fishing; Forestry; Mining
- A01B 63/112: to control draught load, i.e. tractive force
- A01B: SOIL WORKING IN AGRICULTURE OR FORESTRY; PARTS, DETAILS, OR ACCESSORIES OF AGRICULTURAL MACHINES OR IMPLEMENTS, IN GENERAL (making or covering furrows or holes for sowing, planting or manuring A01C5/00; mowers convertible to soil working apparatus or capable of soil working A01D42/04; mowers combined with soil working implements A01D43/12; soil working for engineering purposes E01, E02, E21)
- B60C: VEHICLE TYRES; TYRE INFLATION; TYRE CHANGING; CONNECTING VALVES TO INFLATABLE ELASTIC BODIES IN GENERAL; DEVICES OR ARRANGEMENTS RELATED TO TYRES
- 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
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR

## Abstract

A vehicle sink alert method and system that includes collecting image data, determining field conditions, calculating wheel sink depth, predicting vehicle sink events using wheel sink depth and field conditions, and activating an alert when a vehicle sink event is predicted. The method can include predicting vehicle sink events using GPS coordinates and historical vehicle sink data. The method can include determining and using vehicle motion to predict vehicle sink events. Predicting vehicle sink events can include forming a multi-dimensional model with positive sink points where vehicle sink events have occurred and negative sink points where vehicle sink events have not occurred; generating a current vehicle point using monitored and calculated data; determining whether the current vehicle point is within a positive sink region formed by the positive sink points; and predicting a vehicle sink event if the current vehicle point is within the positive sink region.

## Claims

### Claim 1

A vehicle sink alert method for a vehicle in a surroundings, the vehicle having a plurality of wheels, the vehicle sink alert method comprising:
monitoring lateral force exerted on a monitored wheel of the plurality of wheels using a force sensor coupled to the monitored wheel, the force sensor providing lateral force readings;
collecting image data of the surroundings using a camera;
monitoring vehicle sensors providing vehicle parameter readings, the vehicle parameter readings including vehicle speed readings;
calculating a wheel sink depth for the monitored wheel using the lateral force readings and the vehicle speed readings;
calculating field conditions using the image data;
monitoring vehicle location;
retrieving historical vehicle sink data with associated vehicle sink locations for each historical vehicle sink event; and
predicting whether a vehicle sink event is expected using the calculated wheel sink depth, the calculated field conditions, the monitored vehicle location and the historical vehicle sink data; and
activating an alert device when a vehicle sink event is predicted;
wherein predicting whether a vehicle sink event is expected comprises:
forming a multi-dimensional data model comprising positive sink data points where a historical vehicle sink event has occurred and negative sink data points where a historical vehicle sink event has not occurred;
generating a current vehicle data point using the calculated wheel sink depth, the calculated field conditions, the monitored vehicle location and the historical vehicle sink data;
determining whether the current vehicle data point is inside a positive sink region formed by the positive sink data points or outside the positive sink region; and
predicting a vehicle sink event is expected if the current vehicle data point is inside the positive sink region.

### Claim 2 (depends on 1)

The vehicle sink alert method of claim 1:
wherein monitoring vehicle location comprises monitoring Global Positioning System (GPS) coordinates of the vehicle using a GPS sensor;
wherein the associated vehicle sink locations for each historical vehicle sink event comprises associated GPS coordinates for each historical vehicle sink event; and
wherein predicting whether a vehicle sink event is expected further uses the GPS coordinates.

### Claim 3 (depends on 1)

The vehicle sink alert method of claim 1, further comprising:
determining vehicle motion using the image data and the vehicle parameter readings, the vehicle parameter readings further including vehicle throttle position readings and vehicle gear position readings; and
wherein predicting whether a vehicle sink event is expected further uses the determined vehicle motion.

### Claim 4 (depends on 3)

The vehicle sink alert method of claim 3, further comprising:
calculating a wheel sink depth change for the monitored wheel using current and previous values of the calculated wheel sink depth;
wherein predicting whether a vehicle sink event is expected further uses the wheel sink depth change.

### Claim 5 (depends on 1)

The vehicle sink alert method of claim 1, wherein determining whether the current vehicle data point is inside or outside the positive sink region comprises:
estimating a boundary separating the positive sink data points and the negative sink data points;
determining that the current vehicle data point is inside the positive sink region when the current vehicle data point is on the same side of the boundary as the positive sink data points; and
determining that the current vehicle data point is outside the positive sink region when the current vehicle data point is not on the same side of the boundary as the positive sink data points.

### Claim 6 (depends on 1)

The vehicle sink alert method of claim 1, the vehicle parameter readings further including vehicle throttle position readings and vehicle gear position readings; and the method further comprising:
determining whether a current vehicle sink event is occurring at the current vehicle data point using the image data, the vehicle throttle position readings and the vehicle gear position readings.

### Claim 7 (depends on 6)

The vehicle sink alert method of claim 6, further comprising:
adding the current vehicle data point to the multi-dimensional data model as an additional positive sink data point if the current vehicle data point is inside the positive sink region or a current vehicle sink event is occurring at the current vehicle data point; and
adding the current vehicle data point to the multi-dimensional data model as an additional negative sink data point if the current vehicle data point is not inside the positive sink region and a current vehicle sink event is not occurring at the current vehicle data point.

### Claim 8 (depends on 1)

The vehicle sink alert method of claim 1, wherein calculating a wheel sink depth for the monitored wheel comprises:
detecting a submerge time when the lateral force readings for the monitored wheel increase above a typical range;
detecting an emerge time when the lateral force readings for the monitored wheel decrease back to the typical range;
calculating an elapsed time from the submerge time to the emerge time;
calculating a submerged circumference for the monitored wheel based on the elapsed time and the vehicle speed readings; and
calculating the wheel sink depth for the monitored wheel based on the submerged circumference for the monitored wheel.

### Claim 9

A vehicle sink alert method for a vehicle in a surroundings, the vehicle having a plurality of wheels and a plurality of vehicle sensors, the vehicle sink alert method comprising:
receiving vehicle parameter readings from the plurality of vehicle sensors;
calculating a wheel sink depth for a monitored wheel of the plurality of wheels using the vehicle parameter readings;
receiving image data of the surroundings from a camera;
calculating field conditions using the image data;
predicting whether a vehicle sink event is expected using the calculated wheel sink depth and the calculated field conditions; and
activating an alert when a vehicle sink event is predicted;
wherein predicting whether a vehicle sink event is expected comprises:
forming a multi-dimensional data model comprising positive sink data points where a historical vehicle sink event has occurred and negative sink data points where a historical vehicle sink event has not occurred;
generating a current vehicle data point using current vehicle parameters;
determining whether the current vehicle data point is inside a positive sink region formed by the positive sink data points or outside the positive sink region; and
predicting a vehicle sink event is expected if the current vehicle data point is inside the positive sink region.

### Claim 10 (depends on 9)

The vehicle sink alert method of claim 9, further comprising:
receiving Global Positioning System (GPS) coordinates of the vehicle;
retrieving historical vehicle sink data with associated GPS coordinates for each historical vehicle sink event; and
wherein predicting whether a vehicle sink event is expected further uses the GPS coordinates and the historical vehicle sink data.

### Claim 11 (depends on 10)

The vehicle sink alert method of claim 10, further comprising:
calculating a wheel sink depth change for the monitored wheel using current and previous values of the calculated wheel sink depth;
wherein predicting whether a vehicle sink event is expected further uses the wheel sink depth change.

### Claim 12 (depends on 9)

The vehicle sink alert method of claim 9, further comprising:
determining vehicle motion using the image data and the vehicle parameter readings, the vehicle parameter readings including vehicle throttle position readings and vehicle gear position readings; and
determining whether a current vehicle sink event is occurring at the current vehicle data point using the image data, the vehicle throttle position readings and the vehicle gear position readings.

### Claim 13 (depends on 12)

The vehicle sink alert method of claim 12, further comprising:
adding the current vehicle data point to the multi-dimensional data model as an additional positive sink data point if the current vehicle data point is inside the positive sink region or a current vehicle sink event is occurring at the current vehicle data point; and
adding the current vehicle data point to the multi-dimensional data model as an additional negative sink data point if the current vehicle data point is not inside the positive sink region and a current vehicle sink event is not occurring at the current vehicle data point.

### Claim 14

A vehicle sink alert system for a vehicle that includes a plurality of vehicle sensors and a plurality of wheels, the vehicle sink alert system comprising:
a force sensor configured to be coupled to a monitored wheel of the plurality of wheels, to monitor lateral force on the monitored wheel and to provide lateral force readings;
a camera configured to collect image data;
a vehicle interface configured to communicate with the plurality of vehicle sensors to provide vehicle speed readings;
a controller configured to calculate wheel sink depth based on the lateral force readings and the vehicle speed readings, and to calculate field conditions based on the image data; and
an alert device;
wherein the controller is configured to predict whether a vehicle sink event is expected based on the calculated wheel sink depth and field conditions, and to activate the alert device when a vehicle sink event is predicted; and
wherein the controller is configured to access a multi-dimensional data model that includes positive sink data points where a historical vehicle sink event has occurred, negative sink data points where a historical vehicle sink event has not occurred, and a boundary that separates the positive sink data points from the negative sink data points; to generate a current vehicle data point from current monitored and calculated data; and to predict whether a vehicle sink event is expected based on whether the current vehicle data point is or is not on the side of the boundary with the positive sink data points.

### Claim 15 (depends on 14)

The vehicle sink alert system of claim 14, further comprising:
a Global Positioning System (GPS) sensor configured to monitor vehicle location and provide GPS readings; and
a memory configured to store historical vehicle sink data with associated GPS coordinates for each historical vehicle sink event;
wherein the controller is configured to predict whether a vehicle sink event is expected based also on the GPS readings and the historical vehicle sink data.

### Claim 16 (depends on 15)

The vehicle sink alert system of claim 15, wherein:
the vehicle interface is further configured to provide vehicle throttle position readings and vehicle gear position readings;
the controller is further configured to determine vehicle motion and to determine whether a current vehicle sink event has occurred at the current vehicle location based on the image data, the vehicle throttle position readings and the vehicle gear position readings; and
the controller is configured to predict whether a vehicle sink event is expected based also on the determined vehicle motion.

### Claim 17 (depends on 14)

The vehicle sink alert system of claim 14, wherein the controller is configured to add the current vehicle data point to the multi-dimensional data model as an additional positive sink data point if the current vehicle data point is on the side of the boundary with the positive sink data points or a current vehicle sink event has occurred at the current vehicle data point; and
the controller is configured to add the current vehicle data point to the multi-dimensional data model as an additional negative sink data point if the current vehicle data point is not on the side of the boundary with the positive sink data points and a current vehicle sink event has not occurred at the current vehicle data point.