# US 11,299,179 B2 · Quality index and real-time forward propagation of virtual controls for smart enablement of automated driving

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

- Number: US 11,299,179 B2
- Document ID: US11299179B2
- Status: Granted
- Kind: B2
- Application number: 16/814,146
- Filed: 2020-03-10
- Published: 2021-09-16
- Granted: 2022-04-12
- Earliest claimed: 2020-03-10
- Assignees: GM Global Technology Operations LLC
- Applicants: GM Global Technology Operations LLC
- Inventors: Reza Zarringhalam; Mohammadali Shahriari; Amir Takhmar; Zhi Li
- Web page: https://patentgrep.com/patent/US11299179B2

## CPC

- B60W 60/0016: {of the vehicle or its occupants}
- B60W 60/0059: {Estimation of the risk associated with autonomous or manual driving, e.g. situation too complex, sensor failure or driver incapacity}
- B60W 50/0097: {Predicting future conditions}
- B60W 60/001: {Planning or execution of driving tasks}
- B60W 60/0011: {involving control alternatives for a single driving scenario, e.g. planning several paths to avoid obstacles}
- B60W 60/0051: {from occupants to vehicle}
- B60W 60/0054: {Selection of occupant to assume driving tasks}
- 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

## Abstract

A system to enable an automobile vehicle automated driving control includes a quality index of an automated driving control system prior to enablement of an automated driving control function of an automobile vehicle. An adaptive forward propagation horizon and a prediction horizon for assessment of the quality index are computed. Vehicle states and road geometry are propagated over the adaptive forward propagation horizon, and the quality index is assessed based on forward propagated states over the prediction horizon. A first signal permits actuation of the automated driving control function of the automobile vehicle and a second signal precludes actuation of the automated driving control function. One of the first signal or the second signal is elected based on the results of assessing a quality control index trajectory over the adaptive forward propagation horizon.

## Claims

### Claim 1

A system to enable an automobile vehicle automated driving control in an automobile vehicle, comprising:
a switch configured to enable the automobile vehicle automated driving control; and
a controller in communication with the switch, the controller configured to:
determine a quality index of an automated driving control system of the automobile vehicle applied prior to enablement of the automated driving control function of the automobile vehicle;
calculate an adaptive forward propagation horizon of the automobile vehicle, wherein the adaptive forward propagation horizon is predicted for multiple “N” future predicted vehicle positions represented by predicted forward moving positions of the automobile vehicle over a predetermined window of time, and wherein a value of the “N” future predicted vehicle positions is calculated as a function of a vehicle velocity, a vehicle forward acceleration, a vehicle lateral acceleration, a road geometry, and lane markings;
determine an assessment of the quality index over the adaptive forward propagation horizon; and
generate a first signal permitting enablement of the automated driving control function of the automobile vehicle and a second signal precluding enablement of the automated driving control function, one of the first signal or the second signal elected based on the assessment of the quality index over the adaptive forward propagation horizon.

### Claim 2 (depends on 1)

The system to enable the automobile vehicle automated driving control of claim 1, wherein the quality index includes weighted penalties assigned to variables when calculating the quality index, the weighted penalties grouped into three categories including:
a first category defining multiple safety event penalties applied to multiple safety event elements;
a second category defining multiple actuation penalties applied to multiple actuation elements; and
a third category defining multiple performance and comfort penalties applied to multiple performance and comfort elements.

### Claim 3 (depends on 2)

The system to enable the automobile vehicle automated driving control of claim 2, wherein the safety event penalties have safety event penalty weighting factors and the actuation penalties have actuation penalty weighting factors, and wherein the safety event penalty weighting factors are greater than the actuation penalty weighting factors.

### Claim 4 (depends on 3)

The system to enable the automobile vehicle automated driving control of claim 3, wherein the performance and comfort penalties have performance and comfort weighting factors and the actuation penalty weighting factors are greater than the performance and comfort weighting factors.

### Claim 5 (depends on 1)

The system to enable the automobile vehicle automated driving control of claim 1, further including a virtual controller providing real-time calculation of vehicle states including position, heading, and steering angle and path following curvature included in the calculation of the vehicle adaptive forward propagation over the prediction horizon.

### Claim 6 (depends on 5)

The system to enable the automobile vehicle automated driving control of claim 5, further including a tracking control utilizing multiple vehicle state inputs to generate a virtual vehicle state horizon signal forwarded to a virtual curvature control.

### Claim 7 (depends on 6)

The system to enable the automobile vehicle automated driving control of claim 6, further including a virtual steering angle control, and wherein:
a virtual curvature control signal is generated by the virtual curvature control and forwarded to the virtual steering angle control; and
a virtual steering angle signal is generated by the virtual steering angle control and applied to calculate the vehicle forward propagation over adaptive horizon.

### Claim 8 (depends on 1)

The system to enable the automobile vehicle automated driving control of claim 1, wherein the value of the “N” future predicted vehicle positions is further calculated as a function of a yaw rate, a lane proximity, a curvature tracking error, a yaw rate error, a steering angle, a steering angle rate and a torque commanded.

### Claim 9

A method to enable an automobile vehicle automated driving control in an automobile vehicle, comprising:
actuating, by a user of the automobile vehicle, a switch to enable the automated driving control function;
performing, by a controller, an assessment applying a quality index of an automated driving feature prior to enablement of the automated driving control function of an automobile vehicle;
calculating, by the controller, an adaptive forward propagation horizon and an adaptive horizon of the automobile vehicle having multiple “N” future predicted states of the automobile vehicle including positions of the automobile vehicle over a predetermined window of time;
propagating, by the controller, a road geometry for the “N” future predicted states of the automobile vehicle; and
electing, by the controller, between permitting enablement of the automated driving control function and precluding enablement of the automated driving control function based on the multiple “N” future predicted states of the automobile vehicle in the adaptive forward propagation horizon.

### Claim 10 (depends on 9)

The method to enable the automobile vehicle automated driving control of claim 9, further including:
conducting in parallel with actuating the switch a vehicle model data generation, a road geometry data generation, a driver input collection and a vehicle parameters collection.

### Claim 11 (depends on 10)

The method to enable the automobile vehicle automated driving control of claim 10, further including:
collecting data from the vehicle model data generation, the road geometry data generation, the driver input collection and the vehicle parameters collection together with sensor data from multiple automobile vehicle dynamics sensors; and
applying the data and the sensor data during the calculating the adaptive forward propagation and the adaptive horizon.

### Claim 12 (depends on 11)

The method to enable the automobile vehicle automated driving control of claim 11, further including:
performing the assessment applying the quality index over a predetermined time window; and
performing a quality index rate matrix generation over a moving time window.

### Claim 13 (depends on 12)

The method to enable the automobile vehicle automated driving control of claim 12, further including forwarding a change of the quality index and a rate of change of the quality index to a decision-making block, wherein in the decision-making block, a first determination is made if an absolute value of the change of the quality index is less than a first threshold β1 and a second determination is made if an absolute value of the rate of change of the quality index is less than a second threshold β2, and a third determination is made to identify if the rate of change of the quality index is also negative definite.

### Claim 14 (depends on 13)

The method to enable the automobile vehicle automated driving control of claim 13, further including generating an allow controls signal which permits enablement of the automated driving control function if the first determination identifies the absolute value of the change of the quality index is less than the first threshold β1 and the second determination identifies the absolute value of the rate of change of the quality index is less than the second threshold β2 and the third determination identifies the rate of change of the quality index is also negative definite.

### Claim 15 (depends on 13)

The method to enable the automobile vehicle automated driving control of claim 13, further including generating an inhibit controls signal which prohibits enablement of the automated driving control function if any of the first determination identifies the absolute value of the change of the quality index is equal to or greater than the first threshold β1, the second determination identifies the absolute value of the rate of change of the quality index is equal to or greater than the second threshold β2 or the third determination identifies the rate of change of the quality index is not negative definite.

### Claim 16

A method to enable an automobile vehicle automated driving control in an automobile vehicle, comprising:
actuating, by a user of the automobile vehicle, a switch to enable the automated driving control function;
conducting in parallel, by a controller, a vehicle model data generation, a road geometry data generation, a driver input collection and a vehicle parameters collection;
applying, by the controller, the vehicle model data generation, the road geometry data generation, the driver input collection and the vehicle parameters collection in a quality index;
calculating, by the controller, an adaptive forward propagation horizon of the automobile vehicle, wherein the adaptive forward propagation horizon is predicted for multiple “N” future predicted vehicle positions represented by predicted forward moving positions of the automobile vehicle over a predetermined window of time;
assessing, by the controller, the quality index over the adaptive forward propagation horizon; and
electing, by the controller, between permitting enablement of the automated driving control function and precluding enablement of the automated driving control function based on the results of the assessing of the quality index.

### Claim 17 (depends on 16)

The method to enable the automobile vehicle automated driving control of claim 16, further including calculating a value of the “N” future predicted states of the automobile vehicle as a function of multiple variables, the multiple variables including vehicle performance constraints generated from data of a vehicle dynamics model, safety constraints, and actuation constraints.