# US 12,005,932 B2 · Method and device for automating a driving function

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- Number: US 12,005,932 B2
- Document ID: US12005932B2
- Status: Granted
- Kind: B2
- Application number: 16/944,083
- Filed: 2020-07-30
- Published: 2021-03-18
- Granted: 2024-06-11
- Earliest claimed: 2019-09-17
- Assignees: Robert Bosch GmbH
- Applicants: Robert Bosch GmbH
- Inventors: Rainer Baumgaertner
- Web page: https://patentgrep.com/patent/US12005932B2

## CPC

- B60W 60/0051: {from occupants to vehicle}
- G06N 5/02: Knowledge representation; Symbolic representation
- B60W 40/09: Driving style or behaviour
- B60W 50/12: Limiting control by the driver depending on vehicle state, e.g. interlocking means for the control input for preventing unsafe operation
- B60W 2556/30: Data update rate
- G06F 8/10: Requirements analysis; Specification techniques
- 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
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)

## Abstract

A method for automating a driving function. The method includes an activation of a process controlling the driving function is triggered using an activation condition modelled by a trigger, and the process is temporally controlled by an activation manager during the controlling of the driving function.

## Claims

### Claim 1

A method for automating a driving function, comprising the following steps:
triggering, using an activation condition modelled by a trigger, an activation of a process controlling the driving function; and
temporally controlling, by an activation manager, the process, during the controlling of the driving function, wherein:
the interprocess communication is carried out via middleware interfaces,
the activation condition is modelled using a predefined modelling language, and
states of the interfaces are expressed in the modelling language by Boolean variables, and the modeling language includes Boolean functions of the variables and comparison predicates for time stamps and sequence numbers.

### Claim 2 (depends on 1)

The method as recited in claim 1, wherein the functions are expressed in the modelling language in disjunctive normal form.

### Claim 3 (depends on 1)

The method as recited in claim 1, wherein the trigger is transferred to the process in the case of an activation.

### Claim 4 (depends on 1)

The method as recited in claim 1, further comprising at least one of the following:
the triggering is carried out by an interprocess communication, or
the triggering is carried out periodically.

### Claim 5

A non-transitory machine-readable memory medium on which is stored a computer program for automating a driving function, the computer program, when executed by a computer, causing the computer to perform the following steps:
triggering, using an activation condition modelled by a trigger, an activation of a process controlling the driving function; and
temporally controlling, by an activation manager, the process, during the controlling of the driving function, wherein:
the activation condition is modelled using a predefined modelling language, and
states of the interfaces are expressed in the modelling language by Boolean variables, and the modeling language includes Boolean functions of the variables and comparison predicates for time stamps and sequence numbers.

### Claim 6

A device for automating a driving function, the device configured to:
trigger, using an activation condition modelled by a trigger, an activation of a process controlling the driving function; and
temporally control, by an activation manager, the process, during the controlling of the driving function, wherein:
the activation condition is modelled using a predefined modelling language, and
states of the interfaces are expressed in the modelling language by Boolean variables, and the modeling language includes Boolean functions of the variables and comparison predicates for time stamps and sequence numbers.