Granted Patent B2

US 12,657,969 · App. 18/023,413 · Granted Jun 16, 2026

Inventors: Saadhana B Venkataraman (Chennai, IN); Vijaya Sarathi Indla (Bangalore, IN); Bony Mathew (Perumbavoor, IN); Saikat Mukherjee (Bangalore, IN); Ram Padhy (Ganjam, IN); Sagar Pathrudkar (Pune, IN); Bristi Singh (Bangalore, IN)

Assignee: Siemens Industry Software NV

G07C5/0808G08G1/0112

Abstract

Claims (47)

1 . A computer implemented method for identifying one or more critical scenarios from vehicle data associated with one or more vehicles, the computer implemented method, the method comprising:

obtaining a predefined type of data from the vehicle data recorded by physical IMU sensors mounted on the one or more vehicles, wherein the predefined type of data comprises at least inertial measurement unit (IMU) data, wherein the IMU data is purely searchable text data available in a structured format including timestamps of time instances at which the IMU data was recorded, angular velocity at the time instances, and linear acceleration at the time instances, wherein the structured and searchable format enables automated detection of threshold exceedances used by a data analysis module to identify the one or more critical scenarios;

deriving one or more IMU-based driving parameters from the predefined type of data;

analyzing the one or more IMU-based driving parameters based on one or more predefined thresholds for identifying the one or more critical scenarios;

generating, by a scenario management module of a scenario identification system, one or more traffic scenarios using the vehicle data corresponding to the IMU-based driving parameters exceeding the predefined thresholds;

validating, by the scenario management module, the one or more traffic scenarios for criticality; and

providing the one or more validated traffic scenarios, including associated criticality indices, to a traffic modeling device or vehicle-control verification system for use in verifying, validating, or updating one or more autonomous-vehicle behavior policies that control operation of a vehicle.

2 . The computer implemented method of claim 1 , wherein the IMU-based driving parameters comprise one or more of an acceleration of the vehicle, a velocity of the vehicle, or a trajectory of the vehicle.

3 . The computer implemented method of claim 1 , wherein obtaining the predefined type of data from the vehicle data comprises performing one of:

selecting the IMU data from the vehicle data; or

computing the IMU data based on the vehicle data.

4 . A scenario identification system for identifying one or more critical scenarios from vehicle data associated with one or more vehicles, the scenario identification system comprising:

a non-transitory computer readable storage medium configured to store computer program instructions defined by modules of the scenario identification system;

at least one processor communicatively coupled to the non-transitory computer readable storage medium, the at least one processor configured to execute the defined computer program instructions;

a data reception module configured to operably communicate with the one or more vehicles to receive the vehicle data recorded by physical IMU sensors mounted on the one or more vehicles;

a data processing module configured to:

obtain a predefined type of data from the vehicle data, wherein the predefined type of data comprises at least inertial measurement unit (IMU) data, wherein the IMU data is purely searchable text data available in a structured format including timestamps of time instances at which the IMU data was recorded, angular velocity at the time instances, and linear acceleration at the time instances, wherein the structured and searchable format enables automated detection of threshold exceedances used by a data analysis module to identify the one or more critical scenarios; and

derive IMU-based driving parameters from the predefined type of data, the IMU-based driving parameters comprising at least acceleration, velocity, and trajectory;

the data analysis module configured to analyze the IMU-based driving parameters based on one or more predefined thresholds for identifying the one or more critical scenarios;

a scenario management module configured to:

generate one or more traffic scenarios using the vehicle data corresponding to the one or more IMU-based driving parameters exceeding the one or more predefined thresholds;

validate the one or more traffic scenarios for criticality;

provide the one or more validated traffic scenarios, including associated criticality indices, to a traffic modeling device or vehicle-control verification system for use in verifying, validating, or updating one or more autonomous-vehicle behavior policies that control operation of a vehicle; and

a scenario management database configured to store the vehicle data, the IMU data, the one or more IMU-based driving parameters, the one or more predefined thresholds corresponding to each of the one or more IMU-based driving parameters, and the one or more traffic scenarios.

5 . The scenario identification system of claim 4 , further comprising a data reception module configured to operably communicate with the one or more vehicles and one or more traffic modeling devices for receiving the vehicle data.

6 . A system comprising:

a primary vehicle comprising one or more physical sensors configured to acquire vehicle data related to the primary vehicle;

a scenario identification system for identifying one or more critical scenarios from the vehicle data associated with the primary vehicle, the scenario identification system comprising:

a non-transitory computer readable storage medium configured to store computer program instructions defined by modules of the scenario identification system;

at least one processor communicatively coupled to the non-transitory computer readable storage medium, the at least one processor configured to execute the defined computer program instructions;

a data reception module configured to operably communicate with the one or more vehicles to receive the vehicle data;

a data processing module configured to:

obtain a predefined type of data from the vehicle data, wherein the predefined type of data comprises at least inertial measurement unit (IMU) data, wherein the IMU data is purely searchable text data available in a structured format including timestamps of time instances at which the IMU data was recorded, angular velocity at the time instances, and linear acceleration at the time instances, wherein the structured and searchable format enables automated detection of threshold exceedances used by a data analysis module to identify the one or more critical scenarios; and

derive one or more IMU-based driving parameters from the predefined type of data;

a data analysis module configured to analyze the one or more IMU-based driving parameters based on one or more predefined thresholds for identifying the one or more critical scenarios;

a scenario management module configured to:

generate one or more traffic scenarios using the vehicle data corresponding to the one or more IMU-based driving parameters exceeding the one or more predefined thresholds;

validate the one or more traffic scenarios for criticality; and

provide the one or more validated traffic scenarios, including associated criticality indices, to a traffic modeling device or vehicle-control verification system for use in verifying, validating, or updating one or more autonomous-vehicle behavior policies that control operation of a vehicle; and

a scenario management database configured to store the vehicle data, the IMU data, the one or more IMU-based driving parameters, the one or more predefined thresholds corresponding to each of the one or more IMU-based driving parameters, and the one or more traffic scenarios.

7 . The system of claim 6 , wherein the data processing module is configured to:

translate the vehicle data to one or more features comprising objects that are located through detection and segmentation;

inputting the located objects to one or more filters; and

deriving a state of each object in the surrounding using a random variable concept having a probability assigned to each variable;

wherein the state is used to derive information related to force, angular measurements and magnetic field.

8 . The system of claim 6 , wherein the one or more sensors comprise at least a LIDAR system.

9 . The system of claim 6 , wherein the predefined thresholds comprise where when a lateral acceleration of the primary vehicle is greater than 2.5 meters/sec2 or when the lateral deceleration of the primary vehicle is greater than 2.9 meters/sec2.

Assignments (2)

Continuity (1)

References Cited (21)