Virtual Validation of an Automated Lane-Keeping System with an Extended Operational Design Domain
Abstract
:1. Introduction
1.1. Safety Assessment for ADS
1.2. Virtual Testing of ADS for Safety Assessment
1.3. Scope of Work
- An ODD-driven virtual validation approach;
- A virtual validation simulation framework.
1.4. Structure of the Article
2. Virtual Validation of an ALKS
3. Virtual Validation of an ALKS with Varying ODD
3.1. Virtual Validation Framework for the ALKS with a Standard ODD
3.1.1. AD Function
3.1.2. Sensor Models
3.1.3. Virtual Environment
3.1.4. Vehicle Dynamics
3.2. Virtual Validation Framework for the ALKS with an Extended ODD
3.2.1. AD Function & Sensor Models
3.2.2. Virtual Environment
3.2.3. Vehicle Dynamics
3.2.4. Implementation Details
Algorithm 1: Simulation of a test case with the proposed co-simulation framework. |
4. Simulation Framework Comparison for the ALKS with Varying ODD
5. General Simulation Framework for Virtual Validation
6. Discussion and Outlook
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Abbreviations
ALKS | Automated lane-keeping system |
AD | Automated driving |
ADS | Automated driving system |
ACC | Adaptive cruise control |
TP | Traffic participants |
OEDR | Object and event detection and response |
ODD | Operational design domain |
FOV | Field of view |
DOF | Degree of freedom |
UN | United Nations |
V2X | Vehicle-to-X (e.g., infrastructure) |
ICOS | Independent co-simulation |
XIL | X-in-the-loop |
KPI | Key performance indicators |
ZOH | Zero-order hold |
SAE | Society of Automotive Engineers |
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ALKS Options | Details |
---|---|
Map-based ALKS | Lane-keeping based on a pre-captured map of the motorway |
Perception-based ALKS | Lane-keeping based on lane marking information gathered during runtime |
Interface | Signals | Applicable Standard |
---|---|---|
Actuation | Throttle, brake, steering angle | N/A |
Measurement | Sensor measurement | ASAM OSI® |
Ground truth | Environment ground truth | ASAM OSI® |
Vehicle pose | Global pose of ego vehicle | N/A |
Road network | Defined road network | ASAM OpenDRIVE® |
TP pose | Global pose of TP | N/A |
Environment control | Signals for TP & weather control | N/A |
Scenario description | Scenario description | ASAM OpenSCENARIO® |
Model Fidelity | Low | Medium | High |
---|---|---|---|
Sensor model | Object list-based. Based on ground truth data from simulation environment in the FOV (e.g., [57,63]) | Based on ideal models adding statistical failure rates, modified object list entries (e.g., [58,59]) | Based on the physical principles of the respective sensor type (e.g., [60]) |
Environment model | Able to place objects and update their pose, 2D representation of the scene | 3D representation of objects, no physics-rendering engine | Physics-based rendering engine enabling ray tracing |
Vehicle dynamics model | Point mass model | Single track vehicle model, double track vehicle model (excluding or including a dedicated tyre model) | Multibody vehicle model (including a tyre model) |
Subsystem | Requirements |
---|---|
AD function | Tactical and operational maneuvers: maintain speed, car following, lane-keeping. OEDR: relevant event/response pairs from [18]. Minimum risk manoeuvre: based on [22]. |
Vehicle dynamics | Dynamic model taking the friction between the road and tires into account (standard ODD). Medium-/high-fidelity model used to display the correct lateral behaviour of the car (extended ODD). |
Environment (virtual) | Lane markings (therefore also road, lanes, lane width, road curvature, elevation, lateral profile). Other traffic participants (cars, trucks, motorcycles) GPS -> Georeference (based on the needed environment information for ADS). |
Sensor models | Occlusion behavior, 3D-FOV (based on the necessary traffic scenarios). |
Subsystem | Standard ODD | Extended ODD |
---|---|---|
AD function: | ALKS | ALKS |
Sensor models: | Low-fidelity object sensor and lane marking sensor | Low-fidelity object sensor and lane marking sensor |
Environment simulation: | A2 motorway as virtual environment | Modified A2 motorway with added contruction zone |
Vehicle dynamics: | Python-based single track model | IPG CarMaker |
Subsystem | Parameter | Value | Unit |
---|---|---|---|
Co-simulation: | Coupling step size | 0.02 | s |
Test case | Coupling algorithm | ZOH | - |
Vehicle dynamics step size | 0.02 | s | |
Environment model step size | 0.02 | s | |
Sensor model step size | 0.02 | s | |
AD function step size | 0.02 | s | |
Execution order | Sequential | - | |
Scenario description | adapted from [71] | - | |
Sensor models | Number of sensors | 2 | # |
Type of sensor: | Sensor orientation | front-facing | - |
Low-fidelity | Sensor range | 55 | m |
object sensor | Sensor vertical FOV | 25 | deg |
Sensor horizontal FOV | 60 | deg | |
Type of sensor: | Sensor orientation | front-facing | - |
Lane marking | Sensor range | 30 | m |
sensor | Sensor horizontal FOV | 78 | deg |
Vehicle | Software | IPG CarMaker | - |
dynamics | Version | 8 | - |
Vehicle specification (standard vehicle) | Tesla Model S | - | |
AD function: | Target velocity (standard ODD) | 16 | m/s |
ALKS parameter | Target velocity (extended ODD) | 19 | m/s |
Framework Layer | Parameters | Formats | Description | Unit |
---|---|---|---|---|
Co-simulation | Coupling step size | Co-simulation setting specification format (e.g., XML) | Step size between simulation tools/models | s |
Simulation tool/model step size | Time between calculation step of individual tool/model | s | ||
Execution order | Order in which the individual models are calculated | # | ||
Extrapolation method | Used method for extrapolation (e.g., ZOH) | - | ||
Tool-specific co-simulation capability | Physical interface | ASAM OSI® | Defines the exchanged signals between tools/models | - |
Simulation tools | Parameters for first 5 layers of the 6 layer model [11] | ASAM OpenSCENARIO® | Scenario description | - |
Parameters describing the road network | ASAM OpenDRIVE® | Road network description | - | |
Parameters describing the road surface | ASAM OpenCRG® | Road surface description | - | |
Simulation models | Model specific parametrisation | Various | Necessary parameters to define the respective models | - |
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Weissensteiner, P.; Stettinger, G.; Rumetshofer, J.; Watzenig, D. Virtual Validation of an Automated Lane-Keeping System with an Extended Operational Design Domain. Electronics 2022, 11, 72. https://doi.org/10.3390/electronics11010072
Weissensteiner P, Stettinger G, Rumetshofer J, Watzenig D. Virtual Validation of an Automated Lane-Keeping System with an Extended Operational Design Domain. Electronics. 2022; 11(1):72. https://doi.org/10.3390/electronics11010072
Chicago/Turabian StyleWeissensteiner, Patrick, Georg Stettinger, Johannes Rumetshofer, and Daniel Watzenig. 2022. "Virtual Validation of an Automated Lane-Keeping System with an Extended Operational Design Domain" Electronics 11, no. 1: 72. https://doi.org/10.3390/electronics11010072
APA StyleWeissensteiner, P., Stettinger, G., Rumetshofer, J., & Watzenig, D. (2022). Virtual Validation of an Automated Lane-Keeping System with an Extended Operational Design Domain. Electronics, 11(1), 72. https://doi.org/10.3390/electronics11010072