Several scenarios and traffic flows could be implemented in the simulation approach in order to evaluate the ADF evolution. ADF applied in the simulation will surely improve the safe circulation of the ego vehicle, as well as other road users. All scenarios identified as potentially critical, such as hard deceleration or an accident, should be addressed and studied. Feedback from the simulations will allow the evolution of the ADF and could help ensure that it handles real world driving safely. The critical scenarios mainly arise from malfunctions of AVs but also from unpredictable manoeuvres from other road users and the traffic flow. The identification of critical scenarios is a key factor in the validation of the ADF. A method to identify critical scenarios in the simulation is to canvas expert opinions and use peer reviews (Hallerbach et al., 2018). Guidance on traffic disturbance critical scenarios for ADF up to 60 km/h is provided by the ALKS regulation (UNECE, 2021a).
Main Question
Are simulations being used to evaluate ADF evolution by implementing different scenarios and traffic models?
Sub-Questions
- Are different scenarios, different environments or regions and different traffic flows considered and implemented in the simulation?
- Are emergent, cooperative and interoperability aspects addressed in the simulation?
- Are there appropriate metrics to identify the critical scenarios in the simulation?
- Are there appropriate countermeasures to cover the critical scenarios in the simulation?
References
- Hallerbach, S. et al. (2018) ‘Simulation-based identification of critical scenarios for cooperative and Automated Vehicles’, SAE International Journal of Connected and Automated Vehicles, 1(2), pp. 93–106. doi: https://doi.org/10.4271/2018-01-1066
- UNECE (2021a) Uniform provisions concerning the approval of vehicles with regard to Automated Lane Keeping Systems, Available at: https://op.europa.eu/en/publication-detail/-/publication/36fd3041-807a-11eb-9ac9-01aa75ed71a1 (Accessed: 27 October 2023).