###### Abstract
Previous authors have worked on the validation of automotive models and propose an assessment process that is not only focused on safety validation, but also on the quantification of modeling errors and uncertainties of the simulation compared to real driving [10]. However, the process of implementing simulation-based safety validation must allow sufficient coverage of the operational environment of the AV and meet the \"mile of driving\" requirement. Thus, there is a need for an approach which can identify the set of test scenarios and contribute to an efficient simulation-based validation process [11]. Such an approach would make it possible to select the scenarios that the AV has to face, in particular those that are considered to be challenging, to achieve the validation objectives more quickly. The main issue is how to identify these scenarios. On the road, frequent and often unchallenging scenarios (considered as nominal) will be encountered but rare and challenging scenarios may not be encountered. The simulation must therefore be oriented to test the AV with critical scenarios that are particularly interesting in order to demonstrate the safety of the vehicle. Some approaches have been suggested in the industrial domain to help identify these test scenarios [12]: feedback from experience, feedback from users, accidentology databases, information extracted from driving, consortiums and projects such as MOOVE or PEGASUS. However, despite the efforts made by the car manufacturers, it is difficult to predict all the real-life situations that AV will face, due to many variations in environmental conditions (traffic conditions, weather conditions, infrastructure, behaviors of other road users). As a result, other recommendations to control the scenario generation process have been proposed. The first is to deploy the AV by level of automation. In this case, the vehicle is limited to a number of tactical maneuvers and can carry out its mission in a dedicated and controlled environment called ODD (Operational Design Domain). Another proposal is to structure scenarios into three levels of abstraction in order to gradually identify them: functional, logical and concrete [13]. The functional scenario describes all entities and their relationships in a human-understandable linguistic form. The second level, the logical scenario, uses the functional scenario to describe the state space using parameter ranges. Finally, the concrete scenario allows concrete values to be assigned to the previously defined parameters. This is obtained by choosing a value for each parameter from the range of values defined in the corresponding logical scenario. Structuring scenarios in three levels of abstraction is interesting because it allows a scenario-based approach for the development of AV, while offering a hierarchical approach to structuring the generation process within the infinite space of scenarios. These approaches seem interesting and helpful in the scenario identification process. However, to the best of our knowledge, there is no approach which proposes a metric to identify potentially critical scenarios in advance, in order to guide scenario generation before the simulation. In the literature, several performance indicators (criteria and metrics) have been proposed for the validation of AV [14; 15; 16]. Most of these indicators are used during and after simulation or driving to evaluate the safety level of AV. This means that the proposed indicators can only be used when the scenarios are run, before the measurement is made. In other words, these indicators cannot be used to guide scenario generation, as they only qualify the situation after the simulation. Therefore, in this paper, we propose an approach to analyze and estimate the sensitivity of AV to logical situations and events, in order to guide the search for scenarios that are relevant to the simulation-based safety validation process. The rest of the paper is organized as follows. Section 2 is a more detailed review of the state of the art.