###### Abstract  
Safety validation of Autonomous Vehicles (AV) requires simulation. Automotive manufacturers need to generate scenarios used during this simulation-based validation process. Several approaches have been proposed to master scenario generation. However, none have proposed a method to measure the potential hazardous of the scenarios with regard to the performance limitations of AV. In other words, there is no method offering a metric to guide the search for potentially critical scenarios within the infinite space of scenarios. However, designers have knowledge of the functional limitations of AV components depending on the situations encountered. The more sensitive the AV is to a situation, the more safety experts consider it to be critical. In this paper, we present a new method to help estimate the sensitivity of AV to logical situations and events before their use for the generation of concrete scenarios submitted to simulators. We propose a characterization of the inputs used for sensitivity analysis (definition of the context of the automation function, generation of functional and logical situations with their associated events). We then propose an approach to set up a distribution function that will make it possible to select situations and events according to their importance in terms of sensitivity. We illustrate this approach by implementing it on the Traffic Jam Chauffet (TJC) function. Finally, we compare the obtained sensitivity rank with expert judgment to demonstrate its relevance. This approach has been shown to be a promising method to guide the search for potentially hazardous scenarios that are relevant to the simulation-based safety validation process for AV. road safety; autonomous vehicles; safety validation; sensitivity metric; safety of the intended functionality; logical situation; scenario generation; simulation-based validation Article  
An Approach to Guide the Search for Potentially Hazardous Scenarios for Scenarios for Autonomous Vehicle Safety  
This new standard ISO 21448 is to be used complementarily with the ISO 26262 standard. It is commonly called SOTIF (Safety Of the Intended Functionality), which means: \"absence of unreasonable risk due to hazards resulting from functional insufficiencies of the intended functionality or from reasonably foreseeable misuse by persons\" (ISO 21448, 2022). The technologies used to develop an AV are specific: sensors, localization systems, communication systems and intelligent control systems (potentially including Artificial Intelligence based algorithms). These technologies are subject to limitations which are mainly due to the environment features in which the vehicle will operate, e.g., rain, fog, snow, degradation of pavements, puddles, curvature of roads, lack of road markings [3; 4]. This environment is very complex and its description involves a large number of parameters which must be identified. Therefore, the activities detailed in the standard are intended to define an efficient process for identifying and dealing with scenarios that will be critical for the AV during its operational phase. According to the standard, critical scenarios relate to two areas: the first refers to \"known unsafe scenarios\" (area 2) and the second to \"unknown unsafe scenarios\" (area 3). To explore these two areas, simulation-based validation approaches need to be used to complement driving validation [5]. This is all the more true given that [PERSON] and [PERSON] [6] have demonstrated that the validation of AV by driving would require covering billions of kilometers. The use of simulation has many advantages, including testing controllability and path planning strategies, simulating different ranges of operational parameters, ensuring reproducibility and efficiency of the tests [7; 8], testing specific collision avoidance strategies [9], etc.