Navigating Dimensionality through State Machines in Automotive System Validation

TL;DR

The paper tackles the challenge of validating automated driving functions amid explosive scenario spaces in V2X-enabled, connected systems. It introduces a state-chart–based methodology to model interactions with external gray-box systems (e.g., RSUs and traffic lights) and couples these models with scenario-based VV to reduce dimensionality and guide test generation. Two use cases demonstrate how state charts support scenario coverage analysis and unit-test–driven test case generation, highlighting potential coverage gaps and enabling targeted validation efforts. The approach offers a scalable path to validate connected autonomous driving by focusing on information flow and subsystem interactions, with CARLA-based simulation illustrating practical feasibility and guiding data collection priorities. Future work aims to apply the method to real-world data to further validate and refine the approach in practice.

Abstract

The increasing automation of vehicles is resulting in the integration of more extensive in-vehicle sensor systems, electronic control units, and software. Additionally, vehicle-to-everything communication is seen as an opportunity to extend automated driving capabilities through information from a source outside the ego vehicle. However, the validation and verification of automated driving functions already pose a challenge due to the number of possible scenarios that can occur for a driving function, which makes it difficult to achieve comprehensive test coverage. Currently, the establishment of Safety Of The Intended Functionality ( SOTIF ) mandates the implementation of scenario-based testing. The introduction of additional external systems through vehicle-to-everything further complicates the problem and increases the scenario space. In this paper, a methodology based on state charts is proposed for modeling the interaction with external systems, which may remain as black boxes. This approach leverages the testability and coverage analysis inherent in state charts by combining them with scenario-based testing. The overall objective is to reduce the space of scenarios necessary for testing a networked driving function and to streamline validation and verification. The utilization of this approach is demonstrated using a simulated signalized intersection with a roadside unit that detects vulnerable road users.

Figures (7)

• Figure 1: Connected systems as state charts
• Figure 2: Concept of the state chart method
• Figure 3: Connected Systems as state charts
• Figure 4: Coverage of possible state combinations
• Figure 5: Unit tests for specific scenarios