Assessing the Decisional Capability for an ODD-Compliant Automatic Lane Change System via Sense-Think-Act Paradigm

As autonomous vehicles become more advanced, ensuring their safe and reliable operation is critical. Intelligent Vehicles (IVs) must make real-time decisions while adapting to dynamic environments, such as changing weather conditions, road obstacles, or varying traffic scenarios. However, for an optimal and safe vehicle navigation, it must remain within its Operational Design Domain (ODD), the set of conditions under which it is designed to operate safely. If a vehicle exceeds these limits, the risks of failure, unsafe behavior, or costly interventions increase. A key challenge is aligning the vehicle’s capabilities with its ODD. This means that before executing any maneuver, the vehicle must assess whether it has the necessary capabilities to perform it safely. Current monitoring approaches focus on detecting violations after they occur rather than anticipating them. Furthermore, as vehicles gain autonomy, scalable evaluation methods are needed for ODD compliance. This paper proposes an approach based on the Sense-Think-Act paradigm, utilizing skill graphs to dynamically assess the vehicle’s decisional capability for a lane change maneuver. This allows the IV to assess whether it can successfully perform the maneuver while staying within its ODD. The modular structure of the approach makes it compatible with long-term decision-making. Finally, simulation results prove the efficiency of the approach in preventing the vehicle from exiting its ODD.