Safety assessment of automated vehicle functions by simulation-based fault injection

As automated driving vehicles become more sophisticated and pervasive, it is increasingly important to assure its safety even in the presence of faults. This paper presents a simulation-based fault injection approach (Sabotage) aimed at assessing the safety of automated vehicle functions. In particular, we focus on a case study to forecast fault effects during the model-based design of a lateral control function. The goal is to determine the acceptable fault detection interval for permanent faults based on the maximum lateral error and steering saturation. In this work, we performed fault injection simulations to derive the most appropriate safety goals, safety requirements, and fault handling strategies at an early concept phase of an ISO 26262-compliant safety assessment process.The authors have partially received funding from the ECSEL JU AMASS project under H2020 grant agreement No 692474 and from MINETUR (Spain)

Fault injection method for safety and controllability evaluation of automated driving

Advanced Driver Assistance Systems (ADAS) and automated vehicle applications based on embedded sensors have become a reality today. As road vehicles increase its autonomy and the driver shares his role in the control loop, novel challenges on their dependability assessment arise. One key issue is that the notion of controllability becomes more complex when validating the robustness of the automated vehicle in the presence of faults. This paper presents a simulation-based fault injection approach aimed at finding acceptable controllability properties for the model-based design of control systems. We focus on determining the best fault models inserting exceptional conditions to accelerate the identification of specific areas for testing. In our work we performed fault injection method to find the most appropriate safety concepts, controllability properties and fault handling strategies at early design phases of lateral control functions based on the error in the Differential GPS signal.Authors wants to thank to the H2020 UnCoVerCPS Project (with grant number 643921) and the ECSEL JU AMASS project under H2020 grant agreement No 692474 and from MINETUR (Spain)

Towards improved Validation of Autonomous Systems for Smart Farming

SmartFarming Workshop was held as part of the CPS Week 2018, Porto - Portugal, April 10th - 13th, 2018.ENABLE-S3 is a use-case driven European research project focusing on the implementation and validation of autonomous cyber-physical systems (CPS) in different application domains. This work describes the efforts done so far in the development of infrastructure and tools to make improved validation concepts in agriculture, being part of one of the thirteen use cases included in the project. Aspects related to communication, autonomous vehicles, hyperspectral images, image processing, Unmanned Aerial Vehicles (UAVs), and simulation environments are described. The combination and interaction of these key technologies give rise to social, economic and environmental implications with enormous benefits, increasing the quality of the crops and reducing efforts during their growth and harvesting.info:eu-repo/semantics/publishedVersio