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)

36 Retos de ciberseguridad en automoción. Cifrando el bus CAN

Se pretende profundizar en las necesidades de ciberseguridad en las comunicaciones intra-vehiculares. La tecnología de los vehículos conectados es tendencia, y más recientemente con la entrada de la tecnología 5G para comunicar los vehículos. Se viene innovando en la protección de las nuevas redes de comunicación entre vehículos, no obstante, este no son el único punto vulnerable de los vehículos. La principal red de comunicación interna de los sistemas críticos del vehículo, la conocida como Controller Area Network (CAN) se ha visto vulnerada en distintos ataques- Este documento recoge las vulnerabilidades del bus CAN y la aplicación de técnicas de cifrado para obtener autenticidad e integridad de los datos

Design-Time Safety Assessment of Robotic Systems Using Fault Injection Simulation in a Model-Driven Approach

International audienceThe rapid advancement of autonomy in robotic systems together with the increasing interaction with humans in shared workspaces (e.g. collaborative robots), raises pressing concerns about system safety. In recent years, the need of modeldriven approaches for safety analysis during the design stage has gained a lot of attention. In this context, simulation-based fault injection combined with a virtual robot is a promising practice to complement traditional safety analysis. Fault injection is used to identify the potential safety hazard scenarios and to evaluate the controller's robustness to certain faults. Besides, it enables a quantitative assessment w.r.t. other techniques that only give qualitative hints, such as FMEA. Thus, it facilitates the refinement of safety requirements and the conception of concrete mitigation actions. This paper presents a tool-supported approach that leverages models and simulation-assisted fault injection to assess safety and reliability of robotic systems in the early phases of design. The feasibility of this method is demonstrated by applying it to the design of a real-time cartesian impedance control system in torque mode as a use case scenario