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An automated driving system should have the ability to supervise its own performance and to request human driver to take over when necessary. In the lane keeping scenario, the prediction of vehicle future trajectory is the key to realize safe and trustworthy driving automation. Previous studies on vehicle trajectory prediction mainly fall into two categories, that is, physics-based and manoeuvre-based methods. Using a physics-based methodology, this article proposes a lane departure prediction algorithm based on closed-loop vehicle dynamics model. We use extended Kalman filter to estimate the current vehicle states based on sensing module outputs. Then, a Kalman Predictor with actual lane keeping control law is used to predict steering actions and vehicle states in the future. A lane departure assessment module evaluates the probabilistic distribution of vehicle corner positions and decides whether to initiate a human takeover request. The prediction algorithm is capable to describe the stochastic characteristics of future vehicle pose, which is preliminarily proved in simulated tests. Finally, the on-road tests at speeds of 15–50 km/h further show that the proposed method can accurately predict vehicle future trajectory. It may work as a promising solution to lane departure risk assessment for automated lane keeping functions. [ABSTRACT FROM AUTHOR]

Advanced Driver Assistance Systems (ADAS) such as Lane Keep Assist System (LKAS) offer drivers both convenience and safety benefits. However, assessing ADAS safety benefits can be challenging because crash reports typically include no information as to whether a system was active at the time of a crash. For example, LKAS systems are often disabled by drivers and may be unavailable to assist even when enabled, reducing the safety benefits of the system. However, the precise circumstances in which LKAS is unavailable remain not well known outside organizations directly involved in ADAS system design. This study seeks to make such information more broadly available, exploring the usage and effectiveness of ADAS, with an emphasis on LKAS, using in-vehicle message, accelerometer, and location data. In this study, data loggers were mounted in twelve vehicles owned or rented and driven by employee volunteers. Vehicle message data was decoded and standardized, with a focus on ADAS-related messages. Location data was merged with road feature and weather data. Decoded vehicle messages included fields identifying when the driver turned LKAS on and when the system was ready to assist the driver. Conditions in which the system was active or inactive are described, including two scenarios (concrete bridges and cloverleaf intersections) where the system repeatedly became inactive. [ABSTRACT FROM AUTHOR]

In recent years, driving simulators have been widely used by automotive manufacturers and researchers in human-in-the-loop experiments, because they can reduce time and prototyping costs, and provide unlimited parametrization, more safety, and higher repeatability. Simulators play an important role in studies about driver behavior in operating conditions or with unstable vehicles. The aim of the research is to study the effects that the force feedback (f.f.b.), provided to steering wheel by a lane-keeping-assist (LKA) system, has on a driver’s response in simulators. The steering’s force feedback system is tested by reproducing the conditions of criticality of the LKA system in order to minimize the distance required to recover the driving stability as a function of set f.f.b. intensity and speed. The results, obtained in three specific criticality conditions, show that the behaviour of the LKA system, reproduced in the simulator, is not immediately understood by the driver and, sometimes, it is in opposition with the interventions performed by the driver to ensure driving safety. The results also compare the performance of the subjects, either overall and classified into subgroups, with reference to the perception of the LKA system, evaluated by means of a questionnaire. The proposed experimental methodology is to be regarded as a contribution for the integration of acceptance tests in the evaluation of automation systems.

The implementation of autonomous vehicles involves an increase in the number and depth of system interactions in comparison to user-driven cars. There is a corresponding need to address the system safety implications of autonomy. Traditional hazard analysis techniques are not designed to identify hazardous states caused by system interactions. An emerging technique based on systems theory, Systems Theoretic Process Analysis (STPA), allows for inclusion of system-level causal factors by focusing on component interactions. This study researches the application of STPA to a lane keeping assist system, resulting in identification of design constraints and requirements needed to engineer a safer system. [ABSTRACT FROM AUTHOR]

In recent years, driving simulators have been widely used by automotive manufacturers and researchers in human-in-the-loop experiments, because they can reduce time and prototyping costs, and provide unlimited parametrization, more safety, and higher repeatability. Simulators play an important role in studies about driver behavior in operating conditions or with unstable vehicles. The aim of the research is to study the effects that the force feedback (f.f.b.), provided to steering wheel by a lane-keeping-assist (LKA) system, has on a driver's response in simulators. The steering's force feedback system is tested by reproducing the conditions of criticality of the LKA system in order to minimize the distance required to recover the driving stability as a function of set f.f.b. intensity and speed. The results, obtained in three specific criticality conditions, show that the behaviour of the LKA system, reproduced in the simulator, is not immediately understood by the driver and, sometimes, it is in opposition with the interventions performed by the driver to ensure driving safety. The results also compare the performance of the subjects, either overall and classified into subgroups, with reference to the perception of the LKA system, evaluated by means of a questionnaire. The proposed experimental methodology is to be regarded as a contribution for the integration of acceptance tests in the evaluation of automation systems. [ABSTRACT FROM AUTHOR]