2,717 research outputs found

    Lateral Evasive Maneuver with Shared Control Algorithm: A Simulator Study

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    Shared control algorithms have emerged as a promising approach for enabling real-time driver automated system cooperation in automated vehicles. These algorithms allow human drivers to actively participate in the driving process while receiving continuous assistance from the automated system in specific scenarios. However, despite the theoretical benefits being analyzed in various works, further demonstrations of the effectiveness and user acceptance of these approaches in real-world scenarios are required due to the involvement of the human driver in the control loop. Given this perspective, this paper presents and analyzes the results of a simulator-based study conducted to evaluate a shared control algorithm for a critical lateral maneuver. The maneuver involves the automated system helping to avoid an oncoming motorcycle that enters the vehicle’s lane. The study’s goal is to assess the algorithm’s performance, safety, and user acceptance within this specific scenario. For this purpose, objective measures, such as collision avoidance and lane departure prevention, as well as subjective measures related to the driver’s sense of safety and comfort are studied. In addition, three levels of assistance (gentle, intermediate, and aggressive) are tested in two driver state conditions (focused and distracted). The findings have important implications for the development and execution of shared control algorithms, paving the way for their incorporation into actual vehicles.This research is supported by the EU Commission HADRIAN project. HADRIAN has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 875597. The publication is supported by the EU Commission Aware2All project, under grant agreement No 97878

    On pre-emptive vehicle stability control

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    Future vehicle localisation technologies enable major enhancements of vehicle dynamics control. This study proposes a novel vehicle stability control paradigm, based on pre-emptive control that considers the curvature profile of the expected path ahead in the computation of the reference direct yaw moment and braking control action. The additional information allows pre-emptive trail braking control, which slows down the vehicle if the predicted speed profile based on the current torque demand is deemed incompatible with the reference trajectory ahead. Nonlinear model predictive control is used to implement the approach, in which also the steering angle and reference yaw rate provided to the internal model are varied along the prediction horizon, to account for the expected vehicle path. Two pre-emptive stability control configurations with different levels of complexity are proposed and compared with the passive vehicle, and two state-of-the-art nonlinear model predictive stability controllers, one with and one without non-pre-emptive trail braking control. The performance is assessed along obstacle avoidance tests, simulated with a high-fidelity model of an electric vehicle with in-wheel motors. Results show that the pre-emptive controllers achieve higher maximum entry speeds – up to ∼34% and ∼60% in high and low tyre-road friction conditions – than the formulations without preview.This work was supported in part by the Horizon 2020 Framework Programme of the European Commission under grant agreements no. 769944 (STEVE project) and no. 824311 (ACHILES project)

    Trends in vehicle motion control for automated driving on public roads

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    In this paper, we describe how vehicle systems and the vehicle motion control are affected by automated driving on public roads. We describe the redundancy needed for a road vehicle to meet certain safety goals. The concept of system safety as well as system solutions to fault tolerant actuation of steering and braking and the associated fault tolerant power supply is described. Notably restriction of the operational domain in case of reduced capability of the driving automation system is discussed. Further we consider path tracking, state estimation of vehicle motion control required for automated driving as well as an example of a minimum risk manoeuver and redundant steering by means of differential braking. The steering by differential braking could offer heterogeneous or dissimilar redundancy that complements the redundancy of described fault tolerant steering systems for driving automation equipped vehicles. Finally, the important topic of verification of driving automation systems is addressed

    Robust Fault-Tolerant Control of In-Wheel Driven Bus with Cornering Energy Minimization

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    The aim of this paper is to design fault-tolerant and energy optimal trajectory tracking control for a four-wheel independently actuated (FWIA) electric bus with a steer-by-wire steering system. During normal driving conditions, the architecture of the proposed controller enables the bus to select an energy optimal split between steering intervention and torque vectoring, realized by the independently actuated in-wheel motors by minimizing the cornering resistance of the bus. In the case of skidding or a fault event of an in-wheel motor or the steering system, a high-level control reconfiguration using linear parameter varying (LPV) techniques is applied to reallocate control signals in order to stabilize the bus. The main novelty of the paper is the control reconfiguration method based on the specific characteristics of the in-wheel bus which enables introducing such scheduling variables, with which the safety and efficiency of the FWIA bus can be enhanced
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