Integrated Path-Tracking and Combined-Slip Force Controls of Autonomous Ground Vehicles With Safe Constraints Adaptation

IF 14 1区 工程技术 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Ehsan Hashemi;Amir Khajepour
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引用次数: 0

Abstract

A novel integrated stabilization and path tracking control framework, which includes the combined-slip effect, wheel dynamics, and tire force capacities, is developed for autonomous ground vehicles. The loss of cornering forces caused by increased longitudinal slip are considered in the prediction model of the developed receding horizon controls. Robustness to uncertainties in the road surface friction is addressed by an adaptive constraint scheme on the side handling-limit boundaries in order to provide a reliable stable performance. The integrated framework with constraint adaptation resolves possible conflicts of the multi-actuated system for lateral stabilization, while trajectory tracking on various surface conditions. The performance of the proposed approach, in terms of accuracy and computational efficiency, is evaluated by using hardware-in-the-loop real-time experiments and a high-fidelity CarSim model in various pure- and combined-slip maneuvers, under different road friction conditions. The real-time experiments confirm effectiveness and reliable performance of the proposed approach over existing algorithms, in dealing with reduced tire capacities in harsh obstacle avoidance and cornering scenarios, while path following, as a consequence of constraint adaptation and simultaneous vehicle-wheel stabilization.
具有安全约束适应性的自主地面飞行器的综合路径跟踪和组合滑力控制
为自主地面车辆开发了一种新颖的综合稳定和路径跟踪控制框架,其中包括联合滑移效应、车轮动力学和轮胎受力能力。在所开发的后退地平线控制预测模型中,考虑了纵向滑移增加造成的转弯力损失。为了提供可靠稳定的性能,对路面摩擦力的不确定性采用了侧面操控限制边界自适应约束方案。在各种路面条件下进行轨迹跟踪时,具有约束适应性的集成框架解决了多驱动系统在横向稳定方面可能出现的冲突。在不同的路面摩擦条件下,利用硬件在环实时实验和高保真 CarSim 模型,在各种纯滑动和组合滑动机动中评估了所提方法在精度和计算效率方面的性能。实时实验证实,与现有算法相比,所提出的方法在处理恶劣的避障和转弯场景中轮胎承受能力降低的问题时,以及在路径跟踪过程中,由于约束适应和车辆-车轮同步稳定的结果,具有有效和可靠的性能。
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来源期刊
IEEE Transactions on Intelligent Vehicles
IEEE Transactions on Intelligent Vehicles Mathematics-Control and Optimization
CiteScore
12.10
自引率
13.40%
发文量
177
期刊介绍: The IEEE Transactions on Intelligent Vehicles (T-IV) is a premier platform for publishing peer-reviewed articles that present innovative research concepts, application results, significant theoretical findings, and application case studies in the field of intelligent vehicles. With a particular emphasis on automated vehicles within roadway environments, T-IV aims to raise awareness of pressing research and application challenges. Our focus is on providing critical information to the intelligent vehicle community, serving as a dissemination vehicle for IEEE ITS Society members and others interested in learning about the state-of-the-art developments and progress in research and applications related to intelligent vehicles. Join us in advancing knowledge and innovation in this dynamic field.
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