Semi-Autonomous Driving Control of Multi-Trailer Articulated Heavy Vehicles for Increasing Highway Traffic Safety

多挂车铰接式重型车辆的半自动驾驶控制，提高公路交通安全

• 批准号: RGPIN-2019-05437
• 负责人: He, Yuping
• 金额: $ 2.33万
• 依托单位: University of Ontario Institute of Technology
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=715546
• 关键词: Semi; Autonomous; Driving; Control; Multi

To increase the safety of multi-trailer articulated heavy vehicles (MTAHVs), attention has been paid to exploring active vehicle safety systems (AVSSs), e.g. anti-lock braking systems. These AVSS technologies are classified as reactive safety systems', designed to react to the current vehicle state. These systems are effective, but do not consider the effect of driver errors. The main cause of traffic accidents is linked to human errors. A resolution to the problem is autonomous driving, which removes human factors from the control loop. There will be a long transition period, during which most vehicles have some capabilities of autonomous driving. Since the late 1990s, lane departure warning and adaptive cruise control systems have been proposed. These technologies are classified as predictive safety systems' (PSSs), considering not only the current vehicle state, but also the predicted vehicle state and environmental hazards. These systems assist the driver in identifying, assessing, and avoiding impending hazards. For passenger vehicles, several PSSs have been investigated. These PSSs are featured with semi-autonomous driving functions. MTAHVs represent a 7.5 times higher risk than passenger cars in highway operations. However, much less attention has been paid to exploring these PSSs for MTAHVs. This research will develop a novel design methodology for semi-autonomous driving systems of MTAHVs. The interrelated innovative investigations will be conducted: 1) Modelling and simulation of human driver behaviors and MTAHV dynamics. To conduct numerical and real-time simulations, two versions of MTAHV and driver models are derived and validated. Moreover, a multi-lane one-direction highway and surrounding vehicles will be modelled. 2) Motion planning and predictive threat assessment. The motion trajectories of the MTAHV driven by the driver under typical highway operations are predicted using simulations. Critical safety measures of MTAHVs will be identified and evaluated. 3) An autonomous driving system with automated steering and braking capabilities. The automated steering and braking system for MTAHVs is designed using a well-suited control technique. 4) Exploring the interactions of driver-automation-environment. A semi-autonomous driving system for MTAHVs is designed with the shared driving control between the driver and the proposed automated driving system. Various intervention laws for the automated system will be explored. 5) Developing a design synthesis framework. A simulation-based bi-level design synthesis framework is proposed and tested for designing MTAHVs with the semi-autonomous driving. The research will not only contribute to increasing the safety of MTAHVs, but also advancing the understanding and science of the interactions of driver-controller-vehicle and autonomous driving.

为了提高多拖车铰接式重型车辆（MTAHVS）的安全性，注意探索主动车辆安全系统（AVSSS），例如防抱死制动系统。这些AVSS技术被归类为反应性安全系统，旨在对当前的车辆状态做出反应。这些系统是有效的，但不考虑驾驶员错误的效果。交通事故的主要原因与人类错误有关。解决该问题的解决方案是自主驾驶，它从控制循环中消除了人为因素。将有一个漫长的过渡期，在此期间，大多数车辆具有自动驾驶的一定功能。自1990年代后期以来，已经提出了车道出发警告和自适应巡航控制系统。这些技术被归类为预测安全系统（PSSS），不仅考虑了当前的车辆状态，还考虑了预测的车辆状态和环境危害。这些系统可以帮助驾驶员识别，评估和避免即将发生的危害。对于乘用车，已经研究了几个PSS。这些PSS具有半自治驾驶功能。 MTAHVS的风险是高速公路运营中的乘用车的7.5倍。但是，对探索MTAHVS的这些PSS的关注要少得多。 这项研究将开发一种新型的设计方法，用于MTAHVS的半自治驾驶系统。相互关联的创新调查将进行： 1）人类驱动程序行为和MTAHV动力学的建模和模拟。为了进行数值和实时模拟，得出和验证了两个版本的MTAHV和驱动程序模型。此外，将建模多车道的单向高速公路和周围车辆。 2）运动计划和预测威胁评估。使用模拟预测，在典型的高速公路操作下，由驾驶员驱动的MTAHV的运动轨迹。将确定和评估MTAHV的关键安全措施。 3）具有自动转向和制动功能的自动驾驶系统。 MTAHVS的自动转向和制动系统是使用合理的控制技术设计的。 4）探索驾驶员自动化环境的相互作用。 MTAHVS的半自治驾驶系统的设计，其驾驶员与拟议的自动驾驶系统之间的共享驾驶控制。将探讨自动化系统的各种干预法。 5）开发设计综合框架。提出了一个基于模拟的双层设计合成框架，并测试了使用半自主驾驶设计MTAHV。 这项研究不仅有助于提高MTAHV的安全性，而且还可以促进对驾驶员控制器 - 车辆和自动驾驶的相互作用的理解和科学。