Driving-style-oriented human-like automated driving and its verification

对道路交通事故数据的分析表明，全世界每年有120多万人死于道路交通事故。在大多数交通事故中，驾驶员的行为或驾驶员的失误是最关键的原因。这些都呼唤车辆自动化的新兴发展，它不仅提供更好的驾驶安全，而且为不能驾驶的儿童、老年人和残疾人提供更高的效率和机动性。目前由几家汽车制造商开发的现有自动车辆为自动驾驶提供了一个非常令人鼓舞的未来，然而，在克服一些重要的技术挑战之前，完全自动驾驶仍然是不可行的。研究还表明，许多用户在乘坐自动驾驶车辆时会晕车，这将对自动驾驶车辆的公众接受度和快速普及产生相当大的负面影响。此外，预计更高水平的自动化车辆将为用户提供足够的灵活性，以便在道路上的车辆上执行与工作有关的任务。为了提高自动驾驶车辆的用户友好性和车载任务效率，本研究旨在开发一种集驾驶风格识别和自动驾驶算法于一体的新型仿人自动驾驶框架。研究成果将有助于提高自动化车辆的用户友好性和舒适性，并实现个性化。*拟议的研究计划将以新的科学进步和技术创新开启仿人自动驾驶的新范式。该框架有效地连接了对人类驾驶员驾驶风格的基本理解和表征，以及自主驾驶轨迹规划和跟踪控制，从而实现了自动驾驶中的类人属性。新的模式将有助于汽车公司开发个性化和更友好的新一代自动驾驶车辆。此外，该项目的研究成果将有助于提高公众的接受度，为政策制定者提供与自动驾驶汽车用户体验相关的建议，并加速自动驾驶汽车的渗透。该研究计划还将为直接参与的四名研究生以及实验室的其他学生成员提供绝佳的HQP培训机会。******

Analyses of road accident data have shown that there are more than 1.2 million road fatalities every year worldwide. In most of the traffic accidents, the driver behaviour or driver error is the most critical causal factor. These are calling for an emerging development of vehicle automation which provides not only the improved driving safety, but also the increased efficiency and mobility for children, elderly, disabled who are not able to drive.*******The currently existing automated vehicles developed by several car manufacturers provide a very encouraging future for automated driving, however, fully automated driving is still infeasible at a large scale before overcoming some important technological challenges. Studies have also shown that many users experience motion sickness while riding in an automated vehicle, which would indicate a considerable negative impact on the public acceptance and quick penetration of automated vehicles. Furthermore, higher-level automated vehicles would be expected to provide users sufficient flexibilities for doing work-related tasks in the vehicle on the road. In order to enhance the user-friendliness as well as in-vehicle task efficiency for automated vehicles, this proposed research aims to develop a novel framework of human-like automated driving that integrates driving style recognition and autonomous driving algorithms. The research outcomes will help to improve the user friendliness, comfort and also achieve personalization of automated vehicles.*******The proposed research program will initiate a new paradigm for human-like automated driving with new scientific advances and technological innovations. The framework effectively bridges the fundamental understanding and characterization of human driver driving styles and autonomous driving trajectory planning and tracking control, for achieving the ‘human-like' attribute in automated driving. The new paradigm will help to enable the car companies to develop new-generation of automated driving vehicles to be personalized and more user-friendly. Furthermore, the research outcomes of this program will assist to boost the public acceptance, offer recommendations related to user experience in automated vehicles for policy makers, and accelerate the penetration of automated vehicles. The research program will also offer an excellent HQP training opportunity for the four graduate students directly involved as well as other student members in the laboratory. ******