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

对道路事故数据的分析表明，全世界每年有120多万人死于道路事故。在大多数交通事故中，驾驶员行为或驾驶员失误是最关键的原因。这些都要求车辆自动化的新兴发展，不仅提供了更好的驾驶安全性，而且还提高了儿童，老年人，残疾人谁不能驾驶的效率和流动性。目前由多家汽车制造商开发的现有自动驾驶汽车为自动驾驶提供了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，完全自动驾驶在大规模上仍然不可行。研究还表明，许多用户在乘坐自动驾驶汽车时会晕车，这将对公众接受和自动驾驶汽车的快速普及产生相当大的负面影响。此外，更高级别的自动化车辆将有望为用户提供足够的灵活性，以便在道路上的车辆中完成与工作相关的任务。为了提高自动驾驶汽车的用户友好性和车内任务效率，本研究旨在开发一种新的框架，类似人类的自动驾驶，集成驾驶风格识别和自动驾驶算法。研究成果将有助于提高用户友好性，舒适性，并实现自动驾驶汽车的个性化。拟议的研究计划将通过新的科学进步和技术创新，为类人自动驾驶开创一个新的范式。该框架有效地连接了人类驾驶员驾驶风格的基本理解和表征以及自动驾驶轨迹规划和跟踪控制，以实现自动驾驶中的“类人”属性。新的模式将有助于汽车公司开发新一代的自动驾驶汽车，使其更加个性化和用户友好。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极好的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. ******