Institute of Vehicles and Transportation, Military University of Technology (WAT), ul. gen. Sylwestra Kaliskiego 2, 00-908 Warsaw, Poland.
Łukasiewicz Research Network-Automotive Industry Institute (Łukasiewicz-PIMOT), ul. Jagiellońska 55, 03-301 Warsaw, Poland.
Sensors (Basel). 2022 Aug 31;22(17):6586. doi: 10.3390/s22176586.
Automated and autonomous vehicles are in an intensive development phase. It is a phase that requires a lot of modelling and experimental research. Experimental research into these vehicles is in its initial state. There is a lack of findings and standardized recommendations for the organization and creation of research scenarios. There are also many difficulties in creating research scenarios. The main difficulties are the large number of systems for simultaneous checking. Additionally, the vehicles have a very complicated structure. A review of current publications allowed for systematization of the research scenarios of vehicles and their components as well as the measurement systems used. These include perception systems, automated response to threats, and critical situations in the area of road safety. The scenarios analyzed ensure that the planned research tasks can be carried out, including the investigation of systems that enable autonomous driving. This study uses passenger cars equipped with highly sophisticated sensor systems and localization devices. Perception systems are the necessary equipment during the conducted study. They provide recognition of the environment, mainly through vision sensors (cameras) and lidars. The research tasks include autonomous driving along a detected road lane on a curvilinear track. The effective maintenance of the vehicle in this lane is assessed. The location used in the study is a set of specialized research tracks on which stationary or moving obstacles are often placed.
自动驾驶汽车正处于密集开发阶段。这是一个需要大量建模和实验研究的阶段。这些车辆的实验研究仍处于起步阶段，缺乏组织和创建研究场景的发现和标准化建议。创建研究场景也存在许多困难。主要困难在于需要同时检查的系统数量众多。此外，车辆的结构非常复杂。对当前出版物的回顾使得能够对车辆及其组件以及使用的测量系统的研究场景进行系统化。这些系统包括感知系统、对威胁和道路安全领域的危急情况的自动响应。所分析的场景确保可以执行计划的研究任务，包括对能够实现自动驾驶的系统的调查。本研究使用配备了高度复杂的传感器系统和定位设备的乘用车。在进行的研究中，感知系统是必要的设备。它们通过视觉传感器（摄像头）和激光雷达来提供对环境的识别。研究任务包括在检测到的弯道车道上自动驾驶。评估车辆在该车道上的有效保持。研究中使用的位置是一组专门的研究轨道，这些轨道上经常放置固定或移动的障碍物。
