A survey of autonomous driving frameworks and simulators

Since autonomous driving (AD) is one of the most critical problems in the automobile industry, it has garnered the interest of many academics in recent years. An AD framework or a simulator is used to simulate autonomous vehicles (AVs), it can test modules that an AV needs. There are a large number of researchers studying specific AD simulation tasks, but few studies of systematic AD frameworks and simulators exist. This study distinguishes the functions of AD frameworks and simulators, and it makes a deep study of them, helping promote AV development for researchers, enterprises, and developers. This paper reviews open-source and commercial AD frameworks and simulators, introducing and comparing their features, functionalities, and so on. Additionally, we analyze current research on open-source AD frameworks and simulators according to different applied algorithms and hardware studies and discuss efforts to improve their simulation performance. In the last part, this paper proposes promising research fronts for AD frameworks and simulators for the near future from the viewpoints of hardware deficiencies, AD algorithms, scenario generation, vehicle-to-everything, safety and performance, and co-simulation.