Driving Simulators for Autonomous Vehicles: Comprehensive Review of Current Applications and Research Trends

Engineering notes

Key topics: autonomous driving, autonomous vehicle, adas, deployment, perception, planning, control. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Driving simulators have become essential tools for accelerating the development of advanced driver assistance systems (ADASs) and autonomous vehicles (AVs) by enabling safe, repeatable, flexible, and cost-effective experimentation across increasing levels of vehicle automation. Despite their growing adoption in both academia and industry, the recent literature lacks a comprehensive review that captures recent advancements and the expanding role of simulators in both feature-level ADAS development and fully autonomous driving research. This paper addresses this gap by presenting a systematic review of the evolution of driving simulators and their critical contributions to automotive research, testing, and validation. A structured taxonomy of contemporary simulators is introduced, encompassing fidelity, physical configuration, scale, licensing, and system integration strategies. Key application domains are examined, including driver-centred behaviour and human–machine interaction studies, traffic modelling and control, vehicle dynamics and powertrain development, and the testing of ADAS and autonomous driving subsystems across perception, planning, control, and vehicle-to-everything (V2X) communication. This review highlights driving simulators as foundational enablers for the safe, efficient, and scalable deployment of increasingly automated vehicle technologies.

Links and sources

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