We propose a perception imitation method to simulate results of a certain perception model, and discuss a new heuristic route of autonomous driving simulator without data synthesis. The motivation is that original sensor data is not always necessary for tasks such as planning and control when semantic perception results are ready, so that simulating perception directly is more economic and efficient. In this work, a series of evaluation methods such as matching metric and performance of downstream task are exploited to examine the simulation quality. Experiments show that our method is effective to model the behavior of learning-based perception model, and can be further applied in the proposed simulation route smoothly.

翻译：我们提出了一种感知模仿方法，用于模拟特定感知模型的结果，并探讨了一种无需数据合成的自动驾驶仿真新范式。其核心动机在于：当语义感知结果已可获取时，原始传感器数据对于规划与控制等任务并非必需，因此直接对感知过程进行模拟更具经济性与高效性。本研究采用匹配度量与下游任务性能等一系列评估方法，系统检验了模拟质量。实验表明，本方法能有效刻画基于学习的感知模型的行为特征，并可顺利应用于所提出的仿真范式。