Simulation is a prospective method for generating diverse and realistic traffic scenarios to aid in the development of driving decision-making systems. However, existing simulators often fall short in diverse scenarios or interactive behavior models for traffic participants. This deficiency underscores the need for a flexible, reliable, user-friendly open-source simulator. Addressing this challenge, Tactics2D adopts a modular approach to traffic scenario construction, encompassing road elements, traffic regulations, behavior models, physics simulations for vehicles, and event detection mechanisms. By integrating numerous commonly utilized algorithms and configurations, Tactics2D empowers users to construct their driving scenarios effortlessly, just like assembling building blocks. Users can effectively evaluate the performance of driving decision-making models across various scenarios by leveraging both public datasets and user-collected real-world data. For access to the source code and community support, please visit the official GitHub page for Tactics2D at https://github.com/WoodOxen/Tactics2D.

翻译：仿真是一种生成多样化且真实交通场景的前瞻性方法，用于辅助驾驶决策系统的开发。然而，现有模拟器在场景多样性或交通参与者的交互行为模型方面往往存在不足。这种缺陷凸显了对灵活、可靠且用户友好的开源模拟器的需求。为应对这一挑战，Tactics2D采用模块化方法构建交通场景，涵盖道路元素、交通规则、行为模型、车辆物理仿真及事件检测机制。通过集成大量常用算法与配置，Tactics2D使用户能够像搭积木一样轻松构建驾驶场景。用户可借助公开数据集及自主采集的真实世界数据，在不同场景下有效评估驾驶决策模型的性能。如需获取源代码及社区支持，请访问Tactics2D的官方GitHub页面：https://github.com/WoodOxen/Tactics2D。