通过路径点和速度调节，实现对驾驶模型行为的精准控制。
Control-ITRA: Controlling the Behavior of a Driving Model
- 用路径点和目标速度调控驾驶代理行为。
- 生成可控且无违规的行驶轨迹，保持真实感。
- 适合需要定制化交通场景的研究者使用。
在复杂交通环境中，模拟真实驾驶行为对自动驾驶系统研发与测试至关重要。同时，根据研究需求和安全考量，控制模拟智能体的行为同样关键。本文在通用多智能体驾驶行为模型ITRA（Scibior等，2021）基础上，提出Control-ITRA方法，通过路径点分配和目标速度调节来影响代理行为。借助这两个条件进行建模，使代理能遵循特定轨迹，并间接调整其激进程度。我们比较了训练阶段融合这些条件的不同方式，结果表明该方法可在已见与未见地点均生成可控、无违规的轨迹，同时保持行为真实性。
原文摘要 · Abstract (English)
Simulating realistic driving behavior is crucial for developing and testing autonomous systems in complex traffic environments. Equally important is the ability to control the behavior of simulated agents to tailor scenarios to specific research needs and safety considerations. This paper extends the general-purpose multi-agent driving behavior model ITRA (Scibior et al., 2021), by introducing a method called Control-ITRA to influence agent behavior through waypoint assignment and target speed modulation. By conditioning agents on these two aspects, we provide a mechanism for them to adhere to specific trajectories and indirectly adjust their aggressiveness. We compare different approaches for integrating these conditions during training and demonstrate that our method can generate controllable, infraction-free trajectories while preserving realism in both seen and unseen locations.
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