论文标题
用于离散时间控制的数值稳定动态自行车模型
Numerically Stable Dynamic Bicycle Model for Discrete-time Control
论文作者
论文摘要
动态/运动学模型在智能车辆的决策和控制中具有重要意义。但是，由于低速动态模型的奇异性，运动学模型一直是许多驾驶场景下的唯一选择。本文使用向后的Euler方法的概念在任何低速下可行地提供了一个离散的动态自行车模型。我们进一步提供了足够的条件，基于证明数值的稳定性。仿真验证（1）提出的模型在数值上是稳定的，而前向欧拉人离散的动态模型分流； （2）与运动学模型相比，该模型将预测误差降低了49％。据我们所知，这是动态自行车模型首次有资格用于涉及停留任务的城市驾驶场景。
Dynamic/kinematic model is of great significance in decision and control of intelligent vehicles. However, due to the singularity of dynamic models at low speed, kinematic models have been the only choice under many driving scenarios. This paper presents a discrete dynamic bicycle model feasible at any low speed utilizing the concept of backward Euler method. We further give a sufficient condition, based on which the numerical stability is proved. Simulation verifies that (1) the proposed model is numerically stable while the forward-Euler discretized dynamic model diverges; (2) the model reduces forecast error by up to 49% compared to the kinematic model. As far as we know, it is the first time that a dynamic bicycle model is qualified for urban driving scenarios involving stop-and-go tasks.
