提取操作和观察你的信息u can use to create other environments or agents.
The reinforcement learning environment for this example is the simple longitudinal dynamics for ego car and lead car. The training goal is to make the ego car travel at a set velocity while maintaining a safe distance from lead car by controlling longitudinal acceleration (and braking). This example uses the same vehicle model as theAdaptive Cruise Control System Using Model Predictive Control(Model Predictive Control Toolbox)example.
Open the model and create the reinforcement learning environment.
obsInfoExt = rlNumericSpec with properties: LowerLimit: [3x1 double] UpperLimit: [3x1 double] Name: "observations" Description: "information on velocity error and ego velocity" Dimension: [3 1] DataType: "double"
The action information contains acceleration values while the observation information contains the velocity and velocity error values of the ego vehicle.
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