Does Reinforcement Learning Toolbox support discretization in space, instead of time?

Hello,

I have noticed that almost every example in the 'Reinforcement Learning Help Center' uses a fixed sample time Ts, and the Episode Steps equals to Tf divided by Ts (Tf/Ts). But now I have a problem that a vehicle runs on a hilly road of which the total length is 10km. The action of RL agent is the torque from vehicle motor. If I set a fixed sample time, lets say Ts = 1s, and Tf = 600s, I cannot guarantee that the vehicle reaches destination right on the moment of 600s. So I need to discretize the total length of 10km into 1000 segments, each segment ( delta_S ) equals to 10 meters. I was wondering does the Rinforcement Learning Toolbox in Simulink support this operation?

I really appreciate if someone could help me!

Thanks very much !!!!

[Emmanouil Tzorakoleftherakis]

I don't think this is possible but at the same time I am not sure why you would want to do that. If you action is torque, wouldn't the whole point be to apply sufficient torque such that the vehicle reaches its destination within the specified time?