I was looking at GLSL's smoothstep, aka the Hermite for $f(0)=0, f'(0)=0, f(1)=1, f'(1)=0$.
That led to looking at the quintic Hermite as well, to get the acceleration to also be zero at the edges.
That had me wondering if just using higher degrees was better, but that just leads to (a shifted) Heaviside eventually (despite the discontinuity).
That led to me finding $f(x) = logistic({1\over{1-x}} - {1\over{x}})$ in the discussion of bump functions, to still get all the derivatives zero at the endpoints without approaching infinite velocity in the middle.
But of course there's more than just that one. From simple things like just changing the base of the exponent, to tossing in a √ so the plateau is shorter, to complicated things like the Fabius function, there's got to be lots of these.
Is there one of these that can reasonably be considered "best" for motion smoothing? Or is that just way too underconstrained to be meaningful question, especially since it's non-analytic so might be hard to analyze in the first place?