Good approach to increase accuracy for a continuous value that is highly variable/sensitive to the inputs?
Taking the difference (ie speed1-speed2) as the target variable effectively dismisses any low-frequency variablitiy and targets only high-frequency variability, even noise.
One approach would be to bin the (highly-variable) target variable into fixed range bins and take the mid point (or any other fixed point) of each bin as the new target (stabilised) variable. This will decrease variability (and noise) a bit, or even a lot. Then any regression algorithm can be used on the new stabilised target variable with most probably better results (depending of course on the number of bins, more bins more variability, less bins less variability but there can be some balance point).