RNN using multiple time series
Multivariate time series is an active research topic you will find a lot of recent paper tackling the subject. 

To answer your questions, you can use a single RNN. You can input one value for each time step. Nothing keeps you from adding another value at each time step (if your sensor are synchronized). Your model will then learn how to classify with a two dimensional time series.

You check this blog. In your case, only the output is different.

As for the two last points, aggregating the time series into one is risky in the sense that you might lose important information during the process. Finally the main disadvantage of your last point is that you won't be able to use a potential correlation between the two time series for the final classification.