  One-dimensional run-and-tumble processes may converge towards some localized
steady state when the two velocities and/or the two switching rates are
space-dependent. A long dynamical trajectory can be then analyzed via the large
deviations at Level 2.5 for the joint probability of the empirical densities,
of the empirical spatial currents and of the empirical switching flows. The
scaled cumulant generating function of general time-additive observables can be
obtained via contraction from the Level 2.5, or equivalently via the deformed
generator method and the corresponding Doob conditioned process. Finally, the
large deviations for the empirical intervals between consecutive switching
events can be derived via the introduction of the alternate Markov chain that
governs the series of all the switching events of a long trajectory.
