  Feedback dynamic routing is a commonly used control strategy in
transportation systems. This class of control strategies relies on real-time
information about the traffic state in each link. However, such information may
not always be observable due to temporary sensing faults. In this article, we
consider dynamic routing over two parallel routes, where the sensing on each
link is subject to recurrent and random faults. The faults occur and clear
according to a finite-state Markov chain. When the sensing is faulty on a link,
the traffic state on that link appears to be zero to the controller. Building
on the theories of Markov processes and monotone dynamical systems, we derive
lower and upper bounds for the resilience score, i.e. the guaranteed throughput
of the network, in the face of sensing faults by establishing stability
conditions for the network. We use these results to study how a variety of key
parameters affect the resilience score of the network. The main conclusions
are: (i) Sensing faults can reduce throughput and destabilize a nominally
stable network; (ii) A higher failure rate does not necessarily reduce
throughput, and there may exist a worst rate that minimizes throughput; (iii)
Higher correlation between the failure probabilities of two links leads to
greater throughput; (iv) A large difference in capacity between two links can
result in a drop in throughput.
