  We present the design and validation of a centralized controller, called a
supervisor, for collision avoidance of multiple human-driven vehicles at a road
intersection, considering measurement errors, unmodeled dynamics, and
uncontrolled vehicles. We design the supervisor to be least restrictive, that
is, to minimize its interferences with human drivers. This performance metric
is given a precise mathematical form by splitting the design process into two
subproblems: verification problem and supervisor-design problem. The
verification problem determines whether an input signal exists that makes
controlled vehicles avoid collisions at all future times. The supervisor is
designed such that if the verification problem returns yes, it allows the
drivers' desired inputs; otherwise, it overrides controlled vehicles to prevent
collisions. As a result, we propose exact and efficient supervisors. The exact
supervisor solves the verification problem exactly but with combinatorial
complexity. In contrast, the efficient supervisor solves the verification
problem within a quantified approximation bound in polynomially bounded time
with the number of controlled vehicles. We validate the performances of both
supervisors through simulation and experimental testing.
