  This paper proposes a novel monitoring methodology for car-following control
of automated vehicles that uses real-time measurements of spacing and velocity
obtained through vehicle sensors. This study focuses on monitoring the time
gap, a key parameter that dictates the desired following spacing of the
controlled vehicle. The goal is to monitor deviations in actual time gap from a
desired setting and detect when it deviates beyond a control limit. A random
coefficient modeling is developed to systematically capture the stochastic
distribution of the time gap and derive a closed-form Bayesian updating scheme
for real-time inference. A control chart is then adopted to systematically set
the control limits and inform when the time gap setting should be changed.
Simulation experiments are performed to demonstrate the effectiveness of the
proposes method for monitoring the time gap and alerting when the parameter
setting needs to be changed.
