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Railway signaling has become more important over the years, with the increase in railway traffic and the use of highspeed trains. Since the most important aspect of a railway signaling system is safety, the decision-making ?interlocking system? is the critical element of a railway-signaling system. To satisfy the safety standards set for railway-signaling systems, the interlocking software design must be taken into account, using formal methods. In this study, an automata-based railway signaling and interlocking system is introduced and implemented, using a fail-safe programmable logic controller (PLC) on a scale railway model. [ABSTRACT FROM AUTHOR]

In this paper, an iterative learning approach for the freeway density control under ramp metering and speed regulation is developed in a macroscopic level traffic environment. Rigorous analyses show that the proposed learning control schemes guarantee the asymptotic convergence of the traffic density to the desired one. The two major features of the learning-based density control are 1) less prior modeling knowledge required in the control system design and 2) the ability to reject exogenous traffic perturbations. The control schemes are applied to a freeway model, and simulation results confirm the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]