A semi-autonomous decentralized system for controlling street traffic signals

Our work is based on distributed and knowledge-based methodology for real-time control of street and highway ramp signals. After a running prototype system that proved the feasibility of the approach, we have now completed the first part of a complex, two-phase learning program of the traffic control regime. It produces optimum local (intersection) control of signals in steady-state traffic scenarios. With appropriate communication between adjacent intersections, we should obtain an optimum, global, reactive and predictive control regime of the semi-autonomous, decentralized system.<
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