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- W638908560 abstract "A recently developed fundamentally different approach for optimal centralized signal timing eliminates the need for an open-loop traffic model. The new approach uses a neural network (NN) as the basis for the control law. The internal NN weight estimation occurs real time in closed-loop mode via the simultaneous perturbation stochastic approximation (SPSA) algorithm. This paper investigates applying such a non-network-model-based approach to the problem of adapting real time to long-term traffic variations. The approach is illustrated by simulation on a nine-intersection, mid-Manhattan network with varying short- and long-term congestion behavior and short-term stochastic, nonlinear effects. The approach results in a net 10-percent reduction in vehicle wait time over the performance of the existing, in-place strategy." @default.
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- W638908560 date "1995-01-01" @default.
- W638908560 modified "2023-09-22" @default.
- W638908560 title "EVALUATION OF REAL-TIME, NON-NETWORK-MODEL-BASED TRAFFIC SIGNAL CONTROL TECHNIQUE IN THE PRESENCE OF LONG-TERM TRENDS" @default.
- W638908560 hasPublicationYear "1995" @default.
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