Traffic Signal Predictive Control Based on Cellular Automata Prediction Model and Non-Analytical Optimization

Hong Wang; Yong Hua Zhou; Yang Peng Wang; Wei Wang; Xu Yang

doi:10.4028/www.scientific.net/AMR.433-440.2831

Paper Titles

An Interactive Neural Network for Constrained Multi-Objective Optimization with Application to the Design of Digital Filters
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Calculation and Forecast on Coefficient of Static Frequency Characteristics Based on Curve Fitting
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Study and Simulation on Photovoltaic Grid-Connected System
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Design and Analysis for the Hybrid Capacitance and Micro-Leverage Amplifier Actuator
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Traffic Signal Predictive Control Based on Cellular Automata Prediction Model and Non-Analytical Optimization
p.2831

Using Backward-Traversing Waveform Relaxation Algorithm to Perform Incremental Simulation and Simulation-on-Demand for Circuit Simulation
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Design and Analysis of Digital Filter in Digital Down Converter
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Power System Subsynchronous Oscillations Electromagnetic and Electromechanical Transient Hybrid Real-Time Simulation Based on RTDS
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An New Fuzzy Support Vector Machine for Binary Classification
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 433-440Traffic Signal Predictive Control Based on...

Traffic Signal Predictive Control Based on Cellular Automata Prediction Model and Non-Analytical Optimization

Abstract:

The effective control strategies of traffic signal can increase the passing-through traffic volume and decrease the total queue delay. Based on the prediction model of cellular automata, the corresponding non-analytical optimization procedure utilizing genetic algorithm is established for the traffic signal predictive control. The inductive predictive control for traffic signal is proposed which has certain practical importance. The simulation results demonstrate the advantages of proposed predictive control strategy over the conventional methods.