Agent-Based Simulation Enhanced with Big Data and Artificial Intelligence Methods to Simulate and Optimize Traffic Flow

This proposal is a new agent-based simulation (ABS) to model complex traffic systems by dividing them into a set of interacting autonomous agents that learn the global dynamics of the traffic system from the big data of interactions of many individual behaviors. Our ultimate goal in this research is to integrate artificial intelligence (AI) and Big data technologies with agent-based simulation to realize the following two challenging objectives: 1. Develop a realistic simulation model for Al-Ain city calibrated using actual traffic Big Data that exhibits and demonstrates a realistic pattern of traffic flow, thereby allowing evaluating and visualizing network performance. 2. Using AI-based approaches namely Multi-Objective Metaheuristics, Reinforcement and Deep learning to optimize network flow by optimized signal timing and route choices.  

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Dec 24, 2019