Adaptive strategies for route selection en-route in transportation networks

We examine adaptive strategies adopted by vehicles for route selection en-route in transportation networks. By studying a model of two-dimensional cellular automata, we characterized parameter called path-greediness, which corresponds to the tendency them travel their destinations via shortest path. The path-greediness each individual vehicle is updated based on local traffic conditions, either keep travels shorter path an un-congested region or explore longer diverted paths congested region. found that optimal number steps trigger update dependent density vehicles, and magnitude increment affects macroscopic conditions system. To better coordinate denser networks, should be gradual less frequent.