Improving the bus flow in a Bus Rapid Transit system: an approach based on cellular automata simulations
We studied the bus flow in a Bus Rapid Transit (BRT) system using a novel approach based on a cellular automata (CA) that properly accounts for bus interactions. The model quantitatively reproduces the bus queuing behaviour for both fixed and random dwell times, with one bus service. For more bus services, our results show that the bus flow strongly depends not only on how the buses are distributed among the services, but also on how the bus stops are physically arranged at the stations. The latter dependence has hitherto not been considered in common BRT optimization methods. By using a genetic algorithm, we could find the bus distribution that maximizes the bus flow for a given stops arrangement at the stations, and explore its evolution with the bus density. Our results suggest a set of guidelines which could be applied on working BRT systems to improve the bus flow.