Data-driven online stochastic synchronization strategies of a bus line in a transit network

The waiting time of passengers at transfer stations is one of the most important criteria to measure the service quality of public bus transportation. Because of the stochastic nature of traffic, scheduled transfers cannot always occur. This research develops an online control framework for a bus network using holding, skip-stop and speed change tactics. We build an arc-flow model integrating all possible tactics within an optimization horizon. The model minimizes total passenger travel times by improving, among others, transfer times and reducing deviations from the bus schedule. The methodology is tested on a case-study of the bus system of the city of Laval, Canada. A simulation framework is then developed, integrating real-time data on smart card transactions and bus locations, to verify the results of the optimization model. The number of offline optimizations which can be performed in between decisions is limited by the travel time between stops. We compare the performance of two online stochastic algorithms-Regret and Consensus.