Real-time bus departure time predictions: Vehicle trajectory and countdown display analysis

Uncertainty is an important challenge in operating bus systems. Accurate real-time predictions can therefore facilitate adaptive decision making process of both operations and passengers. This scheme should be tractable, fast and reliable to be used in real time applications. This paper presents a hybrid prediction scheme to generate real-time information concerning downstream vehicle trajectories and next bus arrival. The prediction generated by the proposed hybrid scheme integrates three travel time components: schedule, instantaneous and historical data. Genetic algorithm is applied in order to specify the contribution of each data source component to the prediction scheme. The benefits, transferability and estimation form of the proposed scheme were tested by applying it on three trunk bus lines in Stockholm, Sweden. Its performance was compared to a commonly deployed scheme. The results indicate that the proposed scheme reduces significantly the overall mean absolute error for all routes from both operators' and passengers' perspectives.