Improving the quality of service in public road transportation using real time travel information system

The impact of road public transport in urban transportation cannot be ignored, however, the quality of services provided is not high enough. This has made it unattractive to prospective passengers and less competitive to private transport. One of the ways of resolving these challenges with a view to increasing the quality of service is by the provision of platforms that provides travel information in real time to prospective users. This was achieved in this paper using web, mobile, and short messaging service platforms. The developed platforms employed an artificial neural network-based bus arrival time prediction model for predicting bus arrival time. The accuracy of the prediction model was evaluated using mean absolute error and mean absolute percentage error while the performance and impact of the developed platforms were assessed from users' perspective through a survey based on the unified theory of acceptance and use of technology (UTAUT) model.