An integrated framework to predict bus travel time and its variability using traffic flow data

Abstract

Information about bus travel time and its variability is a key indicator of service performance, and it is valued by passengers and operators. Despite the important effect of traffic flow on bus travel time, previous predictive approaches have not fully considered a traffic measure making their predictions unresponsive to the dynamic changes in traffic congestion. In addition, existing methodologies have primarily concerned predicting average travel time given a certain set of input values. However, predicting travel-time variability has not received sufficient attention in previous research. This article proposes an integrated framework to predict bus average travel time and its variability..