Bus Dwell Time Estimation and Prediction: A Study Case in Shanghai-China

Since dwell time usually takes a large part of bus travel time, the large variability in dwell time always makes accurate prediction of arrival time\travel time difficult. On the other hand, Automatic Vehicle Location (AVL) and Automatic Passengers Counters (APC) systems are increasingly implemented for transit operation, which yield a vast amount of real time data. The emphasis of this research is to develop a bus dwell time model based on AVL and APC dynamic data, which is capable of providing real time information on bus arrival times. This model can be used for stop-based control strategies as well. The dwell time model established in this paper not only includes the number of passengers boarding and alighting, but also considers secondary factors like crowding and fare type. The number of boarding and alighting passengers is estimated by passenger arrival rate, bus headway, and capacity. Collection method, service mode, capacity restriction and occupancy of the vehicle are all taken into account in the model. Furthermore, the model is validated with the data of bus line Jiading 3 in Shanghai, China. It is compared with two previously developed models for the same route in four data sets. The results indicate that the models can be well applied in high demanded urban bus lines, especially in presence of high occupancy of vehicles. Since the effectiveness of estimation models is verified by statistical analysis methods, it will help in obtaining a reliable algorithm which can be adopted for bus arrival time/travel time prediction and assessing transit stop-based dynamic control actions. (C) 2013 The Authors. Published by Elsevier Ltd.