Bus arrival time prediction at bus stop with multiple routes

Authors

Bin Yu
William H.K. Lam
Mei Lam Tam

Document Type

Journal Article

Publication Date

2011

Subject Area

mode - bus, infrastructure - stop, technology - passenger information, technology - automatic vehicle monitoring, technology - intelligent transport systems, place - asia

Keywords

Bus arrival time prediction, Multiple bus routes, Support vector machine, Artificial neural network, k nearest neighbours algorithm

Abstract

Provision of accurate bus arrival information is vital to passengers for reducing their anxieties and waiting times at bus stop. This paper proposes models to predict bus arrival times at the same bus stop but with different routes. In the proposed models, bus running times of multiple routes are used for predicting the bus arrival time of each of these bus routes. Several methods, which include support vector machine (SVM), artificial neural network (ANN), k nearest neighbours algorithm (k-NN) and linear regression (LR), are adopted for the bus arrival time prediction. Observation surveys are conducted to collect bus running and arrival time data for validation of the proposed models. The results show that the proposed models are more accurate than the models based on the bus running times of single route. Moreover, it is found that the SVM model performs the best among the four proposed models for predicting the bus arrival times at bus stop with multiple routes.

Rights

Permission to publish the abstract has been given by Elsevier, copyright remains with them.

Comments

Transportation Research Part C Home Page:

http://www.sciencedirect.com/science/journal/0968090X

Recommended Citation

Yu, B., Lam, W.H.K., Tam, M.L. (2011). Bus arrival time prediction at bus stop with multiple routes. Transportation Research Part C: Emerging Technologies. Article in Press, Corrected Proof.