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Discrete Dynamics in Nature and Society
Volume 2015, Article ID 213204, 11 pages
Research Article

A Modified Cellular Automaton Approach for Mixed Bicycle Traffic Flow Modeling

1Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai 201804, China
2School of Transportation, Southeast University, 2 Sipailou, Nanjing 210096, China

Received 19 March 2015; Accepted 25 June 2015

Academic Editor: Gabriella Bretti

Copyright © 2015 Xiaonian Shan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Several previous studies have used the Cellular Automaton (CA) for the modeling of bicycle traffic flow. However, previous CA models have several limitations, resulting in differences between the simulated and the observed traffic flow features. The primary objective of this study is to propose a modified CA model for simulating the characteristics of mixed bicycle traffic flow. Field data were collected on physically separated bicycle path in Shanghai, China, and were used to calibrate the CA model using the genetic algorithm. Traffic flow features between simulations of several CA models and field observations were compared. The results showed that our modified CA model produced more accurate simulation for the fundamental diagram and the passing events in mixed bicycle traffic flow. Based on our model, the bicycle traffic flow features, including the fundamental diagram, the number of passing events, and the number of lane changes, were analyzed. We also analyzed the traffic flow features with different traffic densities, traffic components on different travel lanes. Results of the study can provide important information for understanding and simulating the operations of mixed bicycle traffic flow.