Modeling of Passing Events in Mixed Bicycle Traffic with Cellular Automata

The primary objective of this study was to use the cellular automata (CA) method to model the characteristics of bicycle passing events in mixed bicycle traffic on separated bicycle paths. The mixed traffic was composed of two types of bicycles: the conventional bicycle (c-bicycle) and the electric bicycle (e-bicycle). The number of passing events and the characteristics of mixed bicycle traffic were investigated in the field on eight physically separated bicycle paths in China. Then a CA model was calibrated with the use of the field data to simulate the passing events in the mixed bicycle traffic. The results showed that the CA model could simulate the features of bicycle passing events well. The simulation results were consistent with field observations. An increase in the ratio of e-bicycles would not significantly increase the number of passing events, but e-bicycles did contribute substantially to passing events in mixed bicycle traffic. E-bicycles were shown to have more stability than c-bicycles, especially in traffic with a high flow rate. The findings of this study could improve the performance of simulation techniques to reflect the actual characteristics of mixed bicycle traffic.