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Driving behavior is heterogeneous for various drivers due to the different influencing factors as reaction time, gender, driving years and so on. Some existing works tried to reproduce some of the complex characteristics of real traffic flow by taking into account the heterogeneous driving behavior, and the drivers are generally divided into two classes (including aggressive drivers and careful drivers) or three classes (including aggressive drivers, normal drivers and careful drivers). Nevertheless, the classification approaches have not been verified, and the rationality of the classifications has not been confirmed as well. In this study, the trajectory data of drivers is extracted from the NGSIM datasets. By combining the K-Means method and Silhouette measure index, the drivers are classified into four clusters (named as clusters A, B, C and D, respectively) in accordance with the acceleration and time headway. The two-dimensional approach is applied to analyze the characteristics of different clusters. Here, one dimension consists of “Cautious” and “Aggressive” behaviors in terms of velocity and acceleration, and the other dimension consists of “Sensitive” and “Insensitive” behaviors in terms of reaction time. Finally, the fuel consumption and emissions for different clusters are calculated by using the VT-Micro model. A surprising result indicates that overly “cautious” and “sensitive” behaviors may result in more fuel consumption and emissions. Therefore, it is necessary to find the balance between the driving characteristics.

To depict the mixed traffic flow consisting of motorized (m-) and non-motorized (nm-) vehicles, a new cellular automaton model is proposed by combining the NaSch model and the BCA model, and some rules are also introduced to depict the interaction between m-vehicles and nm-vehicles. By numerical simulations, the flux-density relations are investigated in detail. It can be found that the flux-density curves of m-vehicle flow can be classified into two types, corresponding to small and large density regions of nm-vehicles, respectively. In small density region of nm-vehicles, the maximum flux as well as the critical density decreases with the increase of nm-vehicle density. Similar characteristics can also be found in large density region of nm-vehicles. However, compared with the former case, the maximum flux is much lower, the phase transition from free flow to congested flow becomes continuous and thus the corresponding critical points are non-existent. The flux-density curves of nm-vehicle flow can also be classified into two types. And interestingly, the maximum flux and the corresponding density decrease first and keep constant later as the density of m-vehicle increases. Finally, the total transport capacity of the system is investigated. The results show that the maximum capacity can be reached at appropriate proportions for m-vehicles and nm-vehicles, which induces a controlling method to promote the capacity of mixed traffic flow.

Crosswalk with push button is prevalent in lots of cities for the purpose of promoting the efficiency of the crosswalk, and thus the delays of both vehicles and pedestrians can be reduced. This strategy has been confirmed to be effective in several developed countries. However, it is a pity that application of push button is aborted in some cities in China. In this work, diverse behaviors of vehicles and pedestrians are analyzed and discussed. Then, a microscopic model is developed by incorporating the interaction between vehicles and pedestrians. Numerical simulations are performed to reveal the characteristics of traffic flow and the efficiency of the signal control strategy. Also, the impacts of risker proportion and button reaction time, as well as the impacts of various behaviors as mass behavior, the patience of pedestrian and push button habit are investigated. It is expected that the results will be helpful to the strategy design of a signalized crosswalk in such developing countries as China.

In this work, a cellular automaton model is presented to depict the traffic flow at such a crosswalk with push button. The characteristics of vehicle flow with various arriving rate of pedestrians are investigated. Flux curves and spatiotemporal diagrams are plotted to show different traffic states and the phase transition features. A parameter, named as button reaction time, is introduced to represent the green time for vehicle flow after the button is pushed by a pedestrian. The effect of button reaction time on saturated flux is investigated. The results show that there is a critical value of button reaction time. The saturated flux increases rapidly when button reaction time is smaller than the critical value, while it increases slowly otherwise. Furthermore, theoretical analysis is performed and the results coincide with the simulation ones.