Xiao-Mei Zhao

CELLULAR AUTOMATA MODEL FOR UNSIGNALIZED T-SHAPED INTERSECTION

In this paper, the unsignalized T-shaped intersection is modeled by a cellular automata model. The main street and the minor street join at the intersection. As to the traffic flow is not controlled by traffic lights, conflict happens between the vehicles from minor street and that from main street. Two different crash avoiding rules are used to dispose the conflicts. In the first rule, the priorities are given to the driving-ahead vehicle and the vehicle on the main street. In the second rule, the vehicle that reaches the conflicting point earlier enters into the intersection. The flux on each lane depending on the inflow rates is studied in detail. The capacity of the system is also investigated. Our simulation results suggest that the two rules do not take the same effect on the capacity under different traffic conditions.

MODELING THE INTERACTION BETWEEN MOTORIZED VEHICLE AND BICYCLE BY USING CELLULAR AUTOMATA MODEL

In this paper, the cellular automata models for motorized vehicle flow and that for bicycle flow are combined to modeling the interactions between the right-turning motorized vehicle and the driving ahead bicycle at intersection. We introduce the probability that the cross point is taken up by the same kind of vehicle during two successive time steps to describe the complex behaviors when conflict happens. The flux of both motorized vehicle and bicycle depending on the inflow rates are investigated and the spatiotemporal diagrams are also presented to show different traffic states as the inflow rates change. The simulation results show that the model can describe the interactions between motorized vehicle and bicycle. It makes foundations for future research on mixed traffic flow.

Traffic Interactions between Motorized Vehicles and Nonmotorized Vehicles near a Bus Stop

This paper studies traffic features in a mixed traffic flow composed of motorized vehicles and nonmotorized vehicles near a bus stop within a completely different framework. Our work has taken the nonlane based behaviors of nonmotorized vehicles into account, which has seldom been considered in previous works. We have investigated flow rates as well as passenger transport capacity of the system. The traffic state diagram and the spatiotemporal pattern are presented as the inflow rates of motorized vehicles and nonmotorized vehicles change. A nonmonotonic change of passenger transport capacity is also identified at specific parameters. The influence of parameters such as stopped time of buses is discussed. These results are expected to shed some light on the management and design of urban mixed traffic systems.

The Effect Of Mixed Vehicles On Traffic Flow In Two Lane Cellular Automata Model

In real traffic, the traffic system is usually composed of different types of vehicles, which have different parameters. How these parameters, especially the lengths of the vehicles, influence the traffic behaviors and transportation capability has seldom been investigated. In this paper, we study the mixed traffic system using the cellular automata traffic flow model. The simulation results show that when the road occupancy rate is large, increasing the fraction of long vehicles can apparently, improve the transportation capability. The influence of slow vehicles fraction on the average velocity of vehicles has been discussed, and it is found that the influences are very different when the difference of vehicle length is considered or not.

Congestions and Spatiotemporal Patterns in a Cellular Automaton Model for Mixed Traffic Flow

This paper studies traffic features in a mixed traffic flow composed of motorized vehicles and nonmotorized vehicles near a bus stop within a completely different framework. By using cellular automaton models, our work has taken the non-lane based behaviors of nonmotorized vehicles into account, which has not been considered in previous works. We have investigated flow rates of the system. The traffic state diagram and the spatiotemporal pattern are presented as the inflow rates of motorized vehicles and nonmotorized vehicles change. Traffic interactions between motorized vehicles and nonmotorized vehicles may cause congestions in traffic flow at dense flow, but has no influence at sparse flow. These results are expected to shed some light on the management and design of urban mixed traffic systems.

Combined Cellular Automaton Model For Mixed Traffic Flow With Non-Motorized Vehicles

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.

Cellular automaton modeling of traffic flow at a crosswalk with push button

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.

Dynamic Rerouting Behavior and Its Impact on Dynamic Traffic Patterns

Advanced information is increasingly being used as an external intervention tool to positively influence system performance. In many traffic assignment problems, the proportion of travellers that reroute is assumed to be constant (static rerouting behavior), whereas the number of travellers that modify their routes will change dynamically with the cost difference (dynamic rerouting behavior). In this paper, dynamic rerouting behavior is considered in day-to-day traffic assignment models to capture travellers’ reactions to advanced information. The properties of a dynamic rerouting weight function are studied using survey data. Our goal is to better understand the dynamic evolution of network flow. In the model, the rerouting weight varies dynamically with the cost difference between travellers’ estimated and expected costs. The linear stability of the equilibrium is analyzed. Both theoretical analyses and numerical simulations indicated that dynamic rerouting behavior increases the stability domain and decreases the parameter sensitivity. Additionally, the dynamic evolution of the cost and flow near the stability boundary is studied. The results show that the dynamic rerouting behavior helps to improve the convergence speed and dampen the oscillations in the evolution process. This paper explains the influence of dynamic rerouting choice behavior on the evolution patterns of transportation networks and provides guidance for network design and management.

Modeling the impact of pedestrian behavior diversity on traffic dynamics at a crosswalk with push button

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.

EXTENDED FIBER BUNDLE MODEL FOR TRAFFIC JAMS ON SCALE-FREE NETWORKS

In this paper, we extend a fiber bundle model to study the propagation of traffic jams on scale-free networks. For the special distributions of traffic handling capacities of the links and traffic load on the nodes, the critical behavior of the jamming transition on scale-free networks is studied analytically. It is found that the links connecting to the nodes with larger degrees are more prone to suffering from traffic jams. This feature is associated with a propagation that follows a precise hierarchical dynamics. Finally, the average failure rate of the networks, which is defined as the fraction of total broken links of the network, is investigated analytically and by simulations in scale-free networks. We mainly find that, when β > γ (β and γ are the scaling exponents of the load distribution and degree distribution, respectively), there is a scaling between the average failure rate of the scale-free networks 1 - G and the network size N, 1 - G ~ N-1, independent of γ.