We use cellular automata model to study the cooperation between cyclists. In the two-lane model, cyclists can change lanes. Even there is someone on the back they will take a cooperative attitude. It means that they will be in a same lattice. Simulation carried out under the open borders. Simulation results show that the density in a certain area appeared surge. When the (or) is constant and (or) changes in isometric, the distance between the curves are getting closer. If and close to the limit 1 or 0, a dramatic change has been observed in density profile.
The automobile is a means of transportation, indispensable in daily life. However, in developing countries, e.g. China, India, Bangladesh and Indonesia [1], m-vehicles come in increasing numbers, and simultaneously no motorized vehicles (thereafter nm-vehicle, including bicycle, three-wheeler, motorcycle) are still prevalent for most short-distance trips due to low income levels or convenient parking.
Modeling road traffic behavior using cellular automata (CA) has become a well-established method to model, analyze, understand, and even forecast the behavior of real road traffic, because the automata’s evolution rules are simple, straightforward to understand, computationally efficient and sufficient to emulate much of the behavior of observed traffic flow [2]. The asymmetric simple exclusion process is one of these models. It has acquired paradigmatic status for several reasons: first, with open boundaries, it shows highly nontrivial behaviors such as distinct phases, shocks, and long-range correlations in both space and time; second, in its simplest forms, its steady-state properties, as well as selected dynamic quantities, can be found exactly; and finally, the model is closely related to applications of traffic flow [3].
Despite findings from previous studies, one important point has been missing, which is the decision-making process of drivers, which unequivocally affects traffic flows. Owing to this background, Yamauchi et al. [4] developed a framework integrating a traffic flow model with game theory. And Nakata et al. [5] observe a dilemma structure in the metastable phase by using the stochastic Nishinari-Fukui-Schadschneider (S-NFS) [6] model instead of SOV. Beyond those backgrounds, the objectives of this paper are to add a cooperative game theory framework as a rational decision process to the two-lane bicycle traffic model, construct a new CA model.
The model is defined in a two-lane lattice of L×2 sites, where L is the length of a lane. The occupation variable is
means that the state of the i th site in lane A or B is occupied or vacant. Following dynamical rules was applied. a chiyu_wang@yahoo.cn b lhwang@gxnu.edu.cn c crh@gxnu.edu.cn We carry out the simulations on the lane of length L=400. The first 10 000 steps are discarded to let the transient time die out. The following 2 000 steps are used for averaging.
Note that the model is different from the model of Jiang et al [7] and the model of Pronina and Kolomeisky [8], in which the particles change lane but not overlap. This difference leads to different results.
In this section, we study the situation arising from preference for the right line, in which the lane changing rates A. Phase and density profile Figure 1 shows the typical density profiles in the different conditions. According to our simulation, there are three kinds of state. The first, like (a), belong to free-flow phase that two lanes have the same density except that a sharp increase in the density of two-lane in the exit, and at this time, the right lane density is greater than the left one. When On the other word, in the exit of left lanes, the curves never intersect each other and arrange in descending order of β with it increasing. The right picture in Figure 2 indicate that right lanes have witnessed phase change from jam phase to metastable phase and then from metastable phase to free-flow phase with the value of β increasing. The curves also never intersect each other and arrange in descending order of β with it increasing.
Figure 3 shows the 100 times average overall density profile in the left lane and right lane for the change of α , while the β is constant. The left picture in Figure 3 indicate that right lanes have witnessed phase change from free-flow phase to metastable phase and then from metastable phase to jam phase the value of α increasing. The curves never intersect each other and arrange in ascending order of α with it increasing. The right picture indicate that in left lanes the density is constant except that a slightly increase in the density of lane in the exit in the various value ofα . On the other word, in the exit of left lanes, the curves never intersect each other and arrange in ascending order of α with it increasing. And the distance between the two curves are getting closer, from bottom to top. From Figure 2 and Figure 3, we can see that in the experiment when theα (or β ) is constant and β (or α ) changes in isometric, the distance the two curves show the density changes regularity. When theα is constant and β changes in isometric, the distance between the curves are getting closer, from top to bottom in the right lane. When the β is constant and α changes in isometric, the distance between the curves are getting closer, from bottom to top in the right lane; in the left lane the distance between the curves are getting closer, from bottom to top ,it just like spectral lines of hydrogen atoms. Figure 4 further study of this phenomenon ne
This content is AI-processed based on open access ArXiv data.
