Dynamic Cellular Automata Model Research Articles

Measuring Dynamics in Evacuation Behaviour with Deep Learning.

Bounded rationality is one crucial component in human behaviours. It plays a key role in the typical collective behaviour of evacuation, in which heterogeneous information can lead to deviations from optimal choices. In this study, we propose a framework of deep learning to extract a key dynamical parameter that drives crowd evacuation behaviour in a cellular automaton (CA) model. On simulation data sets of a replica dynamic CA model, trained deep convolution neural networks (CNNs) can accurately predict dynamics from multiple frames of images. The dynamical parameter could be regarded as a factor describing the optimality of path-choosing decisions in evacuation behaviour. In addition, it should be noted that the performance of this method is robust to incomplete images, in which the information loss caused by cutting images does not hinder the feasibility of the method. Moreover, this framework provides us with a platform to quantitatively measure the optimal strategy in evacuation, and this approach can be extended to other well-designed crowd behaviour experiments.

Dynamic route guidance strategy in a two-route pedestrian-vehicle mixed traffic flow system

With the rapid development of transportation, traffic questions have become the major issue for social, economic and environmental aspects. Especially, during serious emergencies, it is very important to alleviate road traffic congestion and improve the efficiency of evacuation to reduce casualties, and addressing these problems has been a major task for the agencies responsible in recent decades. Advanced road guidance strategies have been developed for homogeneous traffic flows, or to reduce traffic congestion and enhance the road capacity in a symmetric two-route scenario. However, feedback strategies have rarely been considered for pedestrian-vehicle mixed traffic flows with variable velocities and sizes in an asymmetric multi-route traffic system, which is a common phenomenon in many developing countries. In this study, we propose a weighted road occupancy feedback strategy (WROFS) for pedestrian-vehicle mixed traffic flows, which considers the system equilibrium to ease traffic congestion. In order to more realistic simulating the behavior of mixed traffic objects, the paper adopted a refined and dynamic cellular automaton model (RDPV_CA model) as the update mechanism for pedestrian-vehicle mixed traffic flow. Moreover, a bounded rational threshold control was introduced into the feedback strategy to avoid some negative effect of delayed information and reduce. Based on comparisons with the two previously proposed strategies, the simulation results obtained in a pedestrian-vehicle traffic flow scenario demonstrated that the proposed strategy with a bounded rational threshold was more effective and system equilibrium, system stability were reached.

A refined and dynamic cellular automaton model for pedestrian–vehicle mixed traffic flow

Mixed traffic flow sharing the “same lane” and having no discipline on road is a common phenomenon in the developing countries. For example, motorized vehicles (m-vehicles) and nonmotorized vehicles (nm-vehicles) may share the m-vehicle lane or nm-vehicle lane and pedestrians may share the nm-vehicle lane. Simulating pedestrian-vehicle mixed traffic flow consisting of three kinds of traffic objects: m-vehicles, nm-vehicles and pedestrians, can be a challenge because there are some erratic drivers or pedestrians who fail to follow the lane disciplines. In the paper, we investigate various moving and interactive behavior associated with mixed traffic flow, such as lateral drift including illegal lane-changing and transverse crossing different lanes, overtaking and forward movement, and propose some new moving and interactive rules for pedestrian–vehicle mixed traffic flow based on a refined and dynamic cellular automaton (CA) model. Simulation results indicate that the proposed model can be used to investigate the traffic flow characteristic in a mixed traffic flow system and corresponding complicated traffic problems, such as, the moving characteristics of different traffic objects, interaction phenomenon between different traffic objects, traffic jam, traffic conflict, etc., which are consistent with the actual mixed traffic system. Therefore, the proposed model provides a solid foundation for the management, planning and evacuation of the mixed traffic flow.

A dynamic cellular automaton model for evacuation process with obstacles

A dynamic cellular automaton (CA) model is proposed to simulate the evacuation process in the rooms with obstacles. Besides the basic parameters such as human psychology, placement of the doors, doors width, position of the obstacles and light of the environment, distribution of the crowd plays an important role in this model. Applying our model, simulation of the evacuation process for a restaurant and a classroom are presented. Also effects of pedestrians distribution, doors position and doors width on the evacuation time are discussed and the obtained results are compared with several static models.

Numerical study on photoresist etching processes based on a cellular automata model

For the three-dimensional (3-D) numerical study of photoresist etching processes, the 2-D dynamic cellular automata (CA) model has been successfully extended to a 3-D dynamic CA model. Only the boundary cells will be processed in the 3-D dynamic CA model and the structure of “if-else” description in the simulation program is avoided to speed up the simulation. The 3-D dynamic CA model has found to be stable, fast and accurate for the numerical study of photoresist etching processes. The exposure simulation, post-exposure bake (PEB) simulation and etching simulation are integrated together to further investigate the performances of the CA model. Simulation results have been compared with the available experimental results and the simulations show good agreement with the available experiments.

A Novel 3-D Dynamic Cellular Automata Model for Photoresist-Etching Process Simulation

A novel three-dimensional (3-D) dynamic cellular automata (CA) model is presented for a photoresist-etching process simulation (photoresist-dissolution simulation and development simulation). In the 3-D dynamic CA model, the Moore neighborhood is adopted, and the boundary cells are only processed by using a boundary cell array, a corresponding linked list of pointers to the boundary cells, and a state flag to indicate the relations between the cells and the etching boundary. A time-compensation method is also introduced to speed up the photoresist-etching simulation. Therefore, the simulation speed is greatly increased compared with that of the static 3-D CA model, and the preferential etch in different directions reported in cell-removal models is significantly reduced. The 3-D dynamic CA model was successfully tested using some well-known etch-rate distribution test functions and has been shown to be stable, accurate, and fast. Exposure simulation, post-exposure bake simulation, and photoresist-etching simulation have been successfully integrated together to further study the effectiveness of the 3-D dynamic CA model. Simulation results show an agreement with available experimental results

A novel 2D dynamic cellular automata model for photoresist etching process simulation

A novel two-dimensional (2D) dynamic cellular automata (CA) model is presented for photoresist etching process simulation. The speed of the dynamic CA model increases by over ten times compared with the 2D static CA model. At the same time, the simulation accuracy is also increased in this model. The dynamic CA model has been successfully tested using some well-known etch-rate distribution test functions and is demonstrated to be stable even in areas where the fluctuation in etch rates is very sharp.

A Cellular Automata Model of Acid Dissociation

A dynamic cellular automata model that simulates the dissociation of an organic acid in solution is described. In the model, acids are represented by a novel cell type in which one face corresponds to the dissociating carboxylic acid group and the remaining faces represent the anionic portion of the acid. Simulations are described that analyze the effects of variable acid strength, changes of solvent temperature, and environmental influences, such as the presence of cosolutes and other acids. Several general features of acid dissociation in solution are replicated by the model and some additional aspects are examined. As a rule, additional solutes depress acid dissociation, the effect being greatest when the added cosolute is lipophilic, as might occur, for example, in a biological system. In mixtures of two different acids, the dissociation of each is suppressed, the weaker acid experiencing the greater suppression.