Research On The Game Behavior Properties Of City Traffic Flow Based On Cellular Automata Model

Recently, traffic problems have attracted much attention of a community of physi-cists because of the observed nonequilibrium phase transitions and various nonlinear dy-namical phenomena. In order to investigate the dynamical behavior of the traffic flow, a number of traffic models such as fluid dynamical models, gas-kinetic models, car-following models, map lattice models and cellular automata (CA) models have been pro-posed. These dynamical approaches represented complex physical phenomena of traffic flow among which are hysteresis, synchronization, wide moving jams, and phase tran-sitions, etc. Among these models, the advantages of CA approaches, which have been extensively applied and investigated, show the flexibility to adapt complicated features observed in real vehicular traffic. The Nagel-Schreckenberg (NaSch) model is a basic CA models describing one-lane traffic flow. Based on the NaSch model, many CA models have been extended to investigate the properties of the system with realistic traffic factors such as highway junctions, crossing, traffic lights, tollbooths and speed limit zone.Previously, scholars pay more attention to traffic flow while investigating vehicular traffic issues. Most recently, the problems of driver game behavior in traffic system have been investigated widely.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. What we present here implies that the cooperative game the-orists use may underlie a traffic flow phenomenon that is believed to be a typical physics problem.Then we investigate the probability for the occurrence of car accidents in the NS model with velocity-dependent randomization. The VDR model exhibits metastable s-tates and hysteresis effects which encountered in empirical observations. Moreover in the VDR model, the phase-separated steady states at high global densities, which consist of a macroscopic jam and a macroscopic free-flow regime coexisting simultaneously, have been found. The differences of the microscopic structure between NS and VDR mod-els may cause the diversity of the traffic accidents. On the other hand, according to the above studies, the accidents probability is directly related to traffic flow and the fraction of stopped cars, therefore the studies of the probability of the occurrence of car accidents can lead us to further understand traffic flow.Finally, we are investigating how the evolutionary game in the spatial distribution of car density affects the shape, scatter and even the existence of a macroscopic rela-tion between the average flow and vehicle density in urban networks. As data avail-ability from cities is limited, we are following a simulation-based approach to study a range of scenarios. The main contributions of this paper are the introduction of innova-tive modelling techniques, a memory traffic flow routing, and a better understanding of the urban-scale MFD. Our routing method does not require origin-destination tables and complicated routing decisions or route assignment, which are necessary in most urban micro-simulation models. In addition, by applying the flow quantization, we are able to reproduce a realistic variability of network flows even for the same average car density.