Symmetric Two-lane Cellular Automaton Model Research Articles

Multi-lane traffic flow model based on cellular automaton fine-scale under cooperative vehicle infrastructure system

Microscopic traffic flow modeling is crucial for predicting future traffic demand and optimizing the design of transportation systems. At the microscopic level, a well-crafted model is capable of describing the interactions and dynamic variations among vehicles with greater accuracy. The cell scale in the classical cellular automaton (CA) multi-lane traffic flow model is a critical parameter to accurately express the location relationship of vehicles. In this paper, a new method based on Symmetric Two-lane Cellular Automaton (STCA), entitled STCA-X, is proposed for the cell scale selection. Firstly, the position, velocity, acceleration, and interaction of vehicle operation in the urban multi-lane environment are analyzed, and a feature model is built based on CA. One important drawback of the existing models is that they do not match the vehicle movement in the actual lane. To handle this problem, a fine-scale CA multi-lane model is developed. Secondly, a new traffic flow model is created by redefining several key behaviors such as road following, lane changing, and blocking in the STCA model. The experimental results are analyzed and compared with several of the state-of-the-art methods. Analysis of the simulation results proves that STCA-X improves vehicle lane change frequency and lane utilization efficiency. However, the enhancements in the model have resulted in increased computational complexity. Consequently, future research will delve into novel approaches to boost computational efficiency, thereby propelling the progress of traffic flow modeling technology.

Investigating model and impacts of lane-changing execution process based on CA model

Lane changing is one of the basic driving behaviors and consists of lane-changing decision-making process and lane-changing execution process. However, most existing traffic simulation models focus on lane-changing decision-making process and assume that drivers complete their lane-changing behaviors instantaneously. Then these models may not reproduce the actual traffic phenomenon. Furthermore, there are several failed lane-changing behaviors, referring to that drivers may go back to the original lane during lane-changing process. And the impacts of these behaviors have not been investigated up to now. In order to characterize the lateral movement process and to investigate its impacts on traffic flow, this study puts forward a symmetric two-lane cellular automaton model with lane-changing execution (STCA-LE model). In this model, the lateral movement rules of lane changing vehicles are formulated and introduced. The results of numerical simulation indicate that there is a positive relationship between the lane-changing duration and traffic density that is consistent with observation data analysis. Based on this model, the lane-changing trajectories and impacts of lane-changing process are investigated by introducing the critical lane-changing duration. The results of this study could be taken as an important reference to the development of traffic measures and the designation of intelligent vehicles.

Dynamic model of high speed following traffic flow

For the physical phenomenon of high-speed car following in the road traffic flow, all the vehicles with small spacing do not run at low speed. The speeds of the vehicles are significantly higher than those they normally should be when they are in this vehicles’s density. There are more than 7% of high-speed following vehicles in the measured data. At present, the traditional traffic flow model cannot simulate the phenomenon of high-speed car following, so a new nonlinear dynamic mathematical model is needed to describe and analyze the physical phenomenon. In order to study the physical phenomenon of high-speed car following in road traffic, a traffic flow dynamics model for simulating the phenomena is proposed, which combines with the prospect theory and takes into account some factors such as driver’s decision-making behavior and randomization. It is called HCCA (high-speed car following celluar automat) model. In the model, the prospect theory is used to analyze the driver’s lane changing behavior under the uncertain conditions. Combined with the characteristics of the radical driver, the dynamic prediction speed is considered for the front car followed by the radical driver, and the HCCA dynamics rules of high-speed following traffic flow mechanics are defined. By the computer numerical simulation, the evolution mechanism and the characteristics of high-speed car-following flow are studied. The results show that compared with the symmetric two-lane cellular automata (STCA) dynamic model, the HCCA dynamic model established in this paper can simulate abundant traffic physical phenomena, and reproduce complex traffic phenomena such as free flow, synchronous flow and wide-range motion congestion. Finally, the phenomenon of high-speed car following is simulated and the results of high-speed car following rate over 7% with small spacing are in good agreement with the measured results. It overcomes the shortage that traditional STCA model cannot simulate the synchronous flow. It is found that the larger the proportion of radical drivers, the larger the high-speed car following rate and traffic flow with small spacing are under the same road density. The high-speed car following traffic flow mechanics model proposed in this paper has a certain reference significance and practical value for analyzing the physical phenomenon of high-speed car following and enriching the traffic flow theory.

Cellular Automaton-Based Traffic Flow Simulation Model for Traffic Incidents

AbstractTraffic incidents decrease the capacity of road segments and disturb normal traffic flow. Analyzing the evolution of traffic incident effects by building a simulation model for traffic incidents not only helps in better understanding traffic flow characteristics in abnormal conditions, but also provides a theoretical basis for traffic control strategies. Considering the characteristics of driver behavior, this study proposes an improved model of traditional symmetric two-lane cellular automaton (STCA) based on lane-changing rules. Velocity is used to build a traffic simulation cellular automaton model for traffic incident conditions. The improved model simulated traffic flow better than the traditional STCA model.

Segregation effect in symmetric cellular automata model for two-lane mixed traffic

Segregation effects commonly exist in granular mixtures with difference in size, shape or density. In mixed traffic flow, slow vehicle and fast vehicle, as two types of particles, have different desired speed. We investigate the segregation along the road in mixed traffic flow by using a symmetric two-lane cellular automata model. A parameter D, which quantifies the degree of segregation, is defined. We study the density dependency of the parameter at different randomization probability. Simulation results show that segregation is more obviously in free flow region. We argue that the overtaking maneuvers have similar effect as percolation in granular flow.

A realistic two-lane cellular automata traffic model considering aggressive lane-changing behavior of fast vehicle

In real traffic, a vehicle may perform different lane-changing behavior if its preceding vehicle is different. Fast vehicle usually has aggressive lane-changing behavior when its preceding vehicle is a slow one. In this paper, we take the factor into account and propose a new symmetric two-lane cellular automata model. It is shown that aggressive lane-changing behavior of fast vehicle can depress the plug formed by slow vehicles and improve traffic flow in mixed traffic in the intermediate density range. The simulation results also indicate that ping–pang lane-changing behavior is mainly caused by fast vehicles that are hindered by fast vehicles.

Honk effect in the two-lane cellular automaton model for traffic flow

In real traffic, when a vehicle is hindered by its preceding vehicle and simultaneously it cannot change lane, it may honk the horn. As a result, the driver of the preceding vehicle may change lane to make way for it. However, this effect has seldom been investigated before. In this paper, we take this issue into account by proposing a new symmetric two-lane cellular automaton model. It is shown that the honk has almost no effect in the homogeneous traffic whereas it enhances the flux in the intermediate density regime for the heterogeneous traffic. We suggest that this is because the occurrence probability and the lifetime of the plug are suppressed due to the introduction of the honk. Finally, we argue that the honk behavior is not encouraged in the asymmetric two-lane model.