A cellular automata traffic flow model for three-phase theory

Qian, Yongsheng; Xiao, Feng; Zeng, Junwei

doi:10.1016/j.physa.2017.02.057

Cited by 60 publications

(17 citation statements)

References 64 publications

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“…Although the above problems can be solved to a certain extent by further subdividing the road sections, this approach can obtain approximately continuous data at the cost of consuming massive computing power, which makes the approach not suitable for the simulation of the large-scale transportation system. To solve these problems, Yeldan et al [60][61][62][63][64][65] defined the vehicles as cellular instead of road sections and proposed the continuous CA model (as shown in Figure 2) for simulating traffic flow.…”

Section: Simulation Frameworkmentioning

confidence: 99%

“…Future Internet 2021, 13, x FOR PEER REVIEW 5 of 17 cost of consuming massive computing power, which makes the approach not suitable for the simulation of the large-scale transportation system. To solve these problems, Yeldan et al [60][61][62][63][64][65] defined the vehicles as cellular instead of road sections and proposed the continuous CA model (as shown in Figure 2) for simulating traffic flow. In the continuous CA model, the vehicles are defined as cellular, and their motion is regarded as the evolution of cellular states, which enables the model to output data continuous on the time scale.…”

Section: Simulation Frameworkmentioning

confidence: 99%

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Research on the Impacts of Generalized Preceding Vehicle Information on Traffic Flow in V2X Environment

et al. 2021

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With the application of vehicles to everything (V2X) technologies, drivers can obtain massive traffic information and adjust their car-following behavior according to the information. The macro-characteristics of traffic flow are essentially the overall expression of the micro-behavior of drivers. There are some shortcomings in the previous researches on traffic flow in the V2X environment, which result in difficulties to employ the related models or methods in exploring the characteristics of traffic flow affected by the information of generalized preceding vehicles (GPV). Aiming at this, a simulation framework based on the car-following model and the cellular automata (CA) is proposed in this work, then the traffic flow affected by the information of GPV is simulated and analyzed utilizing this framework. The research results suggest that the traffic flow, which is affected by the information of GPV in the V2X environment, would operate with a higher value of velocity, volume as well as jamming density and can maintain the free flow state with a much higher density of vehicles. The simulation framework constructed in this work can provide a reference for further research on the characteristics of traffic flow affected by various information in the V2X environment.

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Section: Simulation Frameworkmentioning

confidence: 99%

Section: Simulation Frameworkmentioning

confidence: 99%

Research on the Impacts of Generalized Preceding Vehicle Information on Traffic Flow in V2X Environment

et al. 2021

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“…This approach is already widely used in many computer simulations fields, be it in the natural sciences or humanities, such as biology, computer science, physics, transportation, the military, human behaviour etc. It is an essential approach to analyse and understand traffic-flow dynamics and has received significant research attention [16][17][18][19][20][21][22][23]. Some classical CA models have been proposed, such as 184 models [22], the Nagel-Schreckenberg (NS) model [24] and its transformation, the Biham-Middleton-Levine (BML) model [25], velocity-dependent randomization model [16], and velocity effect model [26].…”

Section: Cellular Automatamentioning

confidence: 99%

Simulation Analysis of Robotic Mobile Fulfilment System Based on Cellular Automata

Li¹,

Liu²,

Yang³

2021

Int. j. simul. model.

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This paper analyses the picking performance of a robotic mobile fulfilment system (RMFS) and proposes a Simulation Framework of RMFS based on cellular automata (SFRMFSCA). Many previous RMFS simulation platforms stipulate all aisles to be set up in a fixed directional road network for oneway lines. The warehouse robot had to travel an unnecessarily long distance to perform tasks. We relax the one-way constraint on aisles and cross aisles in the warehouse and allocate the right of way among the warehouse aisles and cross-aisles intersection by referring the idea of traffic light and traffic flow control to the RMFS warehouse scenario. To improve the efficiency of RMFS order picking, this paper designs a comprehensive strategy combining adaptive traffic light update rule, deadlock detection and recovery algorithm, and traffic control to improve the traffic flow of the system. A series of numerical experiments show that the comprehensive strategy designed in this paper can effectively improve the order picking efficiency of RMFS and reduce the probability of scale deadlock. These results and strategies provide a useful reference for designers who initially set up the RMFS warehouse.

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“…For example, a classic carfollowing model named Kerner-Klenov model [18] has complicated update rule of vehicle motion to reproduce the theory from the view of traffic physics rather than human factors. Most cellular automata models [46,47] intend to avoid crash by incorporating rigid safety conditions into the models, which deviates from real driving behavior especially for safety evaluation. en, this study proposes a new model by introducing typical human factors that are able to explore the relationship between rear-end crash and driver behavior.…”

Section: Car-following Modelmentioning

confidence: 99%

Simulation Study of Rear-End Crash Evaluation considering Driver Experience Heterogeneity in the Framework of Three-Phase Traffic Theory

Xiao

et al. 2021

Journal of Advanced Transportation

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Driving safety is considered to have a strong relationship with traffic flow characteristics. However, very few studies have addressed the safety impacts in the three-phase traffic theory that has been demonstrated to be an advancement in explaining the empirical features of traffic flow. Another important issue affecting safety is driver experience heterogeneity, especially in developing countries experiencing a dramatic growth in the number of novice drivers. Thus, the primary objective of the current study is to develop a microsimulation environment for evaluating safety performance considering the presence of novice drivers in the framework of three-phase theory. First, a car-following model is developed by incorporating human physiological factors into the classical Intelligent Driver Model (IDM). Moreover, a surrogate safety measure based on the integration concept is modified to evaluate rear-end crashes in terms of probability and severity simultaneously. Based on a vehicle-mounted experiment, the field data of car-following behavior are collected by dividing the subjects into a novice group and an experienced group. These data are used to calibrate the proposed car-following model to explain driver experience heterogeneity. The results indicate that our simulation environment is capable of reproducing the three-phase theory, and the changes in the modified surrogate safety measure are highly correlated with traffic phases. We also discover that the presence of novice drivers leads to different safety performance outcomes across various traffic phases. The effect of driver experience heterogeneity is found to increase the probability of the rear-end crashes as well as the corresponding severity. The results of this study are expected to provide a scientific understanding of the mechanisms of crash occurrences and to provide application suggestions for improving traffic safety performance.

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A cellular automata traffic flow model for three-phase theory

Cited by 60 publications

References 64 publications

Research on the Impacts of Generalized Preceding Vehicle Information on Traffic Flow in V2X Environment

Research on the Impacts of Generalized Preceding Vehicle Information on Traffic Flow in V2X Environment

Simulation Analysis of Robotic Mobile Fulfilment System Based on Cellular Automata

Simulation Study of Rear-End Crash Evaluation considering Driver Experience Heterogeneity in the Framework of Three-Phase Traffic Theory

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