A REALISTIC TWO-LANE CELLULAR AUTOMATON MODEL FOR TRAFFIC FLOW

2004 ◽  
Vol 15 (03) ◽  
pp. 381-392 ◽  
Author(s):  
BIN JIA ◽  
RUI JIANG ◽  
QING-SONG WU

This paper extends a recently proposed single-lane cellular automaton model [Li et al., Phys. Rev. E64, 066128 (2001)], which considers the velocity effect of the preceding car, to two-lane traffic system. The traffic behaviors in both homogeneous system and inhomogeneous system are investigated. For homogeneous traffic, it is shown that the velocity effect enhances the maximum flux but does not change the qualitative properties of the fundamental diagram. Nevertheless, the qualitative changes of the lane changing frequency and congested pattern occur. In the inhomogeneous system, the honk effect is studied. It is found that the honk effect first strengthens then weakens with the increase of R, the ratio of slow cars to all cars.

2007 ◽  
Vol 18 (02) ◽  
pp. 267-279 ◽  
Author(s):  
YAO-MING YUAN ◽  
RUI JIANG ◽  
QING-SONG WU ◽  
RUILI WANG

This paper extends a cellular automaton model, named modified comfortable driving (MCD) model, to a two-lane roadway. A symmetric lane-changing rule set has been proposed (Set I). The fundamental diagram, the lane-changing frequency and space-time plots are presented. It is found that for the two-lane model, there exists a density range in which phase separation between synchronized flow and wide-moving jams on one lane, and between light synchronized flow and heavy synchronized flow on the other lane, can be maintained for quite long periods of time. In this density range, (i) the outflow from jams is synchronized flow; (ii) wide moving jams are sparse. These are consistent with the empirical observation. We also investigate a slightly different lane-changing rule Set II in which stopped vehicles are not allowed to change lane. It is shown that in this case, the phase separation, between free flow and wide moving jams on one lane and between free flow and heavy synchronized flow on the other lane, can be maintained for sufficiently long periods of time. Consequently, the flux is enhanced comparing to that of rule Set I.


2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Jiawen Wang ◽  
Shaobo Li ◽  
Yining Lu ◽  
Lubang Wang

Using a cellular automaton model, this paper studied the evolution mechanism of traffic incidents affecting the capacity of urban expressway under the mixed traffic environment of manual driving and automatic driving. It showed that the length of the automated-driving early-warning zone could affect the capacity of expressway. Specifically, the early-warning zone is divided into an accelerate lane-changing area, a decelerate lane-changing area, and a forced lane-changing area. The areas vary according to the distance between the vehicle and the location of incident. Based on the study, this paper establishes a codirectional two-lane cellular automaton model. The analysis showed that the capacity of the urban expressway varies under different combinations of early-warning area length and division ratio of early-warning zone. In the case of two-lane reduction caused by traffic incidents, the capacity of the expressway is optimized when the length of early-warning zone is between 450 and 600 m, and the ratio of accelerate zone, decelerate zone, and forced zone to the length of early-warning zone is, respectively, 75%, 10%, and 15%. In addition, this study showed that the capacity will rise with the increase in automated vehicles.


2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xu Qu ◽  
Mofeng Yang ◽  
Fan Yang ◽  
Bin Ran ◽  
Linchao Li

Traffic flow models are of vital significance to study the traffic system and reproduce typical traffic phenomena. In the process of establishing traffic flow models, human factors need to be considered particularly to enhance the performance of the models. Accordingly, a series of car-following models and cellular automaton models were proposed based on comprehensive consideration of various driving behaviors. Based on the comfortable driving (CD) model, this paper innovatively proposed an improved cellular automaton model incorporating impaired driver’s radical feature (RF). The impaired driver’s radical feature was added to the model with respect to three aspects, that is, desired speed, car-following behavior, and braking behavior. Empirical data obtained from a highway segment was used to initialize impaired driver’s radical feature distribution and calibrate the proposed model. Then, numerical simulations validated that the proposed improved model can well reproduce the traffic phenomena, as shown by the fundamental diagram and space-time diagram. Also, in low-density state, it can be found that the RF model is superior to the CD model in simulating the speed difference characteristics, where the average speed difference of adjacent vehicles for RF model is more consistent with reality. The result also discussed the potential impact of impaired drivers on rear-end collisions. It should be noted that this study is an early stage work to evaluate the existence of impaired driving behavior.


2017 ◽  
Vol 28 (05) ◽  
pp. 1750059 ◽  
Author(s):  
Zhijian Fu ◽  
Liang Xia ◽  
Hongtai Yang ◽  
Xiaobo Liu ◽  
Jian Ma ◽  
...  

Properties of pedestrian may change along the moving path, for example, as a result of fatigue or injury, which has never been properly investigated in the past research. The paper attempts to study tactical overtaking in pedestrian flow. That is difficult to be modeled using a microscopic discrete model because of the complexity of the detailed overtaking behavior, and crossing/overlaps of pedestrian routes. Thus, a multi-velocity floor field cellular automaton model explaining the detailed psychical process of overtaking decision was proposed. Pedestrian can be either in normal state or in tactical overtaking state. Without tactical decision, pedestrians in normal state are driven by the floor field. Pedestrians make their tactical overtaking decisions by evaluating the walking environment around the overtaking route (the average velocity and density around the route, visual field of pedestrian) and obstructing conditions (the distance and velocity difference between the overtaking pedestrian and the obstructing pedestrian). The effects of tactical overtaking ratio, free velocity dispersion, and visual range on fundamental diagram, conflict density, and successful overtaking ratio were explored. Besides, the sensitivity analysis of the route factor relative intensity was performed.


2020 ◽  
Vol 31 (11) ◽  
pp. 2050154
Author(s):  
H. Binoua ◽  
H. Ez-Zahraouy ◽  
A. Khallouk ◽  
N. Lakouari

In this paper, we propose a cellular automaton model to simulate traffic flow controlled by a series of traffic lights. The synchronized traffic light and the green wave light strategies were investigated. The spatiotemporal diagrams, energy dissipation, and CO2 emission of the system were presented. Our simulations are conducted to clarify the difference between both strategies and their effects on the traffic flow and the CO2 emission. We found that the traffic flow depends mainly on the strategy used for managing the traffic lights as well as on the parameters of the traffic lights, namely the cycle length, the number of traffic lights and the length of the system. The fundamental diagram has barely the same characteristics for both methods and it depends on the combination of the parameters of the system. We find that the green wave is more convenient for the management of a series of traffic lights than the synchronized control strategy in terms of throughput, especially for large-sized systems. Unlike in terms of CO2 emission and energy dissipation, both control strategies outperform each other depending on the density regions and the parameters of the system. Finally, we investigate the effect of both cycles (i.e. red and green) for the synchronized control method on the CO2 emission. It is found that the green cycle generates often a series of acceleration events that increase CO2 emission.


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