Carbon dioxide emission in a single-lane cellular automaton model with a series of traffic lights

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.

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.


2003 ◽  
Vol 14 (05) ◽  
pp. 539-548 ◽  
Author(s):  
DING-WEI HUANG ◽  
WEI-NENG HUANG

We study the influence of traffic lights on the traffic flow in cities. The urban traffic is simulated in the cellular automata framework. Both the deterministic and probabilistic models are discussed. The effects of speed limit and stochastic noise are analyzed. The operation of a traffic light is characterized by two parameters: signal period and phase allocation. With two traffic lights on road, one more parameter is prescribed: synchronization shift. The results of tuning these parameters are presented in the fundamental diagram. We examine the traffic flow and discuss the choice of optimized setting in different density regions.


2004 ◽  
Vol 18 (17n19) ◽  
pp. 2658-2662 ◽  
Author(s):  
HUILI TAN ◽  
CHAOYING ZHANG ◽  
LINGJIANG KONG ◽  
MUREN LIU

A cellular automaton model with open boundary condition for a crossroad system controlled by a traffic light is presented. The traffic flow and speed of the first part of the road are quite different from those of the second part behind the crossing. The impact of turning probabilities and the cycle times of traffic light on the flow are investigated.


2014 ◽  
Vol 12 (1) ◽  
Author(s):  
Tracy Finner ◽  
Matthew Beauregard

A cellular automaton model is proposed, modeling vehicular traffic flow on a two dimensional lattice in which the vehicles turn at an intersection with a given probability. It is shown that the introduction of turning reduces the long-term average velocity, and can be predicted by a power law depending on the probability of a vehicle turning and the density of cars. The reduction in speed decreases rapidly once the light cycle length surpasses a certain threshold, the value of which can be predicted from the observed power law. Keywords: cellular automaton, traffic flow, traffic light strategy, turning, dynamical systems, power law


2009 ◽  
Vol 20 (05) ◽  
pp. 711-719 ◽  
Author(s):  
C. Q. MEI ◽  
H. J. HUANG ◽  
T. Q. TANG

We present a modified cellular automaton model to study the traffic flow on a signal controlled ring road with velocity guidance. The velocity guidance is such a strategy that when vehicles approach the traffic light, suggested velocities are provided for avoiding the vehicles' sharp brakes in front of red light. Simulation results show that this strategy may significantly reduce the vehicles' stopping rate and the effect size is dependent upon the traffic density, the detector position, the signal's cycle time and the obedience rate of vehicles to the guidance.


2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Yingdong Liu

A one-dimensional cellular automaton traffic flow model, which considers the deceleration in advance, is addressed in this paper. The model reflects the situation in the real traffic that drivers usually adjust the current velocity by forecasting its velocities in a short time of future, in order to avoid the sharp deceleration. The fundamental diagram obtained by simulation shows the ability of this model to capture the essential features of traffic flow, for example, synchronized flow, meta-stable state, and phase separation at the high density. Contrasting with the simulation results of the VE model, this model shows a higher maximum flux closer to the measured data, more stability, more efficient dissolving blockage, lower vehicle deceleration, and more reasonable distribution of vehicles. The results indicate that advanced deceleration has an important impact on traffic flow, and this model has some practical significance as the result matching to the actual situation.


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