A two-lane cellular automaton traffic flow model with the influence of driver, vehicle and road

On the basis of one-lane comfortable driving model, this paper established a two-lane traffic cellular automata model, which improves the slow randomization effected by brake light. Considering the driver psychological characteristics and mixed traffic, we studied the lateral influence between vehicles on adjacent lanes. Through computer simulation, the space-time diagram and the fundamental figure under different conditions are obtained. The study found that aggressive driver makes a slight congestion in low-density traffic and improves the capacity of high-density traffic, when the density exceeds 20[Formula: see text]pcu/km the more aggressive drivers the greater the flow, when the density below 40[Formula: see text]pcu/km driver character makes an effect, the more cautious driver, the lower the flow. The ratio of big cars has the same effect as the ratio of aggressive drivers. Brake lights have the greatest impact on traffic flow and when the density exceeds 10[Formula: see text]pcu/km the traffic flow fluctuates. Under periodic boundary conditions, the disturbance of road length on traffic is minimal. The lateral influence only play a limited role in the medium-density conditions, and only affect the average speed of traffic at low density.

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THE EFFECT OF MIXED VEHICLES ON TRAFFIC FLOW IN TWO LANE CELLULAR AUTOMATA MODEL

International Journal of Modern Physics C ◽

10.1142/s0129183105008199 ◽

2005 ◽

Vol 16 (10) ◽

pp. 1617-1627 ◽

Cited By ~ 17

Author(s):

BIN JIA ◽

RUI JIANG ◽

ZI-YOU GAO ◽

XIAO-MEI ZHAO

Keyword(s):

Cellular Automata ◽

Traffic Flow ◽

Flow Model ◽

Mixed Traffic ◽

Cellular Automata Model ◽

Traffic System ◽

The Road ◽

Different Types ◽

The Difference ◽

Real Traffic

In real traffic, the traffic system is usually composed of different types of vehicles, which have different parameters. How these parameters, especially the lengths of the vehicles, influence the traffic behaviors and transportation capability has seldom been investigated. In this paper, we study the mixed traffic system using the cellular automata traffic flow model. The simulation results show that when the road occupancy rate is large, increasing the fraction of long vehicles can apparently, improve the transportation capability. The influence of slow vehicles fraction on the average velocity of vehicles has been discussed, and it is found that the influences are very different when the difference of vehicle length is considered or not.

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A cellular automata model for mixed traffic flow considering the driving behavior of connected automated vehicle platoons

Physica A Statistical Mechanics and its Applications ◽

10.1016/j.physa.2021.126262 ◽

2021 ◽

pp. 126262

Author(s):

Yangsheng Jiang ◽

Sicheng Wang ◽

Zhihong Yao ◽

Bin Zhao ◽

Yi Wang

Keyword(s):

Cellular Automata ◽

Traffic Flow ◽

Driving Behavior ◽

Mixed Traffic ◽

Cellular Automata Model ◽

Mixed Traffic Flow ◽

Automated Vehicle ◽

Vehicle Platoons

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Research on Mandatory Lane-Changing Behavior in Highway Weaving Sections

Journal of Advanced Transportation ◽

10.1155/2020/3754062 ◽

2020 ◽

Vol 2020 ◽

pp. 1-9 ◽

Cited By ~ 2

Author(s):

Wei Hao ◽

Zhaolei Zhang ◽

Zhibo Gao ◽

Kefu Yi ◽

Li Liu ◽

...

Keyword(s):

Traffic Flow ◽

Traffic Accidents ◽

Driving Behavior ◽

Heterogeneous Traffic ◽

Psychological Characteristics ◽

Distribution Characteristics ◽

Mixed Traffic ◽

Lane Changing ◽

Headway Distribution ◽

Analysis Models

As the accident-prone sections and bottlenecks, highway weaving sections will become more complicated when it comes to the mixed-traffic environments with connected and automated vehicles (CAVs) and human-driven vehicles (HVs). In order to make CAVs accurately identify the driving behavior of manual-human vehicles to avoid traffic accidents caused by lane changing, it is necessary to analyze the characteristics of the mandatory lane-changing (MCL) process in the weaving area. An analytical MCL method based on the driver’s psychological characteristics is proposed in this study. Firstly, the driver’s MLC pressure concept was proposed by leading in the distance of the off-ramp. Then, the lane-changing intention was quantified by considering the driver’s MLC pressure and tendentiousness. Finally, based on the lane-changing intention and the headway distribution of the target lane, an MLC positions probability density model was proposed to describe the distribution characteristics of the lane-changing position. Through the NGSIM data verification, the lane-changing analysis models can objectively describe the vehicle lane-changing characteristics in the actual scenarios. Compared with the traditional lane-changing model, the proposed models are more interpretable and in line with the driving intention. The results show significant improvements in the lane-changing safe recognition of CAVs in heterogeneous traffic flow (both CAVs and HVs) in the future.

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Macroscopic Model and Its Numerical Solution for Two-Flow Mixed Traffic with Different Speeds and Lengths

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1852-26 ◽

2003 ◽

Vol 1852 (1) ◽

pp. 209-219 ◽

Cited By ~ 52

Author(s):

Stéphane Chanut ◽

Christine Buisson

Keyword(s):

Traffic Flow ◽

Flow Model ◽

Macroscopic Model ◽

Model Output ◽

Mixed Traffic ◽

Traffic Flow Model ◽

Hyperbolic Conservation ◽

Flux Function ◽

First Order ◽

Proposed Model

A new first-order traffic flow model is introduced that takes into account the fact that various types of vehicles use the roads simultaneously, particularly cars and trucks. The main improvement this model has to offer is that vehicles are differentiated not only by their lengths but also by their speeds in a free-flow regime. Indeed, trucks on European roads are characterized by a lower speed than that of cars. A system of hyperbolic conservation equations is defined. In this system the flux function giving the flow of heavy and light vehicles depends on total and partial densities. This problem is partly solved in the Riemann case in order to establish a Godunov discretization. Some model output is shown stressing that speed differences between the two types of vehicles and congestion propagation are sufficiently reproduced. The limits of the proposed model are highlighted, and potential avenues of research in this domain are suggested.

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Two Dimensional Cellular Automaton Model of the Mixed Traffic Flow for Urban Traffic

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.241-244.2082 ◽

2012 ◽

Vol 241-244 ◽

pp. 2082-2087

Author(s):

Li Yang ◽

Jun Hui Hu ◽

Ling Jiang Kong

Keyword(s):

Boundary Conditions ◽

Cellular Automaton ◽

Traffic Flow ◽

Flow Model ◽

Urban Traffic ◽

Mixed Traffic ◽

Traffic Flow Model ◽

Traffic Lights ◽

Mixed Traffic Flow ◽

Transit Traffic

Based on the two-dimension cellular automaton traffic flow model (BML model), a mixed traffic flow model for urban traffic considering the transit traffic is established in this paper. Under the don't block the box rules and the opening boundary conditions, the impacts of transit traffic, the central station, traffic lights cycle, the vehicles length on the mixed traffic flow is studied by computer simulation. Some important characters appearing in the new model are also elucidated. It shows that traffic flow is closely related to traffic lights cycle, the geometric structure of transport network and boundary conditions. Under certain traffic light cycle time, the traffic flow has a periodical oscillation change. The comparison to practical measured data shows that our stimulation results are accordant with the changes of real traffic flow, which confirms the accuracy and rationality of our model.

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THE TRAFFIC BOTTLENECK EFFECTS CAUSED BY THE LANE CLOSING IN THE CELLULAR AUTOMATA MODEL

International Journal of Modern Physics C ◽

10.1142/s012918310300542x ◽

2003 ◽

Vol 14 (10) ◽

pp. 1295-1303 ◽

Cited By ~ 21

Author(s):

BIN JIA ◽

RUI JIANG ◽

QING-SONG WU

Keyword(s):

Cellular Automata ◽

Traffic Flow ◽

Flow Rate ◽

Flow Model ◽

Maximum Flow ◽

Density Inversion ◽

Cellular Automata Model ◽

Traffic Flow Model ◽

Density Distributions ◽

Inversion Phenomenon

As a kind of bottleneck, the lane closing has seldomly been investigated with cellular automata model. In this paper, we study this issue using the cellular automata traffic flow model. The capacity and the density distribution of this kind of bottleneck are discussed in details. We find that (i) the capacity of the bottleneck is a little smaller than the maximum flow rate of single-lane road; (ii) different regulations may lead to different density distributions of the vehicles upstream of the lane closing. Moreover, the density inversion phenomenon is reported under certain conditions. This enlightens us to propose that the phenomenon of density inversion reported in many publications may be caused by the bottlenecks on the highway.

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MODELING THE INTERACTION BETWEEN MOTORIZED VEHICLE AND BICYCLE BY USING CELLULAR AUTOMATA MODEL

International Journal of Modern Physics C ◽

10.1142/s0129183109013558 ◽

2009 ◽

Vol 20 (02) ◽

pp. 209-222 ◽

Cited By ~ 19

Author(s):

XIN-GANG LI ◽

ZI-YOU GAO ◽

BIN JIA ◽

XIAO-MEI ZHAO

Keyword(s):

Cellular Automata ◽

Traffic Flow ◽

Future Research ◽

Mixed Traffic ◽

Cross Point ◽

Cellular Automata Model ◽

Mixed Traffic Flow ◽

Simulation Results ◽

The Cross ◽

The Right

In this paper, the cellular automata models for motorized vehicle flow and that for bicycle flow are combined to modeling the interactions between the right-turning motorized vehicle and the driving ahead bicycle at intersection. We introduce the probability that the cross point is taken up by the same kind of vehicle during two successive time steps to describe the complex behaviors when conflict happens. The flux of both motorized vehicle and bicycle depending on the inflow rates are investigated and the spatiotemporal diagrams are also presented to show different traffic states as the inflow rates change. The simulation results show that the model can describe the interactions between motorized vehicle and bicycle. It makes foundations for future research on mixed traffic flow.

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