Flow Comparison of the Traffic Model Based on Safe Driving

2014 ◽  
Vol 496-500 ◽  
pp. 2937-2941
Author(s):  
Wei Jun Pan ◽  
Chen Yu Huang
Keyword(s):  
Cellular Automata ◽  
Numerical Simulations ◽  
Traffic Flow ◽  
Critical Density ◽  
Stable State ◽  
Traffic Model ◽  
Safe Driving ◽  
Model Based ◽  
Ca Model ◽  
The Stability

Based on the SDNS cellular automata (CA) traffic model, the safe driving CA model has been proposed by considering the condition of having a stationary vehicle ahead. In this paper, this model was improved by analyzing the condition of safe deceleration, and also another single lane traffic CA model emphasizing high safety was proposed. The new safe driving rule was introduced based on the ascertained deceleration and distance ahead. Numerical simulations have been carried out. The results indicate the increase of traffic flow and the stability of the whole system, and also reveal the presence of meta-stable state near the critical density.

Design and Simulation of Improved One-Dimensional Cellular Automaton Model

2014 ◽  
Vol 496-500 ◽  
pp. 2946-2949
Author(s):  
Rui Kang ◽  
Kai Yang
Keyword(s):  
Model Simulation ◽  
Critical Density ◽  
Stable State ◽  
Traffic Model ◽  
Flow Density ◽  
Entire System ◽  
One Dimensional ◽  
Ca Model ◽  
The Stability ◽  
The Impact

By analyzing the condition of safe deceleration, a new CA traffic model emphasizing high safety was simulated. In order to describe the impact of the safety deceleration on the model, using computer to design and implement safety deceleration CA model simulation program. Computer numerical simulations have been carried out. The flow-density diagrams indicate the increase of flow and the stability of the entire system, and show the presence of meta-stable state near the critical density. With the increase of safety deceleration probability, the traffic flow is higher than that with the former model in the situations of both mid density and mid-low density.

Time-Space Research of the Two Safety Deceleration Models

2014 ◽  
Vol 496-500 ◽  
pp. 2950-2954
Author(s):  
Wei Jun Pan ◽  
Na Lu
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Original Model ◽  
Space Research ◽  
Traffic Model ◽  
Time Space ◽  
Proposed Model ◽  
Ca Model ◽  
Combined Action ◽  
Real Traffic

The SDNS cellular automata (CA) traffic model is chosen as the method to point out the fault in the original model by analyzing the condition of safety deceleration. An improved CA model is proposed in this paper through adjustment of the evolution steps and the redefinition of safe deceleration conditions. Thousands of simulations have been carried out. Comparing with SDNS model and original safety deceleration model with the proposed model in this paper, when emerging congestion, the combined action of urging and safe deceleration enabled system self-adjustment so that efficiently mitigated congestion. This proves that the stop status of the whole traffic flow has been improved, which have been observed in real traffic.

Research and Improvement of the Keep-Right-Except-to-Pass Rule

2014 ◽  
Vol 915-916 ◽  
pp. 459-463
Author(s):  
He Quan Zhang
Keyword(s):  
Fluid Mechanics ◽  
Traffic Flow ◽  
Influence Factors ◽  
Traffic Model ◽  
Light Traffic ◽  
The Road ◽  
Model Based ◽  
Light Passing ◽  
Improved Model ◽  
The Impact

In order to deal with the impact on traffic flow of the rule, we compare the influence factors of traffic flow (passing, etc.) into viscous resistance of fluid mechanics, and establish a traffic model based on fluid mechanics. First, in heavy and light traffic, we respectively use this model to simulate the actual segment of the road and find that when the traffic is heavy, the rule hinder the further increase in traffic. For this reason, we make further improvements to the model to obtain a fluid traffic model based on no passing and find that the improved model makes traffic flow increase significantly. Then, the improved model is applied to the light traffic, we find there are no significant changes in traffic flow .In this regard we propose a new rule: when the traffic is light, passing is allowed, but when the traffic is heavy, passing is not allowed.

A two-lane lattice model considering taillight effect and man–machine hybrid driving

2020 ◽  
Vol 34 (32) ◽  
pp. 2050365
Author(s):  
Siyuan Chen ◽  
Changxi Ma ◽  
Jinchou Gong
Keyword(s):  
Traffic Flow ◽  
Lattice Model ◽  
Critical Density ◽  
Mkdv Equation ◽  
Flow Stability ◽  
Stability Conditions ◽  
Neutral Stability ◽  
Nonlinear Stability Analysis ◽  
Traffic Flow Stability ◽  
The Stability

At present, drivers can rely on road communication technology to obtain the current traffic status information, and the development of intelligent transportation makes self-driving possible. In this paper, considering the mixed traffic flow with self-driving vehicles and the taillight effect, a new macro-two-lane lattice model is established. Combined with the concept of critical density, the judgment conditions for vehicles to take braking measures are given. Based on the linear analysis, the stability conditions of the new model are obtained, and the mKdV equation describing the evolution mechanism of density waves is derived through the nonlinear stability analysis. Finally, with the help of numerical simulation, the phase diagram and kink–anti-kink waveform of neutral stability conditions are obtained, and the effects of different parameters of the model on traffic flow stability are analyzed. The results show that the braking probability, the proportion of self-driving vehicles and the critical density have significant effects on the traffic flow stability. Considering taillight effect and increasing the mixing ratio of self-driving vehicles can effectively enhance the stability of traffic flow, but a larger critical density will destroy the stability of traffic flow.

scholarly journals A Macroscopic Traffic Model based on Driver Reaction and Traffic Stimuli

2019 ◽  
Vol 9 (14) ◽  
pp. 2848 ◽  
Author(s):  
Zawar H. Khan ◽  
Waheed Imran ◽  
Sajid Azeem ◽  
Khurram S. Khattak ◽  
T. Aaron Gulliver ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Traffic Model ◽  
Traffic Flow Model ◽  
Velocity Constant ◽  
Model Based ◽  
Proposed Model ◽  
Macroscopic Traffic Flow ◽  
Macroscopic Traffic Model ◽  
Traffic Behavior

A new macroscopic traffic flow model is proposed, which considers driver presumption based on driver reaction and traffic stimuli. The Payne–Whitham (PW) model characterizes the traffic flow based on a velocity constant C 0 which results in unrealistic density and velocity behavior. Conversely, the proposed model characterizes traffic behavior with velocities based on the distance headway. The performance of the proposed and PW models is evaluated over a 300 m circular road for an inactive bottleneck. The results obtained show that the traffic behavior with the proposed model is more realistic.

Theoretical analysis of a hybrid traffic model accounting for safe velocity

2017 ◽  
Vol 31 (11) ◽  
pp. 1750104 ◽  
Author(s):  
Yu-Qing Wang ◽  
Chao-Fan Zhou ◽  
Bo-Wen Yan ◽  
De-Chen Zhang ◽  
Ji-Xin Wang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Local Equilibrium ◽  
Density Wave ◽  
Traffic Model ◽  
Safe Driving ◽  
Traffic Flow Model ◽  
Velocity Wave ◽  
Vehicle Velocity ◽  
Global Equilibrium

A hybrid traffic-flow model [Wang–Zhou–Yan (WZY) model] is brought out in this paper. In WZY model, the global equilibrium velocity is replaced by the local equilibrium one, which emphasizes that the modification of vehicle velocity is based on the view of safe-driving rather than the global deployment. In the view of safe-driving, the effect of drivers’ estimation is taken into account. Moreover, the linear stability of the traffic model has been performed. Furthermore, in order to test the robustness of the system, the evolvement of the density wave and the velocity wave of the traffic flow has been numerically calculated.

A NEW CELLULAR AUTOMATON MODEL FOR TRAFFIC FLOW WITH DIFFERENT PROBABILITY FOR DRIVERS

2007 ◽  
Vol 18 (05) ◽  
pp. 773-782 ◽  
Author(s):  
H. B. ZHU ◽  
H. X. GE ◽  
S. Q. DAI
Keyword(s):  
Cellular Automaton ◽  
Traffic Flow ◽  
Metastable State ◽  
Maximum Flow ◽  
Traffic Model ◽  
Fundamental Diagram ◽  
Density Dependent ◽  
Spontaneous Formation ◽  
Traffic Jams ◽  
Ca Model

Based on the Nagel–Schreckenberg (NaSch) model of traffic flow, a new cellular automaton (CA) traffic model is proposed to simulate microscopic traffic flow. The probability p is a variable which contains a randomly selected term for each individual driver and a density-dependent term which is the same for all drivers. When the rational probability p is obtained, the larger value of maximum flow which is close to the observed data can be reached compared with that obtained from the NaSch model. The fundamental diagram obtained by simulation shows the ability of this modified CA model to capture the essential features of traffic flow, e.g., the spontaneous formation of traffic jams and appearance of the metastable state. These indicate that the presented model is more reasonable and realistic.

Bottleneck Simulation of Two-Lane Traffic CA Model with Turn Signal

2013 ◽  
Vol 404 ◽  
pp. 640-644
Author(s):  
Rui Kang ◽  
Kai Yang
Keyword(s):  
Numerical Simulations ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Driver Behavior ◽  
Traditional Model ◽  
Right Of Way ◽  
Time Space ◽  
Before And After ◽  
Ca Model ◽  
The Right

Based on the STCA model, an improved two-lane traffic CA model in view of turn signals is proposed. The model considers changes in driver behavior before and after the signaling of the leading vehicle, and introduces rules of changing lanes, cutting lanes and yielding the right of way for the flowing vehicle. Through computer numerical simulations, this study has presented time-space diagrams and also analyzed the effects of driver behavior of the rear vehicles on traffic flow. The results reveal that a higher rate of cutting lanes incurs a heavier traffic flow in normal situations while yielding the right of way relieves traffic congestion in a bottleneck situation. Compared with the traditional model, STCA model can depict more complex traffic situations resulted from different driver behaviors and reproduce a more realistic process of traffic flow.

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