Cellular automata–based modeling and simulation of the mixed traffic flow of vehicle platoon and normal vehicles

2021 ◽  
pp. 126368
Author(s):  
Liling Zhu ◽  
Yandong Tang ◽  
Da Yang
Keyword(s):  
Cellular Automata ◽  
Modeling And Simulation ◽  
Traffic Flow ◽  
Mixed Traffic ◽  
Mixed Traffic Flow ◽  
Vehicle Platoon

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

2009 ◽  
Vol 20 (02) ◽  
pp. 209-222 ◽  
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.

A two-lane mixed traffic flow model with drivers' intention to change lane based on cellular automata

2020 ◽  
Vol 16 (4) ◽  
pp. 229
Author(s):  
Changbing Jiang ◽  
Ruolan Li ◽  
Tinggui Chen ◽  
Chonghuan Xu ◽  
ang Li ◽  
...  
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Flow Model ◽  
Mixed Traffic ◽  
Traffic Flow Model ◽  
Mixed Traffic Flow ◽  
Intention To Change ◽  
Lane Based

scholarly journals A Cellular Automata Traffic Flow Model considering Bus Lane Changing Behavior with Scheduling Parameters

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Zun-dong Zhang ◽  
Yan-fang Yang ◽  
Wenjiao Qi ◽  
Abderrahim Chariete ◽  
Xing-xiang Lin
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Flow Model ◽  
Flow Density ◽  
Mixed Traffic ◽  
Lane Changing ◽  
Traffic Flow Model ◽  
Mixed Traffic Flow ◽  
Bus Lane ◽  
Bus Stops

According to different driving behavioral characteristics of bus drivers, a cellular automata traffic model considering the bus lane changing behavior with scheduling parameters is proposed in this paper. Traffic bottleneck problems caused by bus stops are simulated in multiple lanes roads with no-bay bus stations. With the mixed traffic flow composed of different bus arrival rate, flow-density graph, density distribution graph, and temporal-spatial graph are presented. Furthermore, the mixed traffic flow characteristics are analyzed. Numerical experiment results show that the proposed model can generate a variety of complicated realistic phenomena in the traffic system with bus stops and provide theoretical basis for better using of traffic flow model.

scholarly journals Feature Analysis on Mixed Traffic Flow of Manually Driven and Autonomous Vehicles Based on Cellular Automata

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Xinghua Hu ◽  
Mengyu Huang ◽  
Jianpu Guo
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Theoretical Basis ◽  
Flow Model ◽  
Maximum Flow ◽  
Feature Analysis ◽  
Mixed Traffic ◽  
Mixed Traffic Flow ◽  
Ca Model

This paper attempts to disclose the features of the mixed traffic flow of manually driven vehicles (MVs) and autonomous vehicles (AVs). Considering dynamic headway, the mixed traffic flow was modelled based on the improved single-land cellular automata (CA) traffic flow model (DHD) proposed by Zhang Ningxi. The established CA model was adopted to obtain the maximum flow of the mixed traffic flow and was analyzed under different proportions of AVs. On this basis, the features of the mixed traffic flow were summarized. The main results are as follows: the proportion of AVs has a significant impact on the mixed traffic flow; when the proportion reached 0.6, the flow of the whole lane was twice that of the MV traffic flow. At a low density, the AV proportion has an obvious influence on mixed traffic flow. At a high density, the mixed traffic flow changed very little, as the AV proportion increased from 0 to 5. The reason is that the flow of the whole lane is constrained by the fact that MVs cannot move faster. However, when the AV proportion reached 0.8, the flow of the whole lane became three times that at the proportion of 0.6. At the speed of 126 km/h, the flow rate was 2.5 times the speed limit of 54 km/h. The findings lay a theoretical basis for the modelling of multilane mixed traffic flow.

Simulation study of car accidents at the intersection of two roads in the mixed traffic flow

2015 ◽  
Vol 26 (01) ◽  
pp. 1550007 ◽  
Author(s):  
R. Marzoug ◽  
H. Ez-Zahraouy ◽  
A. Benyoussef
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Critical Density ◽  
Mixed Traffic ◽  
Priority Rules ◽  
Mixed Traffic Flow ◽  
Car Accidents ◽  
First Case ◽  
Accident Probability ◽  
The Impact

Using cellular automata (CA) Nagel–Schreckenberg (NaSch) model, we numerically study the probability P ac of the occurrence of car accidents at nonsignalized intersection when drivers do not respect the priority rules. We also investigated the impact of mixture lengths and velocities of vehicles on this probability. It is found that in the first case, where vehicles distinguished only by their lengths, the car accidents start to occur above a critical density ρc. Furthermore, the increase of the fraction of long vehicles (FL) delays the occurrence of car accidents (increasing ρc) and increases the risk of collisions when ρ > ρc. In other side, the mixture of maximum velocities (with same length for all vehicles) leads to the appearance of accidents at the intersection even in the free flow regime. Moreover, the increase of the fraction of fast vehicles (Ff) reduces the accident probability (P ac ). The influence of roads length is also studied. We found that the decrease of the roads length enhance the risk of collision.

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