CELLULAR AUTOMATA MODEL FOR UNSIGNALIZED T-SHAPED INTERSECTION

2009 ◽  
Vol 20 (04) ◽  
pp. 501-512 ◽  
Author(s):  
XIN-GANG LI ◽  
ZI-YOU GAO ◽  
BIN JIA ◽  
XIAO-MEI ZHAO
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Cellular Automata Model ◽  
Traffic Lights ◽  
Traffic Conditions ◽  
Main Street ◽  
Simulation Results

In this paper, the unsignalized T-shaped intersection is modeled by a cellular automata model. The main street and the minor street join at the intersection. As to the traffic flow is not controlled by traffic lights, conflict happens between the vehicles from minor street and that from main street. Two different crash avoiding rules are used to dispose the conflicts. In the first rule, the priorities are given to the driving-ahead vehicle and the vehicle on the main street. In the second rule, the vehicle that reaches the conflicting point earlier enters into the intersection. The flux on each lane depending on the inflow rates is studied in detail. The capacity of the system is also investigated. Our simulation results suggest that the two rules do not take the same effect on the capacity under different traffic conditions.

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.

scholarly journals CELLULAR AUTOMATA SIMULATION OF TRAFFIC LIGHT STRATEGIES IN OPTIMIZING THE TRAFFIC FLOW

2005 ◽  
Vol 4 (2) ◽  
pp. 13
Author(s):  
E. H. NUGRAHANI ◽  
R. RAMDHANI
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Control Strategies ◽  
Velocity Model ◽  
Flow Density ◽  
Traffic Light ◽  
Cellular Automata Model ◽  
Optimal Velocity ◽  
Traffic Lights ◽  
Traffic System

The behavior of traffic system controlled by traffic lights is presented under assumptions of city traffic on a single lane based on the optimal velocity model.  The effect of differrent traffic light control strategies on the traffic flow is discussed using three different strategies, i.e. the synchronized, green wave, and random offset strategies. The flow-density diagrams are analyzed using these strategies.   The numerical investigation is carried out using cellular automata model to get a better understanding of the microscopic behavior of the system under the three different traffic light strategies.

TRAFFIC FLOW AT A SIGNAL CONTROLLED T-SHAPED INTERSECTION

2010 ◽  
Vol 21 (03) ◽  
pp. 443-455 ◽  
Author(s):  
ZHONG-JUN DING ◽  
XIAO-YAN SUN ◽  
RUN-RAN LIU ◽  
QIAO-MING WANG ◽  
BING-HONG WANG
Keyword(s):  
Phase Diagram ◽  
Cellular Automata ◽  
Traffic Flow ◽  
Signal Phase ◽  
Cellular Automata Model ◽  
Three Phase ◽  
Average Travel Time ◽  
Simulation Results ◽  
Adaptive Signal ◽  
Better Than

In this paper, traffic flow at a signal controlled T-shaped intersection with three input roads is investigated by using the cellular automata model. When each road is a double lane, the model only exists in three conflict points among three directions of flows. We introduce three-phase traffic signal and two types of signal controlling strategies, i.e. fixed signal phase order as well as adaptive signal phase order strategy, to control the traffic flow at the intersection. The phase diagram, the capacity and the average travel time of the system are investigated and compared under both strategies. The simulation results show that the traffic adaptive signal strategy is better than the fixed signal phase order strategy.

Influence of pedestrians’ jaywalking behavior on vehicle flow

2018 ◽  
Vol 32 (22) ◽  
pp. 1850233
Author(s):  
Gang Liu ◽  
Jiayan Lu ◽  
Jingchao Wang ◽  
Xiaodong Jing ◽  
Jing He ◽  
...  
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Experimental Results ◽  
Dynamic Traffic ◽  
Cellular Automata Model ◽  
Urban Streets ◽  
Traffic Lights

There always exist a conflict between vehicles and pedestrians on urban streets. To study the complicated behaviors of vehicles and pedestrians is significant to understand the dynamics of traffic flow and explore efficient strategies for solving traffic problems. Based on this, this paper studies the effect of pedestrian’s jaywalking behavior on vehicle flow with no crosswalks and no traffic lights, and constructs a cellular automata model to describe the dynamic traffic flow by considering some significant traffic behaviors of pedestrians and vehicles. Experimental results show that the maximum vehicle flow will be greatly affected as long as there are jaywalking pedestrians; retreating behavior may lead to the fluctuation in vehicle flow; the maximum vehicle flow is greater if more pedestrians choose the behavior of fast crossing. This research is helpful to further study the interaction between pedestrians and vehicles.

A CELLULAR AUTOMATA MODEL OF TRAFFIC FLOW WITH CONSIDERATION OF THE INERTIAL DRIVING BEHAVIOR

2010 ◽  
Vol 21 (04) ◽  
pp. 549-557 ◽  
Author(s):  
JIAN-XUN DING ◽  
HAI-JUN HUANG
Keyword(s):  
Phase Transition ◽  
Cellular Automata ◽  
Traffic Flow ◽  
Driving Behavior ◽  
Metastable States ◽  
Cellular Automata Model ◽  
Simulation Results ◽  
Real Traffic ◽  
Formation Phase

The inertial driving behavior, although observed in real traffic, has not been deeply understood in most previous studies. In this paper we propose a cellular automata model of the traffic on a single lane highway which considers the drivers' inertial behavior under different driving circumstances. Simulation results show that our model can capture such important features of the traffic as jam formation, phase transition and metastable states. Some of other models, like the slow-to-start model, can be derived from our model.

Mutil-Conditions Impress Nonsingular Dimensional Cellular Automaton on Traffic Flow

2014 ◽  
Vol 926-930 ◽  
pp. 3455-3458
Author(s):  
Li Na Liu ◽  
Jie Wang ◽  
Chang Sheng Zhu ◽  
Ting Jing
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Flow Characteristics ◽  
Open Boundary ◽  
Open Boundary Conditions ◽  
Lane Changing ◽  
Cellular Automata Model ◽  
Traffic Lights ◽  
Traffic Flow Characteristics ◽  
The Relationship

This paper is based on Nagel-Schreckenberg cellular automata model as the foundation, in the open boundary conditions, the traffic vehicle redirecting probability and before lane changing rules get to intersection will produce certain effect to interference with intersection , and so as to builds up the nonsingular cellular automata model. Through the research to redirecting probability, lane changing rules and the settings of traffic lights play a part in traffic flow characteristics, and points out the influence of phase change point position ,and at the same time, traffic lights timing differences can reduce vehicle interference to increase traffic flow, at the same time, play a analysis the critical redirecting probability of traffic flow in controlling significance, and points out the relationship between the critical point of Lane changing probability and traffic flow influence ,and lane-changing rules is correspond to the basic line of vehicles running.

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