Basic Study on Expressway Congestion Mitigation using Cellular Automata

Traffic congestion has become a serious social problem in Japan. In particular, traffic congestion causes enormous time and economic losses on expressways, which are intended to facilitate smooth traffic flow. It also causes environmental problems and a decrease in logistics efficiency, so efforts to eliminate or reduce traffic congestion are essential. The elimination and mitigation of traffic congestion on highways is a factor in reducing traffic accidents and fatalities. In recent years, with the improvement of computing capabilities, research on traffic congestion reduction and mitigation has been conducted using traffic simulation. Traffic simulation allows us to reproduce and evaluate traffic phenomena that occur on roads on a computer. The Kakuto Tunnel is located on the border between Ebino City in Miyazaki Prefecture and Hitoyoshi City in Kumamoto Prefecture. The Kakuto Tunnel has insufficient traffic capacity and is frequently congested on holidays. In this study, we created a traffic simulator assuming the Kakuto Tunnel. In the simulation, we examined the effectiveness of increasing the number of lanes as a method of reducing traffic congestion.

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3D Road Scene Monitoring Based on Real-Time Panorama

Journal of Applied Mathematics ◽

10.1155/2014/403126 ◽

2014 ◽

Vol 2014 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

Yuezhou Wu ◽

Changjiang Liu ◽

Shiyong Lan ◽

Menglong Yang

Keyword(s):

Real Time ◽

Traffic Flow ◽

High Precision ◽

Motion Detection ◽

Large Scale ◽

Traffic Accidents ◽

Traffic Situation ◽

Traffic Capacity ◽

Monitoring Framework ◽

3D Scene

Road monitoring helps to control the regional traffic situation so as to adjust the traffic flow. Real-time panorama is conducive to timely treat traffic accidents and to greatly improve traffic capacity. This paper designs a 3D road scene monitoring framework based on real-time panorama. The system is the combination of large scale panorama, satellite map textures, and 3D scene model, in which users can ramble freely. This paper has the following contributions. Firstly, land-points were extracted followed by motion detection, then comotion algorithm was applied to land-points from adjacent cameras, and homography matrix was constructed. Secondly, reference camera was chosen and transformed to overhead viewpoint; subsequently multiviews were morphed to the same viewpoint and stitched to panorama. Finally, the registration based on high-precision GPS information between 2D road panorama and 3D scene model was also proposed. The proposed framework has been successfully applied to a large road intersection monitoring. Experimental results are furnished at the end of the paper.

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Study on the Traffic Capacity of Expressway Based on Cellular Automata Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.701-702.172 ◽

2014 ◽

Vol 701-702 ◽

pp. 172-179

Author(s):

Xiao Dong Xia ◽

Lin Ling Xu

Keyword(s):

Cellular Automata ◽

Traffic Flow ◽

Heavy Traffic ◽

Accident Rate ◽

Cellular Automata Model ◽

Traffic Capacity ◽

Low Load ◽

The Right ◽

The Relationship ◽

Shape Changes

Based on the Nagel-Schrekenberg cellular automaton model of traffic flow, this article analyzed the influence that driving on the right side takes to the traffic flow in the condition of light and heavy traffic. With the combination of fluid dynamics and vehicle dynamics, we established the Cellular Automata model for mixed speed two-lane traffic flow on the rule driving on the right side. Then we used the AHP method to find out the large bus share rate, the number of vehicles changing lanes and the influence law of safety factors on traffic flow. We came to a conclusion that the relationship between traffic flow and load are inverted U shape changes in the low load and high load conditions, the accident rate is the maximum when the V/C (the ratio of traffic flow and the ability of corresponding section) is the minimum; with the increase of V/C, the accident rate decreased gradually.

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Portable Telematic System as an Effective Traffic Flow Management in Workzones

Transport and Telecommunication Journal ◽

10.1515/ttj-2015-0009 ◽

2015 ◽

Vol 16 (2) ◽

pp. 99-106 ◽

Cited By ~ 1

Author(s):

Marek Ščerba ◽

Tomáš Apeltauer ◽

Jiří Apeltauer

Keyword(s):

Traffic Flow ◽

Traffic Safety ◽

Traffic Control ◽

Traffic Management ◽

Traffic Accidents ◽

Intelligent System ◽

Economic Losses ◽

Road Users ◽

Traffic Flow Management ◽

Negative Impacts

Abstract Traffic infrastructure localities with temporal restrictions for example due to reconstructions, or modernization, are important aspects influencing the traffic safety and traffic flow. On the basis of our research, we can identify main factors, which generate travel time loses, and which often cause traffic accidents in bottlenecks. First of all, it is improper late merge, speeding, tailgating, lower tolerance and consideration to other road users. Nervousness and ignorance of drivers also play an important role in generation of traffic congestions, lower level of service and resulting external economic loses. One of the tools eliminating the traffic restriction negative impacts is usage of portable telematics systems. In 2011 to 2013,project ViaZONE was in progress, which was to design an intelligent system with the aim to eliminate the mentioned risks and reduce economic losses generated by traffic congestions. Using available data and information, we have proved profitability and cost-effectiveness of dynamic systems for traffic control of work zones. Regarding traffic management, the system showed some problems due to indisciplined drivers and the system proved that speeding in these hazardous road segments is a common practice which caused accidents and congestions.

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A Yielding Protocol that Uses Inter-Vehicle Communication to Improve the Traffic of Vehicles on a Low-Priority Road at an Unsignalized Intersection

Future Internet ◽

10.3390/fi11050110 ◽

2019 ◽

Vol 11 (5) ◽

pp. 110

Author(s):

Hayato Yajima ◽

Kazumasa Takami

Keyword(s):

Traffic Flow ◽

Traffic Congestion ◽

Traffic Accidents ◽

Vehicle Communication

Self-driven vehicles are being actively developed. When widespread, they will help reduce the number of traffic accidents and ease traffic congestion. They will coexist with human-driven vehicles for years. If there is a mismatch between human drivers’ operations and the judgments of self-driven vehicles, congestion may arise at an unsignalized intersection, in particular, where roads are prioritized. Vehicles on the low-priority road attempting to cross, or turn to, the priority road can significantly reduce the traffic flow. We have proposed a yielding protocol to deal with this problem and evaluated it using a simulation that focused on traffic flow efficiency at an intersection. In the simulation, we have varied the number of vehicles coming into the roads and the percentage of self-driven vehicles and confirmed that the proposed yielding protocol could improve the traffic flow of vehicles on the low-priority road.

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An Improved Lattice Hydrodynamic Model by considering the Effect of “Backward-Looking” and Anticipation Behavior

Complexity ◽

10.1155/2021/4642202 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Jin Wan ◽

Xin Huang ◽

Wenzhi Qin ◽

Xiuge Gu ◽

Min Zhao

Keyword(s):

Stability Analysis ◽

Traffic Flow ◽

Linear Stability ◽

Linear Stability Analysis ◽

Hydrodynamic Model ◽

Traffic Congestion ◽

Traffic Accidents ◽

Flow Stability ◽

Lattice Hydrodynamic Model ◽

Traffic Flow Stability

In order to prevent the occurrence of traffic accidents, drivers always focus on the running conditions of the preceding and rear vehicles to change their driving behavior. By taking into the “backward-looking” effect and the driver’s anticipation effect of flux difference consideration at the same time, a novel two-lane lattice hydrodynamic model is proposed to reveal driving characteristics. The corresponding stability conditions are derived through a linear stability analysis. Then, the nonlinear theory is also applied to derive the mKdV equation describing traffic congestion near the critical point. Linear and nonlinear analyses of the proposed model show that how the “backward-looking” effect and the driver’s anticipation behavior comprehensively affect the traffic flow stability. The results show that the positive constant γ , the driver’s anticipation time τ , and the sensitivity coefficient p play significant roles in the improvement of traffic flow stability and the alleviation of the traffic congestion. Furthermore, the effectiveness of linear stability analysis and nonlinear analysis results is demonstrated by numerical simulations.

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Modeling traffic flow in work zone sections considering the effect of traffic lights

International Journal of Modern Physics C ◽

10.1142/s0129183121501138 ◽

2021 ◽

pp. 2150113

Author(s):

Xingyu Lu ◽

Li Fei ◽

Huibing Zhu ◽

Wangjun Cheng ◽

Zijie Wang

Keyword(s):

Traffic Flow ◽

Traffic Congestion ◽

Traffic Management ◽

Traffic Accidents ◽

Red Light ◽

Work Zone ◽

Traffic Model ◽

Traffic Density ◽

Highway Traffic ◽

Traffic Lights

Based on the two-lane highway traffic model with a work zone presented previously, a new traffic model with a work zone under the control of traffic lights is proposed. The length of the waiting area for vehicles before traffic lights is recommended cautiously after numerical simulation. The relationship between the vehicles’ queuing time and the cycle of traffic lights is studied, and the cycle time of traffic lights is obtained also considering people’s endurance to the red light. It is found that the traffic lights are effective to ease the traffic congestion in the work zone when the density is medium, and help to eliminate the inducement of traffic accidents. On the other hand, the simulation results show that traffic lights are not needed in the work zone when the traffic density is small. It indicates that the traffic flow in the work zone area can be optimized by using appropriate traffic management when the traffic density varies.

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Urban road traffic flow control under incidental congestion as a function of accident duration

Open Physics ◽

10.1515/phys-2018-0129 ◽

2018 ◽

Vol 16 (1) ◽

pp. 1085-1093

Author(s):

Yang Xu ◽

Duojia Zhang ◽

Ahmad Jalal Khan Chowdhury

Keyword(s):

Flow Control ◽

Traffic Flow ◽

Traffic Congestion ◽

Road Traffic ◽

Abrupt Increase ◽

Urban Road ◽

Catastrophe Model ◽

Traffic Capacity ◽

Control Scheme

Abstract An abrupt increase in urban road traffic flow caused by incidental congestion is considered. The residual traffic capacity varies in different lanes after an accident, and the influence of accident duration on traffic flow is taken into account. The swallowtail catastrophe model was built based on catastrophe theory. The critical state of traffic congestion under incidental congestion was analyzed using this model, and a traffic flow control scheme is proposed with the goal of maximizing the traffic capacity. Finally, the operational state of traffic flow under different scenarios is analyzed through case study and the feasibility of the model is validated.

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An Assessment of Age and Gender Characteristics of Mixed Traffic with Autonomous and Manual Vehicles: A Cellular Automata Approach

Sustainability ◽

10.3390/su12072922 ◽

2020 ◽

Vol 12 (7) ◽

pp. 2922 ◽

Cited By ~ 2

Author(s):

Muhammad Tanveer ◽

Faizan Ahmad Kashmiri ◽

Hassan Naeem ◽

Huimin Yan ◽

Xin Qi ◽

...

Keyword(s):

Cellular Automata ◽

Traffic Flow ◽

Traffic Congestion ◽

Urban Areas ◽

Autonomous Vehicles ◽

Age Groups ◽

Transportation Systems ◽

Heterogeneous Traffic ◽

And Gender ◽

The Impact

Traffic congestion has become increasingly prevalent in many urban areas, and researchers are continuously looking into new ways to resolve this pertinent issue. Autonomous vehicles are one of the technologies expected to revolutionize transportation systems. To this very day, there are limited studies focused on the impact of autonomous vehicles in heterogeneous traffic flow in terms of different driving modes (manual and self-driving). Autonomous vehicles in the near future will be running parallel with manual vehicles, and drivers will have different characteristics and attributes. Previous studies that have focused on the impact of autonomous vehicles in these conditions are scarce. This paper proposes a new cellular automata model to address this issue, where different autonomous vehicles (cars and buses) and manual vehicles (cars and buses) are compared in terms of fundamental traffic parameters. Manual cars are further divided into subcategories on the basis of age groups and gender. Each category has its own distinct attributes, which make it different from the others. This is done in order to obtain a simulation as close as possible to a real-world scenario. Furthermore, different lane-changing behavior patterns have been modeled for autonomous and manual vehicles. Subsequently, different scenarios with different compositions are simulated to investigate the impact of autonomous vehicles on traffic flow in heterogeneous conditions. The results suggest that autonomous vehicles can raise the flow rate of any network considerably despite the running heterogeneous traffic flow.

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A new feedback control scheme for the lattice hydrodynamic model with drivers’ sensory memory

International Journal of Modern Physics C ◽

10.1142/s0129183121500224 ◽

2020 ◽

pp. 2150022

Author(s):

Zhang Yicai ◽

Zhao Min ◽

Sun Dihua ◽

Zhou Zhaomin ◽

Chen Dong

Keyword(s):

Feedback Control ◽

Traffic Flow ◽

Hydrodynamic Model ◽

Traffic Congestion ◽

Sensory Memory ◽

Economic Losses ◽

Short Term ◽

Control Scheme ◽

The Stability

With development of economy, the problem of traffic congestion is becoming more and more serious, which has caused economic losses and environmental pollution. Therefore, it is necessary to put forward reasonable solutions through the study of traffic flow theory. This paper proposes a new hydrodynamic model of traffic flow considering the drivers’ sensory memory and a new corresponding feedback control scheme. Through the stability analysis of the model, the stability conditions are derived. The obtained phase-plot shows that the sensory memory of drivers can affect the instability region, and the new feedback control term will reduce the unstable region. The numerical simulations by analyzing the short-term, long-term behaviors and hysteresis loop of traffic flow verify the impacts of the drivers’ sensory memory and the control sign.

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How To Improve Urban Intelligent Traffic? A Case Study Using Traffic Signal Timing Optimization Model Based On Swarm Intelligence Algorithm

Sensors ◽

10.3390/s21082631 ◽

2021 ◽

Vol 21 (8) ◽

pp. 2631

Author(s):

Xiancheng Fu ◽

Hengqiang Gao ◽

Hongjuan Cai ◽

Zhihao Wang ◽

Weiming Chen

Keyword(s):

Traffic Flow ◽

Optimization Model ◽

Traffic Congestion ◽

Delay Time ◽

Traffic Signal ◽

Urban Traffic ◽

Signal Timing ◽

Average Delay ◽

Traffic Capacity ◽

Traffic Signal Timing

Traffic congestion is a major problem in today’s society, and the intersection, as an important hub of urban traffic, is one of the most common places to produce traffic congestion. To alleviate the phenomenon of congestion at urban traffic intersections and relieve the traffic pressure at intersections, this paper takes the traffic flow at intersections as the research object and adopts the swarm intelligent algorithm to establish an optimization model of intersection traffic signal timing, which takes the average delay time of vehicles, the average number of stops of vehicles and the traffic capacity as the evaluation indexes. This model adjusts the intersection traffic signal timing intelligence according to the real-time traffic flow and carries out simulation experiments with MATLAB. Compared with the traditional timing schemes, the average delay time of vehicles is reduced by 10.25%, the average number of stops of vehicles is reduced by 24.55%, and the total traffic capacity of the intersection is increased by 3.56%, which verifies that the scheme proposed in this paper is effective in relieving traffic congestion.

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