The impact of iterated games on traffic flow at noncontrolled intersections

2015 ◽  
Vol 26 (01) ◽  
pp. 1550004 ◽  
Author(s):  
Chao Zhao ◽  
Ning Jia
Keyword(s):  
Traffic Flow ◽  
Numerical Experiments ◽  
Learning Ability ◽  
Signal Control ◽  
Field Observations ◽  
Fundamental Diagram ◽  
Cellular Automata Model ◽  
Urban Road ◽  
The Impact ◽  
Flow Experiences

Intersections without signal control widely exist in urban road networks. This paper studied the traffic flow in a noncontrolled intersection within an iterated game framework. We assume drivers have learning ability and can repetitively adjust their strategies (to give way or to rush through) in the intersection according to memories. A cellular automata model is applied to investigate the characteristics of the traffic flow. Numerical experiments indicate two main findings. First, the traffic flow experiences a "volcano-shaped" fundamental diagram with three different phases. Second, most drivers choose to give way in the intersection, but the aggressive drivers cannot be completely eliminated, which is coincident with field observations. Analysis are also given out to explain the observed phenomena. These findings allow deeper insight of the real-world bottleneck traffic flow.

scholarly journals Evaluating Impacts of Overloaded Heavy Vehicles on Freeway Traffic Condition by a Novel Multi-Class Traffic Flow Model

2018 ◽  
Vol 10 (12) ◽  
pp. 4694 ◽  
Author(s):  
Xiang Wang ◽  
Po Zhao ◽  
Yanyun Tao
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Management Strategies ◽  
Maximum Speed ◽  
Heavy Vehicles ◽  
Fundamental Diagram ◽  
Traffic Condition ◽  
Traffic Flow Model ◽  
Traffic Conditions ◽  
The Impact

Overloaded heavy vehicles (HVs) have significant negative impacts on traffic conditions due to their inferior driving performance. Highway authorities need to understand the impact of overloaded HVs to assess traffic conditions and set management strategies. We propose a multi-class traffic flow model based on Smulders fundamental diagram to analyze the influence of overloaded HVs on traffic conditions. The relationship between the overloading ratio and maximum speed is established by freeway toll collection data for different types of HVs. Dynamic passenger car equivalent factors are introduced to represent the various impacts of overloaded HVs in different traffic flow patterns. The model is solved analytically and discussed in detail in the appendices. The model validation results show that the proposed model can represent traffic conditions more accurately with consideration for overloaded HVs. The scenario tests indicate that the increase of overloaded HVs leads to both a higher congestion level and longer duration.

Effects of iterative learning based signal control strategies on macroscopic fundamental diagrams of urban road networks

2016 ◽  
Vol 27 (04) ◽  
pp. 1650045 ◽  
Author(s):  
Fei Yan ◽  
Fuli Tian ◽  
Zhongke Shi
Keyword(s):  
Control Strategies ◽  
High Capacity ◽  
Road Networks ◽  
Iterative Learning ◽  
Urban Traffic ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Fundamental Diagram ◽  
Urban Road ◽  
Modeling Uncertainties

Urban traffic flows are inherently repeated on a daily or weekly basis. This repeatability can help improve the traffic conditions if it is used properly by the control system. In this paper, we propose a novel iterative learning control (ILC) strategy for traffic signals of urban road networks using the repeatability feature of traffic flow. To improve the control robustness, the ILC strategy is further integrated with an error feedback control law in a complementary manner. Theoretical analysis indicates that the ILC-based traffic signal control methods can guarantee the asymptotic learning convergence, despite the presence of modeling uncertainties and exogenous disturbances. Finally, the impacts of the ILC-based signal control strategies on the network macroscopic fundamental diagram (MFD) are examined. The results show that the proposed ILC-based control strategies can homogenously distribute the network accumulation by controlling the vehicle numbers in each link to the desired levels under different traffic demands, which can result in the network with high capacity and mobility.

Cellular automaton model for three-lane urban road considering Internet of Vehicles lane

2020 ◽  
Vol 31 (12) ◽  
pp. 2050179
Author(s):  
Han-Tao Zhao ◽  
Xin Zhao ◽  
Liu-Yan Xin
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Road Traffic ◽  
Connected Vehicles ◽  
Cellular Automata Model ◽  
Internet Of Vehicles ◽  
Urban Road ◽  
Long Time ◽  
Set Up ◽  
Space Occupation

Although the technology of Internet of Vehicles (IoV) is developing rapidly, it will still take a long time to realize its overall popularization. Aimed at this transition phase, this paper proposes to set up an IoV lane on the urban road, which is specially designed for the connected vehicles, to provide a better driving environment for the connected vehicles. Considering the operation characteristics of traffic flow under traditional and IoV environment, this paper establishes a three-lane cellular automata model for urban road traffic flow considering IoV lane, modified on the basis of the Modified Comfortable Driving (MCD) model and symmetric two-lane cellular automata (STCA) model, and then takes simulation by MATLAB and makes analysis. The result shows that the setting of IoV lane can improve the velocity of networked vehicles to a great extent with no or just a bit decline in the ordinary vehicles’ speed, and it has a great effect on the mixture traffic flow, including the increase in both traffic volume and the average speed. What’s more, when the networking proportion is between 0.2 and 0.76, and the space occupation ranges from 0.18 to 0.56, the traffic benefit of IoV special lane can reach the best.

scholarly journals A Modified Cellular Automaton Approach for Mixed Bicycle Traffic Flow Modeling

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaonian Shan ◽  
Zhibin Li ◽  
Xiaohong Chen ◽  
Jianhong Ye
Keyword(s):  
Cellular Automaton ◽  
Traffic Flow ◽  
Field Data ◽  
Primary Objective ◽  
Field Observations ◽  
Flow Modeling ◽  
Fundamental Diagram ◽  
Lane Changes ◽  
Flow Features ◽  
Ca Model

Several previous studies have used the Cellular Automaton (CA) for the modeling of bicycle traffic flow. However, previous CA models have several limitations, resulting in differences between the simulated and the observed traffic flow features. The primary objective of this study is to propose a modified CA model for simulating the characteristics of mixed bicycle traffic flow. Field data were collected on physically separated bicycle path in Shanghai, China, and were used to calibrate the CA model using the genetic algorithm. Traffic flow features between simulations of several CA models and field observations were compared. The results showed that our modified CA model produced more accurate simulation for the fundamental diagram and the passing events in mixed bicycle traffic flow. Based on our model, the bicycle traffic flow features, including the fundamental diagram, the number of passing events, and the number of lane changes, were analyzed. We also analyzed the traffic flow features with different traffic densities, traffic components on different travel lanes. Results of the study can provide important information for understanding and simulating the operations of mixed bicycle traffic flow.

Modeling of pollution from the wastewater discharge of the city of Limassol

1995 ◽  
Vol 32 (9-10) ◽  
pp. 197-204
Author(s):  
G. C. Christodoulou ◽  
I. Ioakeim ◽  
K. Ioannou
Keyword(s):  
Field Observations ◽  
Wastewater Discharge ◽  
Dispersion Models ◽  
Preliminary Assessment ◽  
Westerly Winds ◽  
Dimensional Finite Element ◽  
The Impact ◽  
The City ◽  
Oceanographic Conditions ◽  
Continuous Loading

The paper presents a numerical modeling study aimed at a preliminary assessment of the impact of the planned sea outfall of the city of Limassol, Cyprus, on the waters of Akrotiri bay. First the local meteorological and oceanographic conditions as well as the loading characteristics are briefly reviewed. Two-dimensional finite element hydrodynamic and dispersion models are subsequently applied to the study area. The results of the former show an eastbound flow pattern under the prevailing westerly winds, in general agreement with available field observations. The spread of BOD and N under continuous loading is then examined for eastward as well as for westward flow as an indicator for the extent of pollution to be expected. The computed concentrations are generally low and confined to the shallower parts of the bay.

Fluoxetine Protects against Dendritic Spine Loss in Middle-aged APPswe/PSEN1dE9 Double Transgenic Alzheimer’s Disease Mice

2020 ◽  
Vol 17 (1) ◽  
pp. 93-103 ◽  
Author(s):  
Jing Ma ◽  
Yuan Gao ◽  
Wei Tang ◽  
Wei Huang ◽  
Yong Tang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dendritic Spines ◽  
Dendritic Spine ◽  
Early Stage ◽  
Learning Ability ◽  
Middle Aged ◽  
Protein Levels ◽  
Spine Pathology ◽  
The Impact

Background: Studies have suggested that cognitive impairment in Alzheimer’s disease (AD) is associated with dendritic spine loss, especially in the hippocampus. Fluoxetine (FLX) has been shown to improve cognition in the early stage of AD and to be associated with diminishing synapse degeneration in the hippocampus. However, little is known about whether FLX affects the pathogenesis of AD in the middle-tolate stage and whether its effects are correlated with the amelioration of hippocampal dendritic dysfunction. Previously, it has been observed that FLX improves the spatial learning ability of middleaged APP/PS1 mice. Objective: In the present study, we further characterized the impact of FLX on dendritic spines in the hippocampus of middle-aged APP/PS1 mice. Results: It has been found that the numbers of dendritic spines in dentate gyrus (DG), CA1 and CA2/3 of hippocampus were significantly increased by FLX. Meanwhile, FLX effectively attenuated hyperphosphorylation of tau at Ser396 and elevated protein levels of postsynaptic density 95 (PSD-95) and synapsin-1 (SYN-1) in the hippocampus. Conclusion: These results indicated that the enhanced learning ability observed in FLX-treated middle-aged APP/PS1 mice might be associated with remarkable mitigation of hippocampal dendritic spine pathology by FLX and suggested that FLX might be explored as a new strategy for therapy of AD in the middle-to-late stage.

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