scholarly journals An Innovative Eigenvector-Based Method for Traffic Light Scheduling

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Mohammad Amin Soltani-Sarvestani ◽  
Zohreh Azimifar ◽  
Alexander Wong ◽  
Ali Akbar Safavi
Keyword(s):  
Transmission Model ◽  
Cell Transmission Model ◽  
Eigenvector Centrality ◽  
Traffic Light ◽  
Fundamental Diagram ◽  
Scheduling System ◽  
Traffic Jam ◽  
Grid Networks ◽  
Traffic Light Scheduling ◽  
Relation Matrix

This paper introduces two traffic light strategies to control traffic and avoid traffic jam in urban networks. One strategy is a new traffic light scheduling system, which controls traffic light using local variables (waiting time and number of vehicle on links) but has a global impact on the traffic, using shared variables between neighbour intersections. The proposed traffic light scheduling system is designed based on eigenvector centrality of intersection relation matrix. The intersection relation matrix is a new representation of a junction which indicates the traffic relation between intersection’s links and adjacent intersections. The second contribution is expanding a new dual mode traffic light strategy (namely, Exit Status Traffic Light (ETL)), which notifies the drivers whether they are allowed to exit a street or not. In other words, vehicles are allowed to enter a street in both red and green ETL, but they are not allowed to exit the street for a long time in red ETL (while traffic is heavy in the subnetwork). The ETL gives a chance to relax traffic in a subnetwork and avoid traffic jam. The effectiveness of the proposed strategy is analysed and evaluated by a number of simulations on three-way grid networks. Two-way rectangular grid networks are modelled via a cell transmission model (CTM). The macroscopic fundamental diagram (MFD) and the number of jammed cells are compared with two state-of-the-art methods.

A wave-oriented variable cell transmission model in an urban road

2021 ◽  
Author(s):  
Zeyu Shi ◽  
Yangzhou Chen ◽  
Jingyuan Zhan ◽  
Xiangyu Guo ◽  
Shuke An
Keyword(s):  
Traffic Flow ◽  
Urban Traffic ◽  
Transmission Model ◽  
Hybrid Automata ◽  
State Variables ◽  
Cell Transmission Model ◽  
Fundamental Diagram ◽  
Influence Area ◽  
Cell Transmission ◽  
The Waves

To describe the dynamics of traffic flow in the urban link accurately, the waves which generate at intersections are adopted as the influencing factors of traffic flow. Based on the urban traffic waves, a wave-oriented variable cell transmission model (WVCTM) is proposed to illustrate the urban traffic flow. In this model, the average density and length are the state variables. The cells are divided by traffic waves. The upstream cell is the influence area of the waves at the upstream intersection, the downstream cell is the influence area of the waves at the downstream intersection, and the rest is the mediate cell. Consistent with the fundamental diagram and the cell division, the traffic states of urban links are divided into six modes. The variation of modes is explained by hybrid automata. Finally, an experiment is designed to verify the feasibility of WVCTM. The data in the experiment come from the actual scene. Compared with the cell transmission model (CTM) and variable-length CTM (VCTM), WVCTM possesses the valuable performance to predict the traffic states. Likewise, it is rational that WVCTM can correctly illustrate the urban traffic flow.

Urban Traffic Jam Simulation Based on the Cell Transmission Model

2008 ◽  
Vol 11 (1) ◽  
pp. 43-64 ◽  
Author(s):  
Jiancheng Long ◽  
Ziyou Gao ◽  
Xiaomei Zhao ◽  
Aiping Lian ◽  
Penina Orenstein
Keyword(s):  
Urban Traffic ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Traffic Jam ◽  
Simulation Based ◽  
Cell Transmission

Width-Based Cell Transmission Model for Heterogeneous and Undisciplined Traffic Streams

2019 ◽  
Vol 2673 (5) ◽  
pp. 682-692 ◽  
Author(s):  
Afzal Ahmed ◽  
Satish V. Ukkusuri ◽  
Shahrukh Raza Mirza ◽  
Ausaja Hassan
Keyword(s):  
Traffic Flow ◽  
Behavior Modeling ◽  
Flow Diagram ◽  
Transmission Model ◽  
Flow Density ◽  
Cell Transmission Model ◽  
Fundamental Diagram ◽  
Flow Models ◽  
Cell Transmission ◽  
Traffic Flow Models

Traffic streams in many developing countries consist of various modes of transport, with high heterogeneity in driver behavior. Modeling these types of traffic streams, in which traffic rules (speed limit, lane discipline, etc.) are not strictly followed, is a complex task. A review of the existing literature shows that there is a lack of traffic flow models that model the behavior of heterogeneous and undisciplined traffic streams. Like other undisciplined traffic streams, there are no speed limits (hence no speed enforcement) on most of the roads in Karachi, Pakistan. Lane discipline is also not observed by drivers, which results in a varying number of traffic lanes on a road. Therefore, most of the existing traffic flow models/simulation packages developed for disciplined traffic streams cannot appropriately model traffic streams without lane discipline. This research proposes a width-based cell transmission model (WCTM) by developing a fundamental flow-density diagram whose parameters are a function of the road width. Extensive field data have been collected from a selected arterial in Karachi for development of the fundamental traffic flow diagram. The values of the computed parameters are significantly different than the values reported in the literature. The piecewise-linear flow-density relation is developed by optimally estimating the breakpoints. Results show that the quadrilateral and pentagonal-shaped fundamental diagrams fit better with the collected data in comparison with the triangular-shaped fundamental diagram. The proposed WCTM is applied to selected segments of an arterial and results show that the WCTM was able to accurately model different traffic conditions.

Imputation of Ramp Flow Data Using the Asymmetric Cell Transmission Traffic Flow Model

2009 ◽  
Author(s):  
Ajith Muralidharan ◽  
Roberto Horowitz
Keyword(s):  
Iterative Learning Control ◽  
Flow Model ◽  
Stability And Convergence ◽  
Transmission Model ◽  
Flow Density ◽  
Cell Transmission Model ◽  
Flow Data ◽  
Fundamental Diagram ◽  
Cell Transmission ◽  
The Stability

The Asymmetric Cell Transmission model can be used to simulate traffic flows in freeway sections. The model is specified by fundamental diagram parameters—determined from mainline data, and on-ramp and off-ramp flows. The mainline flow/density data are efficiently archived and readily available, but the ramp flow data are generally found missing. This paper presents an imputation technique based on iterative learning control to determine these flows. The imputation technique is applied sequentially on all the segments of the freeway, and the ramp flows, which minimize the error between the model calculated densities/flows and measurements are investigated. The stability and convergence of the density and flow errors using the imputation updates is also presented. Finally an example is shown to illustrate its use in a practical scenario.

scholarly journals On the application of variational theory on networks

2020 ◽  
Author(s):  
Gabriel Tilg ◽  
Lukas Ambühl ◽  
S. F. A. Batista ◽  
Fritz Busch ◽  
Monica Menendez
Keyword(s):  
Computational Cost ◽  
Wave Theory ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Source Terms ◽  
Variational Theory ◽  
Microscopic Simulation ◽  
Fundamental Diagram ◽  
Macroscopic Fundamental Diagram ◽  
State Estimations

The well-known Lighthill-Whitham-Richards (LWR) theory is the fundamental pillar for most macroscopic traffic models. In the past, many methods were developed to numerically derive solutions for LWR problems. Examples for such numerical solution schemes are the cell transmission model, the link transmission model, and the variational theory (VT) of traffic flow. So far, the latter framework found applications in the fields of traffic modelling, macroscopic fundamental diagram estimation, multi-modal traffic analyses, and data fusion. However, these studies apply VT only at the link or corridor level. To the best of our knowledge, there is no methodology yet to apply VT at the network level. We address this gap by developing a VT-based framework applicable to networks. Our model allows us to account for source terms (e.g. inflows and outflows at intersections) and the propagation of spillbacks between adjacent corridors consistent with kinematic wave theory. We show that the trajectories extracted from a microscopic simulation fit the predicted traffic states from our model for a simple intersection with both source terms and spillbacks. We also use this simple example to illustrate the accuracy of the proposed model. Additionally, we apply our model to the Sioux Falls network and again compare the results to those from a microscopic simulation. Our results indicate a close fit of traffic states, but with substantially lower computational cost. The developed methodology is useful for network-wide traffic state estimations in real-time, or other applications within a model-based optimization framework.

scholarly journals On the application of variational theory on networks

2020 ◽  
Author(s):  
Gabriel Tilg ◽  
Lukas Ambühl ◽  
S. F. A. Batista ◽  
Fritz Busch ◽  
Monica Menendez
Keyword(s):  
Computational Cost ◽  
Wave Theory ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Source Terms ◽  
Variational Theory ◽  
Microscopic Simulation ◽  
Fundamental Diagram ◽  
Macroscopic Fundamental Diagram ◽  
State Estimations

The well-known Lighthill-Whitham-Richards (LWR) theory is the fundamental pillar for most macroscopic traffic models. In the past, many methods were developed to numerically derive solutions for LWR problems. Examples for such numerical solution schemes are the cell transmission model, the link transmission model, and the variational theory (VT) of traffic flow. So far, the latter framework found applications in the fields of traffic modelling, macroscopic fundamental diagram estimation, multi-modal traffic analyses, and data fusion. However, these studies apply VT only at the link or corridor level. To the best of our knowledge, there is no methodology yet to apply VT at the network level. We address this gap by developing a VT-based framework applicable to networks. Our model allows us to account for source terms (e.g. inflows and outflows at intersections) and the propagation of spillbacks between adjacent corridors consistent with kinematic wave theory. We show that the trajectories extracted from a microscopic simulation fit the predicted traffic states from our model for a simple intersection with both source terms and spillbacks. We also use this simple example to illustrate the accuracy of the proposed model. Additionally, we apply our model to the Sioux Falls network and again compare the results to those from a microscopic simulation. Our results indicate a close fit of traffic states, but with substantially lower computational cost. The developed methodology is useful for network-wide traffic state estimations in real-time, or other applications within a model-based optimization framework.

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