scholarly journals Forecasting Spatiotemporal Boundary of Emergency-Event-Based Traffic Congestion in Expressway Network Considering Highway Node Acceptance Capacity

2021 ◽  
Vol 13 (21) ◽  
pp. 12195
Author(s):  
Xingliang Liu ◽  
Jian Wang ◽  
Tangzhi Liu ◽  
Jin Xu
Keyword(s):  
Wave Theory ◽  
Local Area ◽  
Volume Density ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Traffic Condition ◽  
Emergency Event ◽  
Emergency Events ◽  
Event Based ◽  
Incident Cases

Emergency eventscan induce serious traffic congestions in a local area which may propagate to the upstream roads, and even the whole network. Until now, the methodology forecasting spatiotemporal boundary propagation of emergency-event-based traffic congestions, with both explicitness and road network availability, has not been found. This study develops a new method for predicting spatiotemporal boundary of the congestion caused by emergency events, which is more applicable and practical than cell transmission model (CTM)-derived methods. This method divides the expressway network into different sections based on their functions and the shockwave direction caused by the emergency events. It characterizes the velocity of the moving congestion boundary based on kinetic wave theory and volume–density relationship. After determining whether the congestion will spread into the network level through an interchange using a new concept, highway node acceptance capacity (HNAC), we can predict the spatiotemporal boundary and corresponding traffic condition within the boundary. The proposed method is tested under four traffic incident cases with corresponding traffic data collected through field observations. We also compare its prediction performances with other methods used in the literature.

scholarly journals An Approach to Modeling the Impact of Traffic Incident on Urban Expressway

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Yaping Li ◽  
Jian Lu ◽  
HongWu Li ◽  
Huihui Xiao ◽  
Qingchao Liu
Keyword(s):  
Traffic Congestion ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Traffic Condition ◽  
Traffic Incident ◽  
Evaluation Indicator ◽  
Urban Expressway ◽  
Time Period ◽  
Foundational Work ◽  
The Impact

To identify network bottlenecks of urban expressway effectively is a foundational work for improving network traffic condition and preventing traffic congestion. This study proposes a methodology to estimate the impact of traffic incident on urban expressway on the basis of modified cell transmission model. The metastable state was taken into account in the proposed method to reflect the actual operating state of traffic flow on urban expressway as much as possible. Regarding the location of traffic incident, the method of cell restructuring settings was discussed. We then proceed to introduce a new concept of the effected length in a given time period as the evaluation indicator to directly depict the influence of traffic incident. The proposed method was tested on a 6516-meter urban expressway section of west second ring road in Beijing. The simulation results indicated that the proposed methodology performs well to predict the impact of traffic incident on urban expressway.

scholarly journals An Improved CTM Model for Urban Signalized Intersections and Exploration of Traffic Evolution

2021 ◽  
Vol 7 (2) ◽  
pp. 357-375
Author(s):  
Arlinda A. Rrecaj ◽  
Vlera Alimehaj ◽  
Marija Malenkovska ◽  
Cvetko Mitrovski
Keyword(s):  
Signalized Intersections ◽  
Traffic Signal ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Time Step ◽  
Traffic Condition ◽  
Urban Network ◽  
Congested Traffic ◽  
Proposed Model ◽  
Urban Arterials

In this paper is going to be proposed a Cell Transmission Model (CTM), its analysis and evaluation with a case study, which addresses in a detailed way the aspect of merging and diverging operations on urban arterials. All those few CTM models that have been developed so far, to model intersections, have some limitations and drawbacks. First, unlike the simple composition road networks, such as highways, urban arterials must include some complex parts called merge sand diverges, due to the fact of vibrational values of reduced capacity, reduced saturation flow rate, etc. In order to simulate an urban network/arterial it is not possible to neglect the traffic signal indication on the respective time step. The objective of this paper is to highlight the difference between the results of the original CTM and our proposed CTM and to provide evidence that the later one is better than the old one.  The proposed and formulated model will be employed through an algorithm of CTM to model a segment- arterial road of Pristina (compound from signalized intersections). For the functionalization and testing of the proposed model is build the experimental setup that is compatible with the algorithm created on C# environment. Results show that the proposed model can describe light and congested traffic condition. In light traffic conditions, in great mass traffic flow is dictated by the traffic signal status, while in medium congestion is obtained a rapid increase of the density to each cell. Fluctuations of the density from the lowest to the highest values are obvious during the first three cycles to all cells of the artery in a congested traffic state. Doi: 10.28991/cej-2021-03091659 Full Text: PDF

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.

Intelligent control of complex traffic conditions based on machine learning

2021 ◽  
pp. 1-12
Author(s):  
Zhe Li
Keyword(s):  
Machine Learning ◽  
Simulation Model ◽  
Traffic Simulation ◽  
Learning Algorithms ◽  
Control Model ◽  
Machine Learning Algorithms ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Traffic Conditions ◽  
Simulation Control

 In order to improve the simulation effect of complex traffic conditions, based on machine learning algorithms, this paper builds a simulation model. Starting from the macroscopic traffic flow LWR theory, this paper introduces the process of establishing the original CTM mathematical model, and combines it with machine learning algorithms to improve it, and establishes the variable cell transmission model VCTM ordinary transmission, split transmission, and combined transmission mathematical expressions. Moreover, this paper establishes a road network simulation model to calibrate related simulation parameters. In addition, this paper combines the actual needs of complex traffic conditions analysis to construct a complex traffic simulation control model based on machine learning, and designs a hybrid microscopic traffic simulation system architecture to simulate all relevant factors of complex road conditions. Finally, this paper designs experiments to verify the performance of the simulation model. The research results show that the simulation control model of complex traffic conditions constructed in this paper has certain practical effects.

Dynamic control cycle speed limit strategy for balanced reduction of travel time and emissions

2021 ◽  
Vol 35 (09) ◽  
pp. 2150153
Author(s):  
Minghui Ma ◽  
Yaozong Zhang ◽  
Shidong Liang
Keyword(s):  
Travel Time ◽  
Traffic Control ◽  
Dynamic Control ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Vehicle Exhaust ◽  
Environmental Benefit ◽  
Multiple Control ◽  
Total Travel Time ◽  
Co Emission

The vehicle exhaust has been one of the major sources of greenhouse gas emissions. With an increase in traffic volume, it has been found that the introduced intelligent traffic control is necessary. This paper investigated a novel VSL strategy considering the dynamic control cycle to improve the traffic efficiency and environmental benefit on freeway. An extension of the cell transmission model (CTM) was used to depict the traffic characteristics under VSL control, and integrated with the microscopic emission and fuel consumption model VT-Micro to estimate the pollution emission of each cell. The VSL strategy was designed to provide multiple control cycles with different length to adjust the scope of VSL changes, furthermore, a probability formula was developed and used to determine the optimal quantity of control cycles to reduce the computational complexity of controller. An objective optimization function was formulated with the aim of minimizing total travel time and CO emission. With simulation experiments, the results showed that the proposed VSL strategy considering the dynamic control cycle outperformed uncontrolled scenario, resulting in up to 8.4% of total travel time reductions, 26.7% of delay optimization, and 14.5% reduction in CO emission, which enhanced the service level of freeway network.

Sign in / Sign up

Export Citation Format

Share Document