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 Exploring Traffic Congestion on Urban Expressways Considering Drivers' Unreasonable Behavior at Merge/Diverge Sections

2018 ◽  
Author(s):  
Kejun Long ◽  
Qin Lin ◽  
Jian Gu ◽  
Wei Wu
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Queue Length ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Spatiotemporal Evolution ◽  
Lane Changing ◽  
Road Design ◽  
Urban Expressway ◽  
Road Geometry

Mechanism of traffic congestion generation is more than complicated, due to complex geometric road design and complicated driving behavior at urban expressway in China. We employ Cell transmission model (CTM) to simulate traffic flow spatiotemporal evolution process along the expressway, and reveal the characteristics of traffic congestion occurrence and propagation. Here we apply the variable-length-cell CTM to adapt the complicated road geometry and configuration, and propose the merge section CTM considering drivers' mandatory lane-changing and other unreasonable behavior at on-ramp merge section, and propose the diverge section CTM considering queue length end extending expressway mainline to generate dynamic bottleneck at diverge section. In the new improved CTM model, we introduce merge ratio and diverge ratio to describe the effect of driver behavior at merge and diverge section. We conduct simulation on the real urban expressway in China, results show that merge section and diverge section are the original location of expressway traffic congestion generation, on/off-ramp traffic flow has great effect on expressway mainline operation. When on-ramp traffic volume increases by 40%, merge section delay increases by 35%. And when off-ramp capacity increases by 100 veh/hr, diverge section delay decreases about by 10%, which proves the strong interaction between expressway and adjacent road networks . Our results provide the underlying insights of traffic congestion mechanism in urban expressway in China, which can be used to better understand and manage this issue.

scholarly journals Exploring Traffic Congestion on Urban Expressways Considering Drivers’ Unreasonable Behavior at Merge/Diverge Sections in China

2018 ◽  
Vol 10 (12) ◽  
pp. 4359 ◽  
Author(s):  
Kejun Long ◽  
Qin Lin ◽  
Jian Gu ◽  
Wei Wu ◽  
Lee D. Han
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Queue Length ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Spatiotemporal Evolution ◽  
Lane Changing ◽  
Urban Expressway ◽  
Road Geometry ◽  
A Cell

The mechanisms of traffic congestion generation are more than complicated, due to complex geometric road designs and complicated driving behavior at urban expressways in China. We employ a cell transmission model (CTM) to simulate the traffic flow spatiotemporal evolution process along the expressway, and reveal the characteristics of traffic congestion occurrence and propagation. Here, we apply the variable-length-cell CTM to adapt the complicated road geometry and configuration, and propose the merge section CTM considering drivers’ mandatory lane-changing and other unreasonable behavior at the on-ramp merge section, and propose the diverge section CTM considering queue length end extending the expressway mainline to generate a dynamic bottleneck at the diverge section. In the new improved CTM model, we introduce merge ratio and diverge ratio to describe the effect of driver behavior at the merge and diverge section. We conduct simulations on the real urban expressway in China, with results showing that the merge section and diverge section are the original location of expressway traffic congestion generation, and on/off-ramp traffic flow has a great effect on the expressway mainline operation. When on-ramp traffic volume increases by 40%, the merge section delay increases by 35%, and when off-ramp capacity increases by 100 veh/hr, the diverge section delay decreases about by 10%, which proves the strong interaction between expressway and adjacent road networks. Our results provide the underlying insights of traffic congestion mechanism in urban expressway in China, which can be used to better understand and manage this issue.

scholarly journals Research on Analysis Method of Traffic Congestion Mechanism Based on Improved Cell Transmission Model

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Hongzhao Dong ◽  
Shuai Ma ◽  
Mingfei Guo ◽  
Dongxu Liu
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Road Network ◽  
Simulation Experiment ◽  
Transmission Model ◽  
Spatial Diffusion ◽  
Cell Transmission Model ◽  
Analysis Method ◽  
Proposed Model ◽  
Cell Transmission

To analyze the spreading regularity of the initial traffic congestion, the improved cell transmission model (CTM) is proposed to describe the evolution mechanism of traffic congestion in regional road grid. Ordinary cells and oriented cells are applied to render the crowd roads and their adjacent roads. Therefore the traffic flow could be simulated by these cells. Resorting to the proposed model, the duration of the initial traffic congestion could be predicted and the subsequent secondary congestion could be located. Accordingly, the spatial diffusion of traffic congestion could be estimated. At last, taking a road network region of Hangzhou city as an example, the simulation experiment is implemented to verify the proposed method by PARAMICS software. The result shows that the method could predict the duration of the initial congestion and estimate its spatial diffusion accurately.

scholarly journals Temporal-Spatial Analysis of Traffic Congestion Based on Modified CTM

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Chenglong Chu ◽  
Na Xie ◽  
Xiqun Chen ◽  
Yuxin Wu ◽  
Xiaoxiao Sun
Keyword(s):  
Traffic Congestion ◽  
Regression Models ◽  
Piecewise Linear ◽  
Transmission Model ◽  
Spatial Evolution ◽  
Cell Transmission Model ◽  
Linear Regression Models ◽  
Piecewise Linear Regression ◽  
Relationship Of ◽  
The Relationship

A modified cell transmission model (CTM) is proposed to depict the temporal-spatial evolution of traffic congestion on urban freeways. Specifically, drivers’ adaptive behaviors and the corresponding influence on traffic flows are emphasized. Two piecewise linear regression models are proposed to describe the relationship of flow and density (occupancy). Several types of cellular connections are designed to depict urban rapid roads with on/off-ramps and junctions. Based on the data collected on freeway of Queen Elizabeth, Ontario, Canada, we show that the new model provides a relatively higher accuracy of temporal-spatial evolution of traffic congestions.

scholarly journals Airspace Capacity Assessment with Augmented Cell Transmission Model

2021 ◽  
Author(s):  
Wei Gao ◽  
Man Liang
Keyword(s):  
Air Traffic ◽  
Mixed Integer ◽  
Transmission Model ◽  
Capacity Assessment ◽  
Fast Time ◽  
Cell Transmission Model ◽  
Traffic Demand ◽  
Airport Capacity ◽  
Cell Transmission ◽  
The Impact

Air traffic congestion is caused by the unbalance between increasing traffic demand and saturating capacity. Flight delay not only causes huge economical lost, but also has very negative environmental impact in the whole air transportation system. In order to identify the impact of extended TMA on airport capacity, an airspace capacity assessment method based on augmented cell transmission model was proposed. Firstly, the airspace structure was modeled with points, segments, layers, and cells. Secondly, mixed integer linear programming model was built up with maximum throughput or capacity as the objective function. Finally, genetic algorithm was used to find the optimal result, and the results were validated by comparing with the fast-time simulation results generated by total airspace and airport modeler (TAAM) software. It is found that the proposed method could achieve a relatively accurate result in a much affordable and fast way. The numerical results could be very helpful for air traffic controllers to analyze the dynamic traffic flow entering and exiting TMA, so as to make decisions via reasonable analysis and do planning in advance by referring to the airport capacity.

Freeway Ramp Metering Based on Cell Transmission Model and Single Neuron

2013 ◽  
Vol 423-426 ◽  
pp. 2877-2881
Author(s):  
Yan Di Ye ◽  
Yan Yan Liu ◽  
Xin Rong Liang ◽  
Chao Jun Dong
Keyword(s):  
Traffic Congestion ◽  
Single Neuron ◽  
Learning Algorithm ◽  
Ramp Metering ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Freeway Traffic ◽  
Tracking Process ◽  
Cell Transmission ◽  
Control Objective

In this work, we apply single neuron method to relieve freeway traffic congestion. We consider a freeway composed of cells and entry/exit ramps, and formulate the ramp metering problem as a density tracking process. The cell transmission model (CTM) is firstly formulated and ramp control objective is determined. Based on CTM and single neuron, a freeway ramp metering system is then designed, and the learning algorithm of single neuron is given in detail. Finally, the ramp metering system is simulated in MATLAB software. The results show that this method can effectively deal with this class of control problem, and can achieve a perfect density tracking performance. This ramp metering can eliminate traffic congestion and maintain traffic flow stability.

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.

Variable speed limit strategies analysis with link transmission model on urban expressway

2018 ◽  
Vol 32 (06) ◽  
pp. 1850077 ◽  
Author(s):  
Shubin Li ◽  
Danni Cao
Keyword(s):  
Traffic Safety ◽  
Traffic Congestion ◽  
Management Strategies ◽  
Simulation Method ◽  
Average Density ◽  
Transmission Model ◽  
Speed Limit ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Urban Expressway

The variable speed limit (VSL) is a kind of active traffic management method. Most of the strategies are used in the expressway traffic flow control in order to ensure traffic safety. However, the urban expressway system is the main artery, carrying most traffic pressure. It has similar traffic characteristics with the expressways between cities. In this paper, the improved link transmission model (LTM) combined with VSL strategies is proposed, based on the urban expressway network. The model can simulate the movement of the vehicles and the shock wave, and well balance the relationship between the amount of calculation and accuracy. Furthermore, the optimal VSL strategy can be proposed based on the simulation method. It can provide management strategies for managers. Finally, a simple example is given to illustrate the model and method. The selected indexes are the average density, the average speed and the average flow on the traffic network in the simulation. The simulation results show that the proposed model and method are feasible. The VSL strategy can effectively alleviate traffic congestion in some cases, and greatly promote the efficiency of the transportation system.

scholarly journals Incentives for Ridesharing: A Case Study of Welfare and Traffic Congestion

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Changle Song ◽  
Julien Monteil ◽  
Jean-Luc Ygnace ◽  
David Rey
Keyword(s):  
Social Welfare ◽  
Traffic Congestion ◽  
Travel Demand ◽  
Transmission Model ◽  
Fixed Point Algorithm ◽  
Optimization Framework ◽  
Simulation Based ◽  
Simulation Based Optimization ◽  
The Impact

Traffic congestion is largely due to the high proportion of solo drivers during peak hours. Ridesharing, in the sense of carpooling, has emerged as a travel mode with the potential to reduce congestion by increasing the average vehicle occupancy rates and reduce the number of vehicles during commuting periods. In this study, we propose a simulation-based optimization framework to explore the potential of subsidizing ridesharing users, drivers, and riders, so as to improve social welfare and reduce congestion. We focus our attention on a realistic case study representative of the morning commute on Sydney’s M4 Motorway in Australia. We synthesize a network model and travel demand data from open data sources and use a multinomial logistic model to capture users’ preferences across different travel roles, including solo drivers, ridesharing drivers, ridesharing passengers, and a reserve option that does not contribute to congestion on the freeway network. We use a link transmission model to simulate traffic congestion on the freeway network and embed a fixed-point algorithm to equilibrate users’ mode choice in the long run within the proposed simulation-based optimization framework. Our numerical results reveal that ridesharing incentives have the potential to improve social welfare and reduce congestion. However, we find that providing too many subsidies to ridesharing users may increase congestion levels and thus be counterproductive from a system performance standpoint. We also investigate the impact of transaction fees to a third-party ridesharing platform on social welfare and traffic congestion. We observe that increasing the transaction fee for ridesharing passengers may help in mitigating congestion effects while improving social welfare in the system.

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