scholarly journals Traffic Signal Synchronization in the Saturated High-Density Grid Road Network

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaojian Hu ◽  
Jian Lu ◽  
Wei Wang ◽  
Ye Zhirui
Keyword(s):  
Traffic Congestion ◽  
Queue Length ◽  
Road Network ◽  
Signalized Intersections ◽  
Traffic Signal ◽  
High Density ◽  
Traffic Flows ◽  
Traffic Efficiency ◽  
Signal Synchronization ◽  
Overall Performance

Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

scholarly journals Integration of Model-Based Signal Control and Queue Spillover Control for Urban Oversaturated Signalized Intersection

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Haitao Xu ◽  
Jing Chen ◽  
Jie Xu
Keyword(s):  
Predictive Control ◽  
Traffic Congestion ◽  
Road Network ◽  
Signalized Intersection ◽  
Signal Control ◽  
Control Approach ◽  
Model Based ◽  
Real Time Traffic ◽  
Overall Performance ◽  
Improved Model

An improved model-based predictive control approach integrating model-based signal control and queue spillover control is proposed in this paper, which includes three modules: model-based signal control, queue spillover identification, and spillover control to deal with the problem of traffic congestion for urban oversaturated signalized intersection. The main steps are as follows. First of all, according to the real-time traffic flow data, the green time splits for all intersections will be solved online by the model-based signal control controller whose optimization model is based on model-predictive control (MPC) strategy. Second, the queue spillover identification module will be used to detect the potential queue spillover. If potential queue spillover is detected, the spillover control module will be activated to prevent vehicles from the upstream link of the link with possible spillover from entering the downstream link to avoid traffic congestion. The experiment is performed on a simulated road network. The results verify that the proposed scheme can significantly decrease the delay which reflects the overall performance of the studied intersection.

scholarly journals Analisis kinerja simpang Ciceri Serang Banten

2018 ◽  
Author(s):  
Darmadi Ir
Keyword(s):  
Time Delay ◽  
Traffic Flow ◽  
Urban Areas ◽  
Queue Length ◽  
Road Network ◽  
Average Degree ◽  
Degree Of Saturation ◽  
Critical Area ◽  
Traffic Flows ◽  
Road Segments

Intersection is a meeting of road segments whose function is to change the direction of traffic flow. Intersection as part of a road network is a critical area in serving traffic flows. In order to support the creation of a reliable, smooth, safe, orderly and comfortable transportation system. especially in urban areas, it is necessary to do research on the crossing conditions of the four Serang city cherries. From the results of the study, the intersections of four Serang Performance Ciceri Intersection intersections are currently considered poor. This can be seen from the average degree of saturation (DS) of 0.7 pcu / hour. The average queue length reaches 33.40 meters and the average time delay is 23.34 pcu / hour (ITP E)Keywords: Fourth intersection, degree of saturation, queue length and average time delay

scholarly journals Traffic Light Optimization using OpenCV

2020 ◽  
Vol 6 (12) ◽  
pp. 171-175
Author(s):  
Aditya Lahoty
Keyword(s):  
Real Time ◽  
Waiting Time ◽  
Traffic Congestion ◽  
Computer Software ◽  
Green Light ◽  
Traffic Signals ◽  
Signalized Intersections ◽  
Traffic Signal ◽  
Traffic Light ◽  
Real Time Traffic

Traffic Light Optimization aims to find the solution for an increased amount of unnecessary waiting time on traffic signals. Traffic Signal Optimization is the process of changing the timing parameters relative to the length of the green light for each traffic movement and the timed relationship between signalized intersections using a computer software program. Our project aims to set the timer of green light based on real-time traffic congestion i.e. number of vehicles in a particular direction of the traffic light. To work in this project, we are using the OpenCV method to detect vehicles and then perform our calculation in the algorithm to predict the time for the green light to be in an active state.

scholarly journals Intelligent Traffic Signal Phase Distribution System Using Deep Q-Network

2022 ◽  
Vol 12 (1) ◽  
pp. 425
Author(s):  
Hyunjin Joo ◽  
Yujin Lim
Keyword(s):  
Control System ◽  
Standard Deviation ◽  
Traffic Congestion ◽  
Queue Length ◽  
Smart Cities ◽  
Traffic Signal ◽  
Optimal Order ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Smart Transportation

Traffic congestion is a worsening problem owing to an increase in traffic volume. Traffic congestion increases the driving time and wastes fuel, generating large amounts of fumes and accelerating environmental pollution. Therefore, traffic congestion is an important problem that needs to be addressed. Smart transportation systems manage various traffic problems by utilizing the infrastructure and networks available in smart cities. The traffic signal control system used in smart transportation analyzes and controls traffic flow in real time. Thus, traffic congestion can be effectively alleviated. We conducted preliminary experiments to analyze the effects of throughput, queue length, and waiting time on the system performance according to the signal allocation techniques. Based on the results of the preliminary experiment, the standard deviation of the queue length is interpreted as an important factor in an order allocation technique. A smart traffic signal control system using a deep Q-network , which is a type of reinforcement learning, is proposed. The proposed algorithm determines the optimal order of a green signal. The goal of the proposed algorithm is to maximize the throughput and efficiently distribute the signals by considering the throughput and standard deviation of the queue length as reward parameters.

scholarly journals Road Network Pre-partitioning Method with Priority for Congestion Control

2019 ◽  
pp. 1-13
Author(s):  
Hao She ◽  
Xingsheng Xie
Keyword(s):  
Congestion Control ◽  
Traffic Congestion ◽  
Spectral Clustering ◽  
Road Network ◽  
Control Area ◽  
Urban Traffic ◽  
The Road ◽  
Traffic Efficiency ◽  
Svm Model ◽  
Partition Method

Urban traffic congestion seriously affects the traffic efficiency, causing travel delays and resources wasted directly. In this paper, a road network pre-partitioning method with priority for congestion control is proposed to reduce traffic congestion. Traffic flow feature is extracted based on CNN, and the estimated accuracy of intersection reach 95.32% through CNN-SVM model. Subarea congestion coefficient and intersection merger coefficient are defined to expand the control area of congestion coordination. The association and similarity of intersections are considered using spectral clustering for non-congested intersection partitioning. The results show that the congestion priority control partition method reduces a congestion intersection compared to directly using spectral clustering for subarea partition, and reduces the road network congestion coefficient by 0.05 after 30 minutes than directly using spectral clustering, which is an effective subarea partition method.  

Network-Wide Optimization of Traffic Signals Using Mixed Integer Programming

2014 ◽  
Vol 26 (5) ◽  
pp. 607-615 ◽  
Author(s):  
Md. Abdus Samad Kamal ◽  
◽  
Jun-ichi Imura ◽  
Tomohisa Hayakawa ◽  
Akira Ohata ◽  
...  
Keyword(s):  
Integer Programming ◽  
Model Predictive Control ◽  
Mixed Integer Programming ◽  
Predictive Control ◽  
Road Network ◽  
Traffic Signals ◽  
Continuous Variable ◽  
Traffic Signal ◽  
Mixed Integer ◽  
Traffic Flows

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00260005/09.jpg"" width=""300"" />Network with four intersections</div> In this paper a network-wide traffic signal control scheme in a model predictive control framework using mixed integer programming is presented. A concise model of traffic is proposed to describe a signalized road network considering conservation of traffic. In the model, the traffic of two sections that belong to a traffic signal group of a junction are represented by a single continuous variable. Therefore, the number of variables required to describe traffic in the network becomes half compared with the models that describe section wise traffic flows. The traffic signal at the junction is represented by a binary variable to express a signal state either green or red. The proposed model is transformed into a mixed logical dynamical system to describe the traffic flows in a finite horizon, and traffic signals are optimized using mixed integer linear programming (MILP) for a given performance index. The scheme simultaneously optimizes all traffic signals in a network in the context of model predictive control by successively extending or terminating a green or red signal of each junction. Consequently, traffic signal patterns with the optimal free parameters, i.e., the cycle times, the split times and the offsets, are realized. Use of the proposed concise traffic model significantly reduces the computation time of the scheme without compromising the performance as it is evaluated on a small road network and compared with a previously proposed scheme. </span>

scholarly journals MODELING TRANSPORT FLOWS UNDER CONDITIONS OF A LOADED STREET-ROAD NETWORK

2020 ◽  
Vol 2020 (1) ◽  
pp. 165-165
Author(s):  
Ol'ga Lebedeva
Keyword(s):  
Travel Time ◽  
Experimental Research ◽  
Traffic Congestion ◽  
Road Network ◽  
Supply And Demand ◽  
Route Selection ◽  
Traffic Flows ◽  
Urban Networks ◽  
The Road ◽  
Modeling Transport

Managing urban networks during traffic congestion requires the use of a dynamic model that allows you to simulate real situations with traffic flows with long queues and responses. To conduct experimental research in this area, it is possible to use a mesoscopic system for simulating traffic with calibration and taking into account the characteristics of the road. All supply and demand parameters (use of detectors, travel time) must be calibrated at the same time. In this study, calibration was performed using the route selection model, given overlapping routes

OPTIMIZATION OF ROAD TRAFFICIN KRASNOYARSK

2021 ◽  
Vol 73 (2) ◽  
pp. 57-62
Author(s):  
S.V. EREMIN ◽  
Keyword(s):  
Transport System ◽  
Traffic Congestion ◽  
Road Network ◽  
Road Traffic ◽  
Traffic Flows ◽  
Transport Industry ◽  
Methodological Approaches ◽  
The City

The article deals with the issues related to improving the organization of traffic on the street and road network of the city of Krasnoyarsk. The article presents scientific and methodological approaches to improving the efficiency of traffic flows on the basis of reducing traffic congestion, increasing the speed of communication and reducing the level of accidents. The implementation of the developed approaches is carried out on the example of the transport system of the city of Kras-noyarsk. The materials presented in the article can be useful for employees of the transport industry in improving the organization of road traffic in cities and regions.

scholarly journals Simulation and analysis of non-recurrent traffic congestion triggered by crashes in road networks using a grid-based approach

2019 ◽  
Vol 11 (10) ◽  
pp. 168781401988416
Author(s):  
Sulan Li ◽  
Junqing Shi ◽  
Xiedong Zhang ◽  
Hongwei Zhu ◽  
Guolian Meng
Keyword(s):  
Traffic Congestion ◽  
Road Networks ◽  
Signalized Intersections ◽  
Practical Applications ◽  
The Road ◽  
Grid Networks ◽  
Traffic Efficiency ◽  
Incident Duration ◽  
On The Road ◽  
Network Speed

The non-recurrent traffic congestion triggered by crashes is one of the most important factors that undermine the traffic efficiency of urban road networks. In this article, an improved cellular automaton model was proposed to simulate the non-recurrent congestion triggered by crashes in grid networks with signalized intersections. Four rules were adopted to represent vehicle movements on road sections and intersections. The network speed is adopted to capture the propagation and dissipation of the non-recurrent congestion. The effect of main influencing factors of crashes on the road network was evaluated through the simulation. Simulation results showed the incident duration and areas affected by the distance between the crash point and the upstream intersection, the number of closed lanes, and the crash duration. In addition, the stop-start wave was observed in the simulation. The realistic findings from the simulations validated the model to have the potential for practical applications in the analysis of the non-recurrent congestion triggered by crashes.

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