Dynamic Analysis of Traffic State and Congestion Propagation on Bidirectional Grid Network

Discrete Dynamics in Nature and Society ◽

10.1155/2013/165086 ◽

2013 ◽

Vol 2013 ◽

pp. 1-7 ◽

Cited By ~ 2

Author(s):

Shu-bin Li ◽

Bai-bai Fu ◽

Jian-feng Zheng

Keyword(s):

Traffic Congestion ◽

Traffic Management ◽

Network Performance ◽

Simulation Software ◽

Urban Traffic ◽

Grid Network ◽

Traffic State ◽

Proposed Model ◽

Air Pollutions ◽

Density Relationship

Many traffic problems in China such as traffic jams and air pollutions are mainly caused by the increasing traffic volume. In order to alleviate the traffic congestion and improve the network performance, the analysis of traffic state and congestion propagation has attracted a great interest. In this paper, an improved mesoscopic traffic flow model is proposed to capture the speed-density relationship on segments, the length of queue, the flow on links, and so forth, The self-developed dynamic traffic simulation software (DynaCHINA) is used to reproduce the traffic congestion and propagation in a bidirectional grid network for different demand levels. The simulation results show that the proposed model and method are capable of capturing the real traffic states. Hence, our results can provide decision supports for the urban traffic management and planning.

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Urban Wasteful Transport and Its Estimation Methods

Sustainability ◽

10.3390/su10124562 ◽

2018 ◽

Vol 10 (12) ◽

pp. 4562 ◽

Cited By ~ 1

Author(s):

Xiangyang Cao ◽

Bingzhong Zhou ◽

Qiang Tang ◽

Jiaqi Li ◽

Donghui Shi

Keyword(s):

Traffic Flow ◽

Traffic Congestion ◽

Transport Theory ◽

Road Traffic ◽

Urban Traffic ◽

Flow Density ◽

Urban Road ◽

Road Capacity ◽

Density Relationship

The paper studies urban road traffic problems from the perspective of resource science. The resource composition of urban road traffic system is analysed, and the road network is proved as a scarce resource in the system resource combination. According to the role of scarce resources, the decisive role of road capacity in urban traffic is inferred. Then the new academic viewpoint of “wasteful transport” was proposed. Through in-depth research, the paper defines the definition of wasteful transport and expounds its connotation. Through the flow-density relationship analysis of urban road traffic survey data, it is found that there is a clear boundary between normal and wasteful transport in urban traffic flow. On the basis of constructing the flow-density relationship model of road traffic, combined with investigation and analysis, the quantitative estimation method of wasteful transport is established. An empirical study on the traffic conditions of the Guoding section of Shanghai shows that there is wasteful transport and confirms the correctness of the wasteful transport theory and method. The research of urban wasteful transport also reveals that: (1) urban road traffic is not always effective; (2) traffic flow exceeding road capacity is wasteful transport, and traffic demand beyond the capacity of road capacity is an unreasonable demand for customers; (3) the explanation that the traffic congestion should apply the comprehensive theory of traffic engineering and resource economics; and (4) the wasteful transport theory and method may be one of the methods that can be applied to alleviate traffic congestion.

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Traffic Efficiency Models for Urban Traffic Management Using Mobile Crowd Sensing: A Survey

Sustainability ◽

10.3390/su132313068 ◽

2021 ◽

Vol 13 (23) ◽

pp. 13068

Author(s):

Akbar Ali ◽

Nasir Ayub ◽

Muhammad Shiraz ◽

Niamat Ullah ◽

Abdullah Gani ◽

...

Keyword(s):

Traffic Congestion ◽

Traffic Management ◽

Low Cost ◽

Urban Traffic ◽

Traffic Data ◽

Mobile Crowdsensing ◽

Traffic Efficiency ◽

Crowd Sensing ◽

Management Schemes ◽

Mobile Crowd

The population is increasing rapidly, due to which the number of vehicles has increased, but the transportation system has not yet developed as development occurred in technologies. Currently, the lowest capacity and old infrastructure of roads do not support the amount of vehicles flow which cause traffic congestion. The purpose of this survey is to present the literature and propose such a realistic traffic efficiency model to collect vehicular traffic data without roadside sensor deployment and manage traffic dynamically. Today’s urban traffic congestion is one of the core problems to be solved by such a traffic management scheme. Due to traffic congestion, static control systems may stop emergency vehicles during congestion. In daily routine, there are two-time slots in which the traffic is at peak level, which causes traffic congestion to occur in an urban transportation environment. Traffic congestion mostly occurs in peak hours from 8 a.m. to 10 a.m. when people go to offices and students go to educational institutes and when they come back home from 4 p.m. to 8 p.m. The main purpose of this survey is to provide a taxonomy of different traffic management schemes for avoiding traffic congestion. The available literature categorized and classified traffic congestion in urban areas by devising a taxonomy based on the model type, sensor technology, data gathering techniques, selected road infrastructure, traffic flow model, and result verification approaches. Consider the existing urban traffic management schemes to avoid congestion and to provide an alternate path, and lay the foundation for further research based on the IoT using a Mobile crowd sensing-based traffic congestion control model. Mobile crowdsensing has attracted increasing attention in traffic prediction. In mobile crowdsensing, the vehicular traffic data are collected at a very low cost without any special sensor network infrastructure deployment. Mobile crowdsensing is very popular because it can transmit information faster, collect vehicle traffic data at a very low cost by using motorists’ smartphone or GPS vehicular embedded sensor, and it is easy to install, requires no special network deployment, has less maintenance, is compact, and is cheaper compared to other network options.

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Optimalisasi Manajemen Lalu Lintas Kawasan Jenderal Sudirman Kota Salatiga

Wahana Teknik Sipil: Jurnal Pengembangan Teknik Sipil ◽

10.32497/wahanats.v24i2.1729 ◽

2019 ◽

Vol 24 (2) ◽

pp. 117

Author(s):

Rahadian Pradipta ◽

Bambang Haryadi ◽

Ismiyati Ismiyati

Keyword(s):

Scenario Analysis ◽

Traffic Congestion ◽

Traffic Management ◽

Management Strategy ◽

Network Performance ◽

Degree Of Saturation ◽

Banking Services ◽

The Road ◽

Traditional Markets

The Jenderal Sudirman area has a strategic function as a trade and service area that gives strong character in the Salatiga. The growth of trade and service activities has increased to become a regional trading area that is influenced by modern trade. With the existence of modern shopping centers, five-star hotels, banking services beside the existing traditional markets affect the increasement of activities. The high intensity of activities raises problems related to traffic congestion. The purpose of this research is to determine the performance of the road network in the Jenderal Sudirman area and formulate a traffic management strategy to deal with the current traffic problems. This research was conducted by analyzing the existing conditions. The method of calculating volume, degree of saturation, and speed used is MKJI 1997. This study uses the SATURN 10.4 program to determine overall network performance. The results showed that the existing condition of the Jenderal Sudirman area undergone problems in Jalan Jenderal Sudirman (2 directions) with 0.86 degree of saturation. The first scenario analysis shows the value of the degree of saturation in Jalan Jenderal Sudirman dropped to 0.55; The Second scenario analysis to 0.90; and the third scenario analysis becomes 0.98. As for the overall network performance, first scenario has advantages on 3 indicators, namely average speed, passenger car unit(pcu)-hour, pcu-rupiah. Based on the overall analysis, a concept of handling traffic problems can be arranged by applying the traffic management strategy first scenario and second scenario through the short-term and long-term stages.

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KINERJA MANAJEMEN LALU LINTAS BARU DI KAWASAN LOSARI KOTA MAKASSAR

Jurnal Transportasi ◽

10.26593/jtrans.v20i1.3854.37-46 ◽

2020 ◽

Vol 20 (1) ◽

pp. 37-46

Author(s):

Qadriathi Dg Bau ◽

Ichsan Ali ◽

Nurul Tri Ayu Reski

Keyword(s):

Traffic Congestion ◽

Traffic Management ◽

Negative Impact ◽

Service Level ◽

Urban Traffic ◽

Management Service ◽

Traffic Conditions ◽

Management Scheme ◽

The Government ◽

Main Thing

Abstract The problem of urban traffic congestion is the main thing that always gets attention because congestion has a negative impact on the economy, the environment, and vehicle drivers. Makassar City is one of the cities experiencing traffic congestion on several existing roads, including roads in the Losari Area. Various efforts have been made by the government to reduce traffic congestion in the area, but optimum results have not been obtained. In 2019, a change in the direction of traffic movement in the Losari area was done by implementing a traffic management called the New Traffic Management. Through this new scheme, changes are made in the direction of movement of traffic on Jalan Penghibur, Jalan Haji Bau, and Jalan Lamadukelleng. This study aims to analyze the performance of the New Traffic Management towards improving traffic conditions in the Losari Area. The results of this study indicate that the application of New Traffic Management in the Losari Area has succeeded in improving traffic conditions in the area. Through this new traffic management scheme, the three road sections observed have service level A. Keywords: traffic congestion, traffic management, service level Abstrak Masalah kemacetan lalu lintas di perkotaan merupakan hal utama yang selalu mendapat perhatian karena kemacetan menimbulkan dampak negatif terhadap ekonomi, lingkungan, dan pengemudi kendaraan. Kota Makassar merupakan salah satu kota yang mengalami kemacetan lalu lintas di beberapa ruas jalan yang ada, termasuk jalan-jalan di kawasan Losari. Berbagai upaya telah dilakukan oleh pemerintah untuk mengurangi kemacetan lalu lintas di kawasan tersebut, tetapi belum diperoleh hasil yang optimum. Pada tahun 2019, dilakukan perubahan arah pergerakan lalu lintas di kawasan Losari dengan menerapkan suatu manajemen lalu lintas yang dinamakan Manajemen Lalu Lintas Baru atau New Traffic Management. Melalui skema yang baru ini dilakukan perubahan arah pergerakan lalu lintas di Jalan Penghibur, Jalan Haji Bau, dan Jalan Lamadu-kelleng. Penelitian ini bertujuan menganalisis kinerja Manajemen Lalu Lintas Baru ini terhadap perbaikan kondisi lalu lintas di kawasan Losari. Hasil studi ini menunjukkan bahwa penerapan Manajemen Lalu Lintas Baru di kawasan Losari berhasil memperbaiki kondisi lalu lintas di kawasan tersebut. Melalui skema manajemen lalu lintas yang baru ini, ketiga ruas jalan yang diamati mempunyai tingkat pelayanan A. Kata-kata kunci: kemacetan lalu lintas, manajemen lalu lintas, tingkat pelayanan

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Research and Strategy of Urban Traffic Congestion Control

Urban Transportation & Construction ◽

10.18686/utc.v6i2.87 ◽

2020 ◽

Vol 6 (2) ◽

pp. 34

Author(s):

Zhiran Wang

Keyword(s):

Congestion Control ◽

Public Transportation ◽

Traffic Congestion ◽

Traffic Management ◽

Urban Traffic ◽

Management Level ◽

Long Time ◽

Traffic Congestion Control ◽

Supply Capacity ◽

Restrictive Measures

With the acceleration of urbanization, urban public transportation has been developed and improved for a long time as well. Currently, China’s traditional and single ground transportation system has been transformed into a multi-functional and compound multi-transportation one. However, the congestion problem in cities has become increasingly serious. Cities in different countries should take different measures to implement the accumulation pole. They also should focus on energy source consumption, environmental pollution and health care brought by traffic congestion. The practice and research countermeasures of relieving urban traffic congestion can be divided into developmental, managerial and restrictive measures. Urban traffic congestion is a systematic problem, which needs to be treated by comprehensive measures, and given priority to the use of developmental measures in order to improve urban traffic supply capacity. It is necessary to strive to enhance urban traffic management level, practice administrative measures. With historical basis, development level and fairness of urban development in China need to be taken into account, and carefully consider the use of restrictive measures.Research and Strategy of Urban Traffic Congestion Control

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Optimal Design of Signal Controlled Road Networks Using Differential Evolution Optimization Algorithm

Mathematical Problems in Engineering ◽

10.1155/2013/696374 ◽

2013 ◽

Vol 2013 ◽

pp. 1-11 ◽

Cited By ~ 6

Author(s):

Huseyin Ceylan

Keyword(s):

Differential Evolution ◽

Optimization Algorithm ◽

Performance Index ◽

Traffic Congestion ◽

Network Performance ◽

Harmony Search ◽

User Equilibrium ◽

Simulation Software ◽

Computational Time ◽

Stochastic User Equilibrium

This study proposes a traffic congestion minimization model in which the traffic signal setting optimization is performed through a combined simulation-optimization model. In this model, the TRANSYT traffic simulation software is combined with Differential Evolution (DE) optimization algorithm, which is based on the natural selection paradigm. In this context, the EQuilibrium Network Design (EQND) problem is formulated as a bilevel programming problem in which the upper level is the minimization of the total network performance index. In the lower level, the traffic assignment problem, which represents the route choice behavior of the road users, is solved using the Path Flow Estimator (PFE) as a stochastic user equilibrium assessment. The solution of the bilevel EQND problem is carried out by the proposed Differential Evolution and TRANSYT with PFE, the so-called DETRANSPFE model, on a well-known signal controlled test network. Performance of the proposed model is compared to that of two previous works where the EQND problem has been solved by Genetic-Algorithms- (GAs-) and Harmony-Search- (HS-) based models. Results show that the DETRANSPFE model outperforms the GA- and HS-based models in terms of the network performance index and the computational time required.

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The Analysis of Characterization of Urban Traffic Congestion Based on Mixed Speed Distribution of Taxi GPS Data

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.241-244.2076 ◽

2012 ◽

Vol 241-244 ◽

pp. 2076-2081 ◽

Cited By ~ 2

Author(s):

Shou Feng Lu ◽

Yan Hui Mai ◽

Xi Min Liu

Keyword(s):

Probability Density ◽

Density Estimation ◽

Traffic Congestion ◽

Traffic Management ◽

Gaussian Model ◽

Urban Traffic ◽

Gaussian Kernel ◽

Gps Data ◽

Speed Distribution

The taxi with GPS is an efficient measure for detecting traffic condition. It is often called as floating car or moving detector. The aim of the paper is to estimate the characterization of urban traffic congestion based on taxi GPS data. Owing to the various factors including signal control, heterogeneous driver behavior, various vehicle performance, speed distribution of urban traffic is the typical mixed distribution. Based on this understanding, the paper firstly used kernel density estimation technique to estimate the probability density of mixed speed distribution. This method was a non-parametric probability density estimation method. Under the precondition that Gaussian kernel obtained the good fit quality, the paper used mixed Gaussian model to analyze the characterization of the congestion. By mixed Gaussian model, the paper obtained the numerical index including the mean, variance, weight. The example shows that we can estimate the characterization of urban traffic congestion using the paper's method. The results are important for designing traffic management plan for different scenarios and evaluating the performance of traffic management facilities.

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Urban Safety: An Image-Processing and Deep-Learning-Based Intelligent Traffic Management and Control System

Sensors ◽

10.3390/s21227705 ◽

2021 ◽

Vol 21 (22) ◽

pp. 7705

Author(s):

Selim Reza ◽

Hugo S. Oliveira ◽

José J. M. Machado ◽

João Manuel R. S. Tavares

Keyword(s):

Image Processing ◽

Deep Learning ◽

Traffic Management ◽

Resource Constraints ◽

Urban Traffic ◽

Signal Control ◽

Traffic State ◽

Wide Range ◽

Intersection Signal Control ◽

And Control

With the rapid growth and development of cities, Intelligent Traffic Management and Control (ITMC) is becoming a fundamental component to address the challenges of modern urban traffic management, where a wide range of daily problems need to be addressed in a prompt and expedited manner. Issues such as unpredictable traffic dynamics, resource constraints, and abnormal events pose difficulties to city managers. ITMC aims to increase the efficiency of traffic management by minimizing the odds of traffic problems, by providing real-time traffic state forecasts to better schedule the intersection signal controls. Reliable implementations of ITMC improve the safety of inhabitants and the quality of life, leading to economic growth. In recent years, researchers have proposed different solutions to address specific problems concerning traffic management, ranging from image-processing and deep-learning techniques to forecasting the traffic state and deriving policies to control intersection signals. This review article studies the primary public datasets helpful in developing models to address the identified problems, complemented with a deep analysis of the works related to traffic state forecast and intersection-signal-control models. Our analysis found that deep-learning-based approaches for short-term traffic state forecast and multi-intersection signal control showed reasonable results, but lacked robustness for unusual scenarios, particularly during oversaturated situations, which can be resolved by explicitly addressing these cases, potentially leading to significant improvements of the systems overall. However, there is arguably a long path until these models can be used safely and effectively in real-world scenarios.

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Methods for estimating vehicle queues at a marine terminal: A computational comparison

International Journal of Applied Mathematics and Computer Science ◽

10.2478/amcs-2014-0044 ◽

2014 ◽

Vol 24 (3) ◽

pp. 611-619 ◽

Cited By ~ 3

Author(s):

Gang Chen ◽

Zhong-Zhen Yang

Keyword(s):

Queue Length ◽

Simulation Software ◽

Urban Traffic ◽

Estimation Accuracy ◽

Estimation Model ◽

Advantages And Disadvantages ◽

Natural Logarithm ◽

Length Estimation ◽

Proposed Model ◽

Simulation Based

Abstract A long queue of vehicles at the gate of a marine terminal is a common traffic phenomenon in a port-city, which sometimes causes problems in urban traffic. In order to be able to solve this issue, we firstly need accurate models to estimate such a vehicle queue length. In this paper, we compare the existing methods in a case study, and evaluate their advantages and disadvantages. Particularly, we develop a simulation-based regression model, using the micro traffic simulation software PARAMIC. In simulation, it is found that the queue transient process follows a natural logarithm curve. Then, based on these curves, we develop a queue length estimation model. In the numerical experiment, the proposed model exhibits better estimation accuracy than the other existing methods

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Presentation of a Novel Method for Prediction of Traffic with Climate Condition Based on Ensemble Learning of Neural Architecture Search (NAS) and Linear Regression

Complexity ◽

10.1155/2021/8500572 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Javad Artin ◽

Amin Valizadeh ◽

Mohsen Ahmadi ◽

Sathish A. P. Kumar ◽

Abbas Sharifi

Keyword(s):

Linear Regression ◽

Ensemble Learning ◽

Traffic Congestion ◽

Traffic Management ◽

Absolute Humidity ◽

Urban Traffic ◽

Dew Point ◽

The Other ◽

A Value ◽

A Minor

Traffic prediction is critical to expanding a smart city and country because it improves urban planning and traffic management. This prediction is very challenging due to the multifactorial and random nature of traffic. This study presented a method based on ensemble learning to predict urban traffic congestion based on weather criteria. We used the NAS algorithm, which in the output based on heuristic methods creates an optimal model concerning input data. We had 400 data, which included the characteristics of the day’s weather, including six features: absolute humidity, dew point, visibility, wind speed, cloud height, and temperature, which in the final column is the urban traffic congestion target. We have analyzed linear regression with the results obtained in the project; this method was more efficient than other regression models. This method had an error of 0.00002 in terms of MSE criteria and SVR, random forest, and MLP methods, which have error values of 0.01033, 0.00003, and 0.0011, respectively. According to the MAE criterion, this method has a value of 0.0039. The other methods have obtained values of 0.0850, 0.0045, and 0.027, respectively, which show that our proposed model has a minor error than other methods and has been able to outpace the other models.

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