scholarly journals 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 ◽  
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.

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

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.

scholarly journals KINERJA MANAJEMEN LALU LINTAS BARU DI KAWASAN LOSARI KOTA MAKASSAR

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

scholarly journals Research and Strategy of Urban Traffic Congestion Control

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

<p class="MsoNormal" style="margin-bottom: 0.0000pt; text-indent: 0.0000pt; mso-layout-grid-align: none; line-height: 15.0000pt; mso-line-height-rule: exactly;"><span style="mso-spacerun: 'yes'; font-family: 'Times New Roman'; mso-fareast-font-family: 宋体; mso-font-kerning: 1.0000pt;">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.</span></p><p class="MsoNormal" style="margin-top: 70pt; margin-bottom: 8pt; text-indent: 0pt;"><strong><span style="font-family: 'Times New Roman'; font-size: 16pt;">Research and Strategy of Urban Traffic Congestion Control</span></strong><strong></strong></p>

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

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
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.

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

2012 ◽  
Vol 241-244 ◽  
pp. 2076-2081 ◽  
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.

scholarly journals Research on the Intelligent Assignment Model of Urban Traffic Planning Based on Optimal Path Optimization Algorithm

2022 ◽  
Vol 2022 ◽  
pp. 1-7
Author(s):  
Yuan Lu ◽  
Shengyong Yao ◽  
Yifeng Yao
Keyword(s):  
Growth Rate ◽  
Optimization Algorithm ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Negative Impact ◽  
Optimal Path ◽  
Urban Traffic ◽  
Path Optimization ◽  
The Road

Congestion and complexity in the field of highway transportation have risen steadily in recent years, particularly because the growth rate of vehicles has far outpaced the growth rate of roads and other transportation facilities. To ensure smooth traffic, reduce traffic congestion, improve road safety, and reduce the negative impact of air pollution on the environment, an increasing number of traffic management departments are turning to new scientifically developed technology. The urban road traffic is simulated by nodes and sidelines in this study, which is combined with graph theory, and the information of real-time changes of road traffic is added to display and calculate the relevant data and parameters in the road. On this foundation, the dynamic path optimization algorithm model is discussed in the context of high informationization. Although the improved algorithm’s optimal path may not be the conventional shortest path, its actual travel time is the shortest, which is more in line with users’ actual travel needs to a large extent.

Urban Traffic Management and Urban Planning

2012 ◽  
Vol 178-181 ◽  
pp. 1820-1823
Author(s):  
Ji Peng Liu ◽  
Zhen Xing Tang
Keyword(s):  
Urban Planning ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Construction ◽  
Urban Traffic ◽  
Traffic Planning ◽  
Land Utilization ◽  
Urban City ◽  
The Government ◽  
The City

At present, traffic problem has become one of the biggest problems about the development of urban city in China. Faced with this problem, it is important for traffic planning to keep traffic be in accordance with the city. It is a challenge to urban planning, especially to the traditional method by land utilization planning. To relieve traffic congestion and other issues blocking, we can not only enhance road construction, but also make some innovation about the new thoughts and methods for the functional departments of the government. This is the key to solve the urban traffic problem for the time being.

scholarly journals Detecting Predominance of on-Street Parking Payment Schemes by Means of Linear Regression

2020 ◽  
Vol 8 (6) ◽  
pp. 59-64
Keyword(s):  
Linear Regression ◽  
Traffic Congestion ◽  
Linear Regression Analysis ◽  
Open Data ◽  
Urban Traffic ◽  
Parking Space ◽  
Machine Learning Technique ◽  
Data Set ◽  
Learning Technique ◽  
Payment Schemes

—On street parking is one of the important and crucial components of urban traffic and transportation system. Allocation of parking space on street is major reason for traffic congestion. Optimizing traffic congestion and facilitating on street parking is a long stand issue. According to urban environment it is expected that car drivers prefers parking space based on road conditions, speed limit and surrounding activities and availability of parking space. The other major components to be ponder while searching parking space is payment method used while parking the car. This paper investigates car driver’s behaviors in selecting parking payment schemas, visualized data as well predicted via machine learning technique of linear regression analysis on the open data set of On-street Car Parking Meters with Location of City of Melbourne's in the Australian.

scholarly journals Application of Data Science Technologies in Intelligent Prediction of Traffic Congestion

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Xu Yang ◽  
Shixin Luo ◽  
Keyan Gao ◽  
Tingting Qiao ◽  
Xiaoya Chen
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Data Science ◽  
Vehicular Networks ◽  
Rapid Development ◽  
Prediction Method ◽  
Urban Traffic ◽  
Motor Vehicles ◽  
Car Accidents ◽  
Heavy Burden

In recent years, with the rapid development of economy, more and more urban residents, while owning their own motor vehicles, are also troubled by the traffic congestion caused by the backward traffic facilities or traffic management methods. The loss of productivity, car accidents, high emissions, and environmental pollution caused by traffic congestion has become a huge and increasingly heavy burden on all countries in the world. Therefore, the prediction of urban road network traffic flow and the rapid and accurate evaluation of traffic congestion are of great significance to the study of urban traffic solutions. This paper focuses on how to apply data science technologies on vehicular networks data to present a prediction method for traffic congestion based on both real-time and predicted traffic data. Two evaluation frameworks are established, and existing methods are used to compare and evaluate the accuracy and efficiency of the presented method.

Study on Traffic Multi-Source Data Fusion

2019 ◽  
Vol 13 (2) ◽  
pp. 63-75
Author(s):  
Suping Liu ◽  
Dongbo Zhang ◽  
Jialin Li
Keyword(s):  
Data Fusion ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Analysis Data ◽  
Urban Traffic ◽  
Data Sources ◽  
Flow Parameters ◽  
Fusion Methods ◽  
Single Detector

In order to alleviate urban traffic congestion, it is necessary to obtain roadway network traffic flow parameters to estimate the traffic conditions. Single-detector data may not be sufficient to obtain a comprehensive, effective, accurate and high-quality traffic flow data. Neural networks and regression analysis data fusion methods are employed to expand data sources as well as for improving data quality. The multi-source detector data can provide fundamental support for traffic management. An empirical analysis was conducted using acquisition technology employed by the Beijing urban expressway to estimate traffic flow parameters. The results show that the proposed data fusion method is feasible and provides reliable data sources.

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