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

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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Mobile Crowd Sensing Based Dynamic Traffic Efficiency Framework for Urban Traffic Congestion Control

Sustainable Computing Informatics and Systems ◽

10.1016/j.suscom.2021.100608 ◽

2021 ◽

pp. 100608

Author(s):

Akbar Ali ◽

Muhammad Ahsan Qureshi ◽

Muhammad Shiraz ◽

Azra Shamim

Keyword(s):

Congestion Control ◽

Traffic Congestion ◽

Urban Traffic ◽

Dynamic Traffic ◽

Mobile Crowd Sensing ◽

Traffic Efficiency ◽

Crowd Sensing ◽

Traffic Congestion Control ◽

Mobile Crowd

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Evaluation of the Applicability of the Ramp Metering to a Freeway Using Microsimulation: A Case Study in Riyadh, Saudi Arabia

Applied Sciences ◽

10.3390/app9204406 ◽

2019 ◽

Vol 9 (20) ◽

pp. 4406

Author(s):

Seongkwan Lee ◽

Amr Shokri ◽

Abdullah Al-Mansour

Keyword(s):

Saudi Arabia ◽

Traffic Congestion ◽

Traffic Management ◽

Fixed Time ◽

Ramp Metering ◽

Traffic Data ◽

Geometrical Data ◽

Overall Performance ◽

Length Reduction

Riyadh, the capital of Saudi Arabia, suffers from traffic congestion like other modern societies, during peak hours but also all day long, even without any incidents. To solve this horrible traffic congestion problem, various efforts have been made from the Active Traffic Management (ATM) aspect. Ramp metering (RM) is one of the representative methods of the ATM and has already proven its value in many locations worldwide. Unfortunately, RM has not yet been fully implemented in Saudi Arabia. This research aimed to assess the applicability of RM to a freeway in Riyadh using microsimulation. The widely known software VISSIM (PTV Planung Transport Verkehr AG, Germany, 1992) was chosen to compare the performances of various RM operating scenarios, such as fixedtime operation with different sub-scenarios and traffic-responsive operation using ALINEA (Asservissement Lineaire d’entree Autoroutiere) algorithm. For the simulations, this study targeted Makkah Road, one of the major freeways in Riyadh, and collected geometrical data and traffic data from that freeway. Analysis of four main scenarios and eight sub-scenarios, proved that overall performance of the fixed-time RM operation is generally good. The sub-scenario 4V3R of the fixed-time RM operation was the best in average queue length reduction. However, the traffic-responsive operation was best in average speed improvement.

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Smart and Connected Cities Through Technologies

Advances in Civil and Industrial Engineering - Big Data Analytics for Smart and Connected Cities ◽

10.4018/978-1-5225-6207-8.ch001 ◽

2019 ◽

pp. 1-24 ◽

Cited By ~ 5

Author(s):

Vrushali Gajanan Kadam ◽

Sharvari Chandrashekhar Tamane ◽

Vijender Kumar Solanki

Keyword(s):

Big Data ◽

Traffic Congestion ◽

Smart City ◽

Smart Cities ◽

Big Data Analytics ◽

Crowd Sensing ◽

The World ◽

Important Challenge ◽

Mobile Crowd

The world is growing and energy conservation is a very important challenge for the engineering domain. The emergence of smart cities is one possible solution for the same, as it claims that energy and resources are saved in the smart city infrastructure. This chapter is divided into five sections. Section 1 gives the past, present, and future of the living style. It gives the representation from rural, urban, to smart city. Section 2 gives the explanations of four pillars of big data, and through grid, a big data analysis is presented in the chapter. Section 3 started with the case study on smart grid. It comprises traffic congestion and their prospective solution through big data analytics. Section 4 starts from the mobile crowd sensing. It discusses a good elaboration on crowd sensing whereas Section 5 discusses the smart city approach. Important issues like lighting, parking, and traffic were taken into consideration.

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Detection of Road Traffic Anomalies Based on Computational Data Science

10.21203/rs.3.rs-1149975/v1 ◽

2022 ◽

Author(s):

Jamal Raiyn

Keyword(s):

Traffic Congestion ◽

Autonomous Vehicles ◽

Data Science ◽

Road Traffic ◽

Smart Devices ◽

Traffic Data ◽

Forecasting Accuracy ◽

Traffic Efficiency ◽

Computational Data

Abstract The development of 5G has enabled the autonomous vehicles (AVs) to have full control over all functions. The AV acts autonomously and collects travel data based on various smart devices and sensors, with the goal of enabling it to operate under its own power. However, the collected data is affected by several sources that degrade the forecasting accuracy. To manage large amounts of traffic data in different formats, a computational data science approach (CDS) is proposed. The computational data science scheme introduced to detect anomalies in traffic data that negatively affect traffic efficiency. The combination of data science and advanced artificial intelligence techniques, such as deep leaning provides higher degree of data anomalies detection which leads to reduce traffic congestion and vehicular queuing. The main contribution of the CDS approach is summarized in detection of the factors that caused data anomalies early to avoid long- term traffic congestions. Moreover, CDS indicated a promoting results in various road traffic scenarios.

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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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A node optimization model based on the spatiotemporal characteristics of the road network for urban traffic mobile crowd sensing

Vehicular Communications ◽

10.1016/j.vehcom.2021.100383 ◽

2021 ◽

pp. 100383

Author(s):

Haiyang Yu ◽

Jing Fang ◽

Shuai Liu ◽

Yilong Ren ◽

Jian Lu

Keyword(s):

Optimization Model ◽

Road Network ◽

Urban Traffic ◽

Mobile Crowd Sensing ◽

The Road ◽

Model Based ◽

Spatiotemporal Characteristics ◽

Crowd Sensing ◽

Mobile Crowd

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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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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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