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Journal articles on the topic 'Traffic Congestion Reduction'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Chaurasia, Brijesh Kumar, Wellington S. Manjoro, and Mradul Dhakar. "Traffic Congestion Identification and Reduction." Wireless Personal Communications 114, no. 2 (2020): 1267–86. http://dx.doi.org/10.1007/s11277-020-07420-0.

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2

Yang, Shuxia, Yu Ji, Di Zhang, and Jing Fu. "Equilibrium between Road Traffic Congestion and Low-Carbon Economy: A Case Study from Beijing, China." Sustainability 11, no. 1 (2019): 219. http://dx.doi.org/10.3390/su11010219.

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China has allocated low-carbon targets into all regions and trades, and road traffic also has its own emission reduction targets. Congestion may increase carbon emissions from road traffic. It is worthwhile to study whether it is possible to achieve the goal of road traffic reduction by controlling congestion; that is, to achieve the equilibrium between traffic congestion and a low-carbon economy. The innovation of this paper is mainly reflected in the innovative topic selection, the introduction of a traffic index, and the establishment of the first traffic congestion and low-carbon economic

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3

FUSE, Takashi. "Reduction of Traffic Accidents and Congestion." Journal of the Society of Mechanical Engineers 115, no. 1123 (2012): 382–83. http://dx.doi.org/10.1299/jsmemag.115.1123_382.

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4

A, Lakshna, Gokila S, Ramesh K, and Surendiran R. "Smart Traffic: Traffic Congestion Reduction by Shortest Route * Search Algorithm." International Journal of Engineering Trends and Technology 71, no. 3 (2022): 423–33. http://dx.doi.org/10.14445/22315381/ijett-v71i3p244.

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5

Wang, Li, Shimin Lin, Jingfeng Yang, et al. "Dynamic Traffic Congestion Simulation and Dissipation Control Based on Traffic Flow Theory Model and Neural Network Data Calibration Algorithm." Complexity 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/5067145.

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Traffic congestion is a common problem in many countries, especially in big cities. At present, China’s urban road traffic accidents occur frequently, the occurrence frequency is high, the accident causes traffic congestion, and accidents cause traffic congestion and vice versa. The occurrence of traffic accidents usually leads to the reduction of road traffic capacity and the formation of traffic bottlenecks, causing the traffic congestion. In this paper, the formation and propagation of traffic congestion are simulated by using the improved medium traffic model, and the control strategy of c

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6

Hafees, Mohammed, and Madhu Kavitha. "Travel Time Reduction and Driver Preferences after the Construction of Alappuzha Bypass." Journal of Transportation Engineering and Traffic Management 3, no. 1 (2022): 1–5. https://doi.org/10.5281/zenodo.6008605.

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Ring roads are considered to be the best option for reducing the traffic congestions of a city. For the cost effective movement of goods and people, these traffic congestions must be reduced. This study is mainly conducted about the Alappuzha Bypass which is recently constructed for the purpose as a ring road. It is constructed for easy travel through Alappuzha town by NH 66 and better connectivity for the town. This is built in turn to reduce the traffic congestion inside the city. Alappuzha Bypass is a part of NH 66 that bypasses traffic of Alappuzha city in Kerala, India. The 6.8 km long by

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7

Pavlović, Ratko. "Solving the problem of congestion in city centers by applying Congestion Pricing - simulation in Belgrade." Put i saobraćaj 68, no. 3 (2022): 47–54. http://dx.doi.org/10.31075/pis.68.03.07.

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The problem of traffic congestion is one of the most significant global problems in the world. Numerous negative effects of congestion affect both the users themselves and people who are not direct participants in the traffic. The most significant negative effects caused by traffic congestion are greater time losses, increased emission of harmful gases, greater number of traffic accidents, noise, etc. Congestion charging is one of the measures that affects the reduction of traffic congestion by influencing the transport requirements of users. So far, congestion charging has been implemented in

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8

Miyamoto, Kodai, Taketo Kamasaka, Makoto Sakamoto, and Tsunehiro Yoshinaga. "Basic Study on Expressway Congestion Mitigation using Cellular Automata." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 3 (2021): 164–69. http://dx.doi.org/10.35940/ijrte.c6462.0910321.

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Traffic congestion has become a serious social problem in Japan. In particular, traffic congestion causes enormous time and economic losses on expressways, which are intended to facilitate smooth traffic flow. It also causes environmental problems and a decrease in logistics efficiency, so efforts to eliminate or reduce traffic congestion are essential. The elimination and mitigation of traffic congestion on highways is a factor in reducing traffic accidents and fatalities. In recent years, with the improvement of computing capabilities, research on traffic congestion reduction and mitigation

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9

Kodai, Miyamoto, Kamasaka Taketo, Sakamoto Makoto, and Yoshinaga Tsunehiro. "Basic Study on Expressway Congestion Mitigation using Cellular Automata." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 3 (2021): 164–69. https://doi.org/10.35940/ijrte.C6462.0910321.

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Traffic congestion has become a serious social problem in Japan. In particular, traffic congestion causes enormous time and economic losses on expressways, which are intended to facilitate smooth traffic flow. It also causes environmental problems and a decrease in logistics efficiency, so efforts to eliminate or reduce traffic congestion are essential. The elimination and mitigation of traffic congestion on highways is a factor in reducing traffic accidents and fatalities. In recent years, with the improvement of computing capabilities, research on traffic congestion reduction and mitigation

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10

Gandhi, Palash, Aakash Chandrana, and Tushar Karia. "Intelligent Traffic Congestion Reduction System using Proximity Sensors." International Journal of Computer Applications 101, no. 8 (2014): 34–36. http://dx.doi.org/10.5120/17710-8720.

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11

Winchester, Alyse K., Ryan A. Peterson, Ellison Carter, and Mary D. Sammel. "Impact of COVID-19 Social Distancing Policies on Traffic Congestion, Mobility, and NO2 Pollution." Sustainability 13, no. 13 (2021): 7275. http://dx.doi.org/10.3390/su13137275.

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Lockdowns implemented during the COVID-19 pandemic were utilized to evaluate the associations between “social distancing policies” (SDPs), traffic congestion, mobility, and NO2 air pollution. Spatiotemporal linear mixed models were used on city-day data from 22 US cities to estimate the associations between SDPs, traffic congestion and mobility. Autoregressive integrated moving average models with Fourier terms were then used on historical data to forecast expected 2020 NO2. Time series models were subsequently employed to measure how much reductions in local traffic congestion were associated

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12

Moumen, Idriss, Jaafar Abouchabaka, and Najat Rafalia. "Regional feature learning using attribute structural analysis in bipartite attention framework for vehicle re-identification." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 5 (2023): 5813–23. https://doi.org/10.11591/ijece.v13i5.pp5813-5823.

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Traffic congestion prediction is one of the essential components of intelligent transport systems (ITS). This is due to the rapid growth of population and, consequently, the high number of vehicles in cities. Nowadays, the problem of traffic congestion attracts more and more attention from researchers in the field of ITS. Traffic congestion can be predicted in advance by analyzing traffic flow data. In this article, we used machine learning algorithms such as linear regression, random forest regressor, decision tree regressor, gradient boosting regressor, and K-neighbor regressor to predict tr

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13

Zhang, Jun, and Guangtong Hu. "Transformer model-based multi-scale fine-grained identification and classification of regional traffic states." PeerJ Computer Science 10 (December 18, 2024): e2625. https://doi.org/10.7717/peerj-cs.2625.

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To address the limitations in precision of conventional traffic state estimation methods, this article introduces a novel approach based on the Transformer model for traffic state identification and classification. Traditional methods commonly categorize traffic states into four or six classes; however, they often fail to accurately capture the nuanced transitions in traffic states before and after the implementation of traffic congestion reduction strategies. Many traffic congestion reduction strategies can alleviate congestion, but they often fail to effectively transition the traffic state

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Konge, Pratik Diliprao, and Madhuri Nikam. "Solution for Reduction of Traffic Congestion: A Case Study of Intersection on Badlapur- Katai Road." International Journal for Research in Applied Science and Engineering Technology 10, no. 11 (2022): 599–606. http://dx.doi.org/10.22214/ijraset.2022.47389.

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Abstract: The increasing vehicular traffic on roads is growing issue in today’s life. This leads to the congestion on the streets and degrades safe and efficient movement of traffic. This is becoming an important issue in the urban premises. It is observed that traffic congestions take place majorly at the intersections where the entering and exiting traffic from the towns to the highways creates conflicts due to improper movement. This study intended to examine flow of traffic at an intersection on Badlapur – Katai road in state of Maharashtra. The location is a part suburban areas of Mumbai

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15

Weisbrod, Glen, Don Vary, and George Treyz. "Measuring Economic Costs of Urban Traffic Congestion to Business." Transportation Research Record: Journal of the Transportation Research Board 1839, no. 1 (2003): 98–106. http://dx.doi.org/10.3141/1839-10.

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Key findings are provided from NCHRP Study 2-21, which examined how urban traffic congestion imposes economic costs within metropolitan areas. Specifically, the study applied data from Chicago and Philadelphia to examine how various producers of economic goods and services are sensitive to congestion, through its impact on business costs, productivity, and output levels. The data analysis showed that sensitivity to traffic congestion varies by industry sector and is attributable to differences in each industry sector's mix of required inputs and hence its reliance on access to skilled labor, a

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16

Kreindler, Gabriel. "Peak‐Hour Road Congestion Pricing: Experimental Evidence and Equilibrium Implications." Econometrica 92, no. 4 (2024): 1233–68. http://dx.doi.org/10.3982/ecta18422.

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Developing country megacities suffer from severe road traffic congestion, yet the level of congestion is not a direct measure of equilibrium inefficiency. I study the peak‐hour traffic congestion equilibrium in Bangalore. To measure travel preferences, I use a model of departure time choice to design a field experiment with congestion pricing policies and implement it using precise GPS data. Commuter responses in the experiment reveal moderate schedule inflexibility and a high value of time. I then show that in Bangalore, traffic density has a moderate and linear impact on travel delay. My pol

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17

Milutinović, Milica, and Vladimir Đorić. "Expert assessment of measures on reduction of congestion in cities." Tehnika 75, no. 6 (2020): 767–74. http://dx.doi.org/10.5937/tehnika2006767m.

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Traffic congestion is defined as mutual obstruction of traffic by vehicles due to the existing relation between the speed of vehicles and the flow in conditions of exceeding the capacity of the infrastructure. The paper presents an analysis of local experts survey on the role of non-motorized and motorized ways of travel to reduce congestion, as well as a comparison with the assessments given by foreign experts. The performance and the impact of different modes of transport (motorized and non-motorized) on congestion in urban conditions were assessed. The impact of the mode of transport on con

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18

Farhan, Marwa K., and Muayad S. Croock. "Optimized reduction approach of congestion in mobile ad hoc network based on Lagrange multiplier." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (2022): 6341. http://dx.doi.org/10.11591/ijece.v12i6.pp6341-6349.

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<span lang="EN-US">Over the past decades, computer networks have experienced an outbreak and with that came severe congestion problems. Congestion is a crucial determinant in the delivery of delay-sensitive applications (voice and video) and the quality of the network. in this paper, the Lagrangian optimization rate, delay, packet loss, and congestion approach (LORDPC) are presented. A congestion avoidance routing method for device-to-device (D2D) nodes in an ad hoc network that addresses the traffic intensity problem. The method of Lagrange multipliers is utilized for active route elect

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Marwa, K. Farhan, and S. Croock Muayad. "Optimized reduction approach of congestion in mobile ad hoc network based on Lagrange multiplier." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (2022): 6341–49. https://doi.org/10.11591/ijece.v12i6.pp6341-6349.

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Over the past decades, computer networks have experienced an outbreak and with that came severe congestion problems. Congestion is a crucial determinant in the delivery of delay-sensitive applications (voice and video) and the quality of the network. in this paper, the Lagrangian optimization rate, delay, packet loss, and congestion approach (LORDPC) are presented. A congestion avoidance routing method for device-to-device (D2D) nodes in an ad hoc network that addresses the traffic intensity problem. The method of Lagrange multipliers is utilized for active route election to dodge heavy traffi

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20

Stan, Ioan, Daniel Alexandru Ghere, Paula Iarina Dan, and Rodica Potolea. "Urban Congestion Avoidance Methodology Based on Vehicular Traffic Thresholding." Applied Sciences 13, no. 4 (2023): 2143. http://dx.doi.org/10.3390/app13042143.

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Vehicular traffic in urban areas faces congestion challenges that negatively impact our lives. The infrastructure associated with intelligent transportation systems provides means for addressing the associated challenges in urban areas. This study proposes an effective and scalable vehicular traffic congestion avoidance methodology. It introduces a traffic thresholding mechanism to predict and avoid vehicular traffic congestion during route computation. Our methodology was evaluated and validated by employing four road network topologies, three vehicular traffic density levels and various traf

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21

P. Chauhan, Boski. "Traffic simulation-emission modelling to evaluate impact of signal cycle on automobile emissions." European Transport/Trasporti Europei, no. 98 (June 2024): 1–15. http://dx.doi.org/10.48295/et.2024.98.9.

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Vehicular traffic comprises different types of vehicles with varying static and dynamic characteristics, under heterogeneous traffic conditions in India. The continuous growth of vehicles results in high congestion and becoming the main source of air pollution. The reduction in emissions is directly linked to the reduction in traffic congestion. At urban corridors, higher concentration of pollutants is observed near the traffic signals because of the influence of traffic signal operations on vehicular speed. The present research is carried out with the principal objective as the study of the e

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22

Fan, Xueru, Guanxin Yao, and Yang Yang. "Multi-Compartment Vehicle Routing Problem Considering Traffic Congestion under the Mixed Carbon Policy." Applied Sciences 13, no. 18 (2023): 10304. http://dx.doi.org/10.3390/app131810304.

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The use of multi-compartment vehicles (MCVs) in urban logistics distribution is increasing. However, urban traffic congestion causes high carbon emissions in the logistics distribution, resulting in unsustainable development in urban transportation. In addition, the application of the mixed carbon policy has gradually become the first choice for energy conservation and emission reduction in some countries and regions. The transportation industry is a major carbon-emitting industry, which needs to be constrained by carbon emission reduction policies. In this context, the research on the multi-c

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23

Moumen, Idriss, Jaafar Abouchabaka, and Najat Rafalia. "Adaptive traffic lights based on traffic flow prediction using machine learning models." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 5 (2023): 5813. http://dx.doi.org/10.11591/ijece.v13i5.pp5813-5823.

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<span lang="EN-US">Traffic congestion prediction is one of the essential components of intelligent transport systems (ITS). This is due to the rapid growth of population and, consequently, the high number of vehicles in cities. Nowadays, the problem of traffic congestion attracts more and more attention from researchers in the field of ITS. Traffic congestion can be predicted in advance by analyzing traffic flow data. In this article, we used machine learning algorithms such as linear regression, random forest regressor, decision tree regressor, gradient boosting regressor, and K-neighbo

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Joshi, Jetendra, Manash Jyoti Deka, Anshumali Singh, and Lakshya Gourav Moitra. "OCTM: Over-Speeding and Congestion Reduction in Traffic Management." Advanced Science Letters 22, no. 9 (2016): 2091–95. http://dx.doi.org/10.1166/asl.2016.7062.

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25

Blinova, Tatiana, Rakesh Kumar, Lavish Kansal, Prabhakar Bhandari, Ugur Guven, and Y. Lakshmi Prasanna. "Data-Intensive Traffic Management: Real-Time Insights from the Traffic Management Simulation Test." BIO Web of Conferences 86 (2024): 01089. http://dx.doi.org/10.1051/bioconf/20248601089.

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This research examined the effectiveness of data-intensive traffic management in urban settings using real-time insights from traffic management simulation experiments. The examination of data on traffic flow revealed a noteworthy decrease in congestion, with a 25% increase in traffic velocity during peak hours. Real-time information led to a 40% drop in the severity of traffic accidents and a 50% reduction in reaction times. Improved road safety was aided by a 30% decrease in accidents during inclement weather thanks to real-time weather data. To further optimize urban traffic flow, dynamic t

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S. P., Dr Khandait. "Streamlining Toll Management: A Survey of Business Requirement Solutions." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem33806.

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Effective toll control performs a pivotal role in improving traffic flow, decreasing congestion, and enhancing overall transportation performance. However, toll plaza operators frequently face demanding situations in efficaciously handling statistics and monitoring transactional activities. This studies paper proposes a secure, fast, and dependable statistics control answer tailor-made to the precise wishes of toll plaza operators. By implementing this solution, toll plaza proprietors can successfully track income and loss states, examine regular transaction statistics, and optimize traffic co

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Aprianto, Rizal, Muhammad Rifqi Irfani, Brasie Pradana Sela Bunga Riska Ayu, and I. Made Suraharta. "Assessing the efficacy of contraflow strategies and ripple effects on peripheral road network performance: Insights from Brigjen Sudiarto Road, Semarang." BIS Energy and Engineering 2 (May 31, 2025): V225006. https://doi.org/10.31603/biseeng.345.

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Traffic congestion is a significant challenge in Semarang, Indonesia, a rapidly urbanizing metropolitan area. To address this issue, a contraflow strategy was implemented on Brigjen Sudiarto Road, aiming to alleviate congestion and enhance traffic efficiency. The assessment of the contraflow system's effectiveness utilized the Indonesian Highway Capacity Manual (PKJI). Data were obtained through direct observation and secondary sources, focusing on traffic volume, road capacity, and level of service (LOS) comparisons before and after implementation. Findings revealed a 75% reduction in westbou

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Ehiagwina, Frederick, Seun Olatinwo, Abdultawwab Ibiyeye, Lateef Afolabi, and Olusina Olumbe-Salau. "Development of a Microcontroller-Based Intelligent Traffic Light Control System for Vehicular Movement in T Junctions." Tanzania Journal of Engineering and Technology 44, no. 1 (2024): 190–203. https://doi.org/10.52339/tjet.v44i1.1141.

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This research is devoted to the issue of regulating traffic congestion in major cities using light-dependent resistors coupled with the PIC16F877A microcontroller. This study proposes an intelligent traffic control system for T-Junctions, utilizing sensing and control to optimize traffic flow through dynamic phase adjustments and congestion reduction, enabled by a microcontroller-based decision-making system. The proposed system reduces traffic congestion, automates control, and enhances safety, minimizing accidents and lowering infrastructure costs. Under simulated environment, it demonstrate

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Sánchez González, Santiago, Felipe Bedoya-Maya, and Agustina Calatayud. "Understanding the Effect of Traffic Congestion on Accidents Using Big Data." Sustainability 13, no. 13 (2021): 7500. http://dx.doi.org/10.3390/su13137500.

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Understanding the temporal and spatial dynamics of traffic accidents are a key determinant in their mitigation. This article leverages big data and a Poisson model with fixed effects to understand the causality of traffic congestion on road accidents in ten cities in Latin America: Bogota, Buenos Aires, Lima, Mexico City, Montevideo, Rio de Janeiro, San Salvador, Santiago, Santo Domingo, and Sao Paulo. Analyzing over 10 billion observations in 2019, results show a positive non-linear causality of congestion on the number of accidents. Overall, the results suggest that a 10% reduction in traffi

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Khanza, Shabrina Luthfiani, Erma Suryani, and Rully Agus Hendrawan. "Scenario Model to Mitigate Traffic Congestion and Improve Commuting Time Efficiency." Journal of Information Systems Engineering and Business Intelligence 7, no. 2 (2021): 112. http://dx.doi.org/10.20473/jisebi.7.2.112-118.

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Background: Commuting time is highly influenced by traffic congestion. System dynamics simulation can help identify the cause of traffic problems to improve travel time efficiency.Objective: This study aims to reduce traffic congestion and minimise commuting time efficiency using system dynamics simulation and scenarios. The developed scenarios implement the Bus Rapid Transit (BRT) and trams projects in the model.Methods: System dynamics simulation is used to analyse the transport system in Surabaya and the impact of BRT and trams project implementation in the model in order to improve commuti

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31

Almusawy, Muntather Hassan. "Improved Arithmetic Optimization with Deep Learning Driven Traffic Congestion Control for Intelligent Transportation Systems in Smart Cities." Journal of Smart Internet of Things 2022, no. 1 (2022): 81–96. http://dx.doi.org/10.2478/jsiot-2022-0006.

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Abstract In the last few years, some progress had been made in smart cities, and reduction in traffic congestion was the topmost concern in the development of smart cities. Shorter delays in transmission between Roadside Units (RSUs) and vehicles, road safety, and smooth traffic flow are the major difficulties of Intelligent Transportation Systems (ITS). The rapid improvement in automobiles occurs which increased the number of road accidents and traffic congestion. Machine Learning (ML) was an advanced technique to find hidden insights into ITSs without being explicitly programmed by learning

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Gantimurova, Julia. "MODELING TRAFFIC PARAMETERS TAKEN INTO ACCOUNT OF «BOTTLENECK» IN TRAFFIC FLOW." Scientific Papers Collection of the Angarsk State Technical University 2024, no. 1 (2024): 185–88. http://dx.doi.org/10.36629/2686-7788-2024-1-185-188.

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The article examines a macromodel of traffic flow considering a static bottleneck in order to study the impact on traffic conditions. Analytical results show that the proposed model can qualitatively de-scribe the equilibrium flow and capacity reduction in the event of traffic congestion

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Bhagat-Conway, Matthew Wigginton, and Sam Zhang. "Rush hour-and-a-half: Traffic is spreading out post-lockdown." PLOS ONE 18, no. 9 (2023): e0290534. http://dx.doi.org/10.1371/journal.pone.0290534.

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Traffic congestion is ubiquitous in major cities around the world. Congestion is associated with a slew of negative effects, including delays and local air pollution. Because of the negative effects of congestion, governments invest billions of dollars into the highway system to try to reduce congestion and accommodate peak-hour automobile travel demand. The COVID-19 pandemic presented a significant disruption to transportation systems globally. One impact was a drastic reduction in travel, leading to free-flowing traffic conditions in many previously-congested cities. As lockdowns eased, traf

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M, Arjun K., Nandha Krishna P. T, Aleena Jesrin K, Akhil P, and Malavika I. P. "Economic Evaluation of Traffic Congestion & Design of Traffic Signal with Simulation at Ottapalam." International Journal for Research in Applied Science and Engineering Technology 11, no. 6 (2023): 1259–73. http://dx.doi.org/10.22214/ijraset.2023.53881.

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Abstract: Traffic congestion is the most outstanding performance of the negative externalities of urban road traffic, which is characterized by the negative effects of time delay, energy waste, air pollution and many other impacts. It affects people’s daily life and could cause stress other than time and monetary loss. Traffic congestion causes negative impacts to transport sector and cause a massive increase in the transportation cost. Time is a precious commodity that we all have an equal amount of, and it is something that should not be wasted. A lot of our time is being wasted due to traff

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Alshabibi, Nawaf Mohamed. "Impact Assessment of Integrating AVs in Optimizing Urban Traffic Operations for Sustainable Transportation Planning in Riyadh." World Electric Vehicle Journal 16, no. 5 (2025): 246. https://doi.org/10.3390/wevj16050246.

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Integrating autonomous vehicles (AVs) into urban traffic systems presents significant opportunities for optimizing traffic flow, reducing congestion, and enhancing transportation efficiency. This study proposes a comprehensive framework that combines mathematical optimization techniques, policy planning, and AV adoption modeling to improve urban mobility. Using Highway Capacity Manual (HCM) Optimization methods, the research fine-tunes traffic signal timings, dynamically allocates green time, and enhances intersection coordination to maximize throughput. The study evaluates the impact of AV pe

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Ananya, Paul, Ghosh Kiton, and Mitra Sulata. "Three Fog Computing Based Variants of Congestion Control in ITS." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 1 (2021): 333–48. https://doi.org/10.35940/ijrte.A5966.0510121.

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The growth of vehicles and inadequate road capacity in the urban area trigger traffic congestion and raise the frequency of road accident. Therefore the need of drastically reducing traffic congestion is a significant concern. Advancement in the technology like fog computing, Internet of Things (IoT)in Intelligent Transportation Systems (ITS) aid in the more constructive management of traffic congestion. Three IoT basedFog computing oriented models are designed in the present work for mitigating traffic congestion. The first two schemes are vehicledependent as they control traffic congestion d

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Szymanek, Andrzej, Józef Stokłosa, and Tomasz Zawisza. "Carpooling and the reduction of urban traffic." IOP Conference Series: Materials Science and Engineering 1247, no. 1 (2022): 012042. http://dx.doi.org/10.1088/1757-899x/1247/1/012042.

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Abstract The article presents the results of research that quantitatively confirm the well-known thesis on the impact of carpooling (measured by the declared carpooling indicator, DCI) on a significant reduction in the intensity of urban traffic flows. Of course, it is about joint journeys by passenger cars, which (especially in medium-sized and large cities) are an important source of transport congestion, and the connection with the intensity of traffic is obvious. The working hypothesis was verified by conducting observations and measurements in the central area of a medium-sized city in Po

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Zhao, Zilong, Mengyuan Fang, Luliang Tang, Xue Yang, Zihan Kan, and Qingquan Li. "The Impact of Community Shuttle Services on Traffic and Traffic-Related Air Pollution." International Journal of Environmental Research and Public Health 19, no. 22 (2022): 15128. http://dx.doi.org/10.3390/ijerph192215128.

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Community shuttle services have the potential to alleviate traffic congestion and reduce traffic pollution caused by massive short-distance taxi-hailing trips. However, few studies have evaluated and quantified the impact of community shuttle services on urban traffic and traffic-related air pollution. In this paper, we propose a complete framework to quantitatively assess the positive impacts of community shuttle services, including route design, traffic congestion alleviation, and air pollution reduction. During the design of community shuttle services, we developed a novel method to adaptiv

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Ramirez, Juan Rodriguez, Yuki Minami, and Kenji Sugimoto. "Event-Triggered Quantizers for Network Traffic Reduction." Journal of Advanced Computational Intelligence and Intelligent Informatics 21, no. 6 (2017): 1111–13. http://dx.doi.org/10.20965/jaciii.2017.p1111.

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In the operation of networked control systems, signal quantization is a fundamental problem. Because a network can be shared, another important problem that affects the system performance is the network’s traffic congestion. The event-triggered quantizer is developed to reduce the effects of such problems. Its design problem is formulated, and it is solved using the differential evolution (DE) metaheuristic algorithm. The effectiveness of the event-triggered quantizer is verified through numerical examples.

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Alkaissi, Zainab Ahmed, Ali Nasser Hussein, and Murtada Hassan Muhammad. "Traffic Congestion Measures and Sustainability Evaluation of Urban Street." Journal of Engineering 30, no. 06 (2024): 19–38. http://dx.doi.org/10.31026/j.eng.2024.06.02.

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Traffic congestion become a serious problem that traffic engineers still face. This research explains the sustainable indicators and congestion index for urban streets and their implementation to evaluate the performance measures proceeding toward sustainable roads. Congestion measures in terms of speed reduction and sustainable indicators; mobility (congestion index, travel time, and delay), costs (vehicle operating cost), socio-economic effect (in terms of an estimated factor called User Satisfaction Index (USI), and air pollution (Fuel emissions) are estimated. Link 3 has the highest delay

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Sardari, Reza, Shima Hamidi, and Raha Pouladi. "Effects of Traffic Congestion on Vehicle Miles Traveled." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 47 (2018): 92–102. http://dx.doi.org/10.1177/0361198118791865.

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The effects of traffic congestion on travel behavior are complex and multidimensional because they are related to various factors such as density, land use patterns, network connectivity, and individual preferences. Traffic congestion is a phenomenon that not only affects transportation systems but also influences commuters’ quality of life and population mobility. The present research aims to analyze the effects of traffic congestion on individuals’ travel behaviors, addressing both direct and indirect effects of congestion on vehicle miles traveled (VMT) per driver by implementing structural

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Paul, Ananya, Kiton Ghosh, and Mitra Sulata. "Three Fog Computing Based Variants of Congestion Control in ITS." International Journal of Recent Technology and Engineering 10, no. 1 (2021): 333–48. http://dx.doi.org/10.35940/ijrte.a5966.0510121.

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The growth of vehicles and inadequate road capacity in the urban area trigger traffic congestion and raise the frequency of road accident. Therefore the need of drastically reducing traffic congestion is a significant concern. Advancement in the technology like fog computing, Internet of Things (IoT)in Intelligent Transportation Systems (ITS) aid in the more constructive management of traffic congestion. Three IoT basedFog computing oriented models are designed in the present work for mitigating traffic congestion. The first two schemes are vehicledependent as they control traffic congestion d

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Laksmini, Ni Nyoman Triana. "Koordinasi Lampu Lalu Lintas Antar Simpang Pada Ruas Jalan Pemuda Jakarta Timur." Warta Penelitian Perhubungan 23, no. 5 (2019): 524. http://dx.doi.org/10.25104/warlit.v23i5.1109.

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Traffic jams that frequently occur in the Jakarta city require more serious handling of the involved parties. Traffic management arrangements are needed to improoe traffic conditions which exist today. Pemuda Street is one of the main roads in the East Jakarta Rawamangun. Transportation problems that exist today in these streets is a traffic jam caused by high traffic volume. Intersection coordination setting is the one way to reduce the level of congestion that occurs, so that during the expected congestion that occurs on these roads can be tackled. From the analysis results the queue and del

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Labib, S. M., Hossain Mohiuddin, Irfan Mohammad Al Hasib, Shariful Hasnine Sabuj, and Shrabanti Hira. "Integrating Data Mining and Microsimulation Modelling to Reduce Traffic Congestion: A Case Study of Signalized Intersections in Dhaka, Bangladesh." Urban Science 3, no. 2 (2019): 41. http://dx.doi.org/10.3390/urbansci3020041.

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A growing body of research has applied intelligent transportation technologies to reduce traffic congestion at signalized intersections. However, most of these studies have not considered the systematic integration of traffic data collection methods when simulating optimum signal timing. The present study developed a three-part system to create optimized variable signal timing profiles for a congested intersection in Dhaka, regulated by fixed-time traffic signals. Video footage of traffic from the studied intersection was analyzed using a computer vision tool that extracted traffic flow data.

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Mahona, John N. P., Cuthbert F. Mhilu, Joseph Kihedu, and Hannibal Bwire. "Effects of static bottlenecks on traffic flow in urban road network." International Journal of Engineering, Science and Technology 12, no. 3 (2020): 1–15. http://dx.doi.org/10.4314/ijest.v12i3.1.

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Existing traffic flow models do not consider the effects of road static bottlenecks on traffic flow. In this paper, a modified macroscopic continuum model for traffic flow on urban road network with static bottlenecks is presented. The model takes into account the fluctuations of traffic flow considering static bottlenecks during the morning peak period. The model results show that existence of static road bottlenecks with various configurations cause traffic flow instabilities. This phenomenon lead into stop-and-go traffic flow conditions under the moderate density and reduction of the traffi

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Barwick, Panle Jia, Shanjun Li, Andrew Waxman, Jing Wu, and Tianli Xia. "Efficiency and Equity Impacts of Urban Transportation Policies with Equilibrium Sorting." American Economic Review 114, no. 10 (2024): 3161–205. http://dx.doi.org/10.1257/aer.20220212.

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We estimate an equilibrium sorting model of housing location and commuting mode choice with endogenous traffic congestion to evaluate urban transportation policies. Leveraging fine-scale data from travel diaries and housing transactions identifying residents' home and work locations, we recover rich preference heterogeneity over both travel mode and residential location decisions. While different policies produce the same congestion reduction, their impacts on social welfare differ drastically. In addition, sorting undermines the congestion reduction under driving restrictions and subway expan

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Srinath, M. "Vehicular Traffic Flow Prediction Model Deep Learning." International Journal for Research in Applied Science and Engineering Technology 11, no. 7 (2023): 109–12. http://dx.doi.org/10.22214/ijraset.2023.54576.

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Abstract: Efficient traffic flow prediction is crucial for effective traffic management and congestion reduction in urban areas. However, traditional statistical models often struggle to accurately capture the intricate dynamics of vehicular traffic flow, particularly under dynamic conditions. In this research project, we propose a novel approach that leverages deep learning techniques, specifically Long Short-Term Memory (LSTM) neural networks, AdaBoost, and gradient descent, to enhance the accuracy of traffic flow predictions .By harnessing historical traffic data, our model generates precis

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Chen, Juan, Qinxuan Feng, and Qi Guo. "Multi-Class Freeway Congestion and Emission Based on Robust Dynamic Multi-Objective Optimization." Algorithms 14, no. 9 (2021): 266. http://dx.doi.org/10.3390/a14090266.

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In order to solve the problem of traffic congestion and emission optimization of urban multi-class expressways, a robust dynamic nondominated sorting multi-objective genetic algorithm DFCM-RDNSGA-III based on density fuzzy c-means clustering method is proposed in this paper. Considering the three performance indicators of travel time, ramp queue and traffic emissions, the ramp metering and variable speed limit control schemes of an expressway are optimized to improve the main road and ramp traffic congestion, therefore achieving energy conservation and emission reduction. In the VISSIM simulat

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Cox, Taylor, and Parimala Thulasiraman. "A zone-based traffic assignment algorithm for scalable congestion reduction." ICT Express 3, no. 4 (2017): 204–8. http://dx.doi.org/10.1016/j.icte.2017.11.003.

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Triani, Lily, Joni Arliansyah, and Melawaty Agustien. "Analysis of Flyover Construction Effect to Increase Traffic Services and Reduce Exhaust Emissions at an Intersection." International Journal of Innovative Science and Research Technology 5, no. 6 (2020): 1016–22. http://dx.doi.org/10.38124/ijisrt20jun827.

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Patal - Pusri Intersection is one of the intersections in Palembang with heavy traffic flow and frequent traffic jams. The existence of Underpass construction, apparently could not be a complete solution to unravel traffic congestion. The purpose of this research is to analyze five alternative scenario plans to disentangled the vehicle density, congestion, and reduce pollution from exhaust emissions caused by vehicle density. This research was conducted using VISSIM Microsimulation Program assistance to simulate existing alternative scenarios and to analyze the effect of these alternative scen

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