Correlation Analysis of Internet Car and Urban Traffic Congestion Based on Logistics Regression Congestion

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Guangliang Zhang ◽  
Jian Wang ◽  
Xiaowei Hu
Keyword(s):  
Correlation Analysis ◽  
Traffic Congestion ◽  
Urban Traffic ◽  
Logistics Regression

scholarly journals Population Density or Populations Size. Which Factor Determines Urban Traffic Congestion?

2021 ◽  
Vol 13 (8) ◽  
pp. 4280
Author(s):  
Yu Sang Chang ◽  
Sung Jun Jo ◽  
Yoo-Taek Lee ◽  
Yoonji Lee
Keyword(s):  
Population Density ◽  
Population Size ◽  
Traffic Congestion ◽  
Critical Role ◽  
Small Population ◽  
High Density ◽  
Urban Traffic ◽  
Contradictory Result ◽  
Low Density

A large number of articles have documented that as population density of cities increases, car use declines and public transit use rises. These articles had a significant impact of promoting high-density compact urban development to mitigate traffic congestion. Another approach followed by other researchers used the urban scaling model to indicate that traffic congestion increases as population size of cities increases, thus generating a possible contradictory result. Therefore, this study examines the role of both density and population size on traffic congestion in 164 global cities by the use of Stochastic Impacts by Regression on Population, Affluence and Technology model. We divide 164 cities into the two subgroups of 66 low density cities and 98 high density cities for analysis. The findings from the subgroups analysis indicated a clear-cut difference on the critical role of density in low-density cities and the exclusive role of population size in high-density cities. Furthermore, using threshold regression model, 164 cities are divided into the two regions of large and small population cities to determine population scale advantage of traffic congestion. Our findings highlight the importance of including analysis of subgroups based on density and/or population size in future studies of traffic congestion.

scholarly journals Identification and Prediction of Urban Traffic Congestion via Cyber-Physical Link Optimization

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 63268-63278 ◽  
Author(s):  
Darong Huang ◽  
Zhenping Deng ◽  
Shaohua Wan ◽  
Bo Mi ◽  
Yang Liu
Keyword(s):  
Traffic Congestion ◽  
Urban Traffic

scholarly journals Discovering Urban Traffic Congestion Propagation Patterns With Taxi Trajectory Data

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 69481-69491 ◽  
Author(s):  
Zhenhua Chen ◽  
Yongjian Yang ◽  
Liping Huang ◽  
En Wang ◽  
Dawei Li
Keyword(s):  
Traffic Congestion ◽  
Urban Traffic ◽  
Trajectory Data ◽  
Taxi Trajectory

scholarly journals Research on Decision Evaluation Model of HOV Lane Setting

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Ding Lv ◽  
Qunqi Wu ◽  
Bo Chen ◽  
Yahong Jiang
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Evaluation Model ◽  
Path Selection ◽  
Urban Traffic ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Travel Efficiency ◽  
Hov Lanes ◽  
The City

In order to achieve the purpose of improving the travel efficiency of commuters in the periphery of the city, expanding the beneficiary groups of urban rail transit, and alleviating urban road traffic congestion, when planning and setting up HOV in the periphery of the city, it is necessary to analyze the feasibility of HOV lane setting from both the demand conditions and the setting conditions. This paper combines machine learning to construct a decision-making evaluation model for HOV lane setting and studies the optimal layout model and algorithm of HOV lanes in service rail transit commuter chain. The setting, planning, and layout of HOV lanes are a two-way interactive process of traveler's path selection and designer's road planning. Finally, after the model is constructed, the performance of the system model is verified. The results show that the system studied in this paper can be used for traffic data and lane planning analysis. Therefore, in the process of urban operation, the HOV model constructed in this paper is mainly used to alleviate urban traffic and improve urban operation efficiency.

scholarly journals Traffic Congestion In Azadpur Mandi: A Study On The Largest Vegetables And Fruits Market Of Asia

2021 ◽  
Vol 14 (1) ◽  
pp. 122-131
Author(s):  
Raman Ekta ◽  
Anand Subhash ◽  
Suresh V. Madha ◽  
Sharma Poonam ◽  
Singh Anju ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Sustainable Development Goals ◽  
Transportation Network ◽  
Heavy Traffic ◽  
Urban Traffic ◽  
The Road ◽  
The People ◽  
Development Goals ◽  
Green Transportation ◽  
Vegetables And Fruits

India’s intended nationally determined contribution emission which is safe, smart and sustainable green transportation network. Azadpur Mandi which is known for the biggest selling place of fruits and vegetable in Delhi is becoming a place of very heavy traffic area zone. People who are living nearby and the people coming to Azadpur Mandi facing a lot of traffic and also because of no proper direction hinted there people are not able to reach their destination on time. This paper assesses urban traffic congestions and its impact on the daily life of stakeholders and also advocates some possible solutions. In this research found results the number of vehicles has increased in the last ten to fifteen years. The total number of categorised vehicle has also increased. Azadpur Mandi has impacted the land value of the surroundings. The road infrastructure is not sufficient to cater to the traffic volume of this area. The number of lanes in this area is less. This paper outlines the problems of traffic congestion in Asia’s largest sabji (Vegetable) Mandi by using statistical tools. There are very few parking lots inside and outside of the Mandi. This paper investigates the goal 11 of Sustainable Development Goals (SDGs). Goal 11 says to make cities safe, resilience, sustainable. According to the Delhi Traffic police, Azadpur is one of the most accident-prone hotspots of Delhi.

Review of Urban Traffic Congestion Formation and Diffusion Mechanism

CICTP 2015 ◽  
2015 ◽  
Author(s):  
Changfen Zhang ◽  
Han Bai ◽  
Shunchao Wang ◽  
Changyu Xie
Keyword(s):  
Traffic Congestion ◽  
Diffusion Mechanism ◽  
Urban Traffic ◽  
And Diffusion
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