Recurrence analysis of urban traffic congestion index on multi-scale

2022 ◽  
Vol 585 ◽  
pp. 126439
Author(s):  
Jiaxin Wu ◽  
Xubing Zhou ◽  
Yi Peng ◽  
Xiaojun Zhao
Keyword(s):  
Traffic Congestion ◽  
Urban Traffic ◽  
Recurrence Analysis ◽  
Multi Scale ◽  
Congestion Index

Application of AHP-GIS Technology to Assess Congestion Vulnerability, a Case Study of Ranchi City, India

2017 ◽  
Vol 8 (1) ◽  
pp. 19-42
Author(s):  
Alok Bhushan Mukherjee ◽  
Akhouri Pramod Krishna ◽  
Nilanchal Patel
Keyword(s):  
Influencing Factors ◽  
Traffic Congestion ◽  
Urban Traffic ◽  
Gis Technology ◽  
Absolute Deviation ◽  
Average Speed ◽  
Smooth Flow ◽  
Real Scenario ◽  
Index Value ◽  
Congestion Index

Urban traffic congestion is a multi-dimensional phenomenon and therefore, is sensitive to certain influencing factors behaving in a random manner. Consequently, the possibility of a route characterized by smooth flow of traffic becoming congested cannot be ruled out. The present research investigation attempts to categorize different routes of the study area in terms of their degree of congestion vulnerability. Average Speed (AS), Delay Ratio of Average Speed (DRAS), Stopped Time (ST), Stopped Time Gradient (STG), and Absolute Deviation in Congestion Index Value (ADCIV) were identified as the potential influencing factors. The AHP was employed to rank the importance of the aforementioned influencing factors in triggering congestion that can sometimes lead to traffic deadlock. On the other hand, the GIS Weighted Sum Overlay technique was employed to determine the integrated impact of the influencing factors on the behavior of traffic flow. The results showed close agreement with the real scenario of the traffic congestion observed in the field.

scholarly journals Impact of Rainfall on Traffic Speed in Major Cities of China

2021 ◽  
Vol 13 (16) ◽  
pp. 9074
Author(s):  
Min Zhang ◽  
Yufu Liu ◽  
Wenqi Sun ◽  
Yixiong Xiao ◽  
Chang Jiang ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Vulnerability Index ◽  
Urban Traffic ◽  
Healthy Development ◽  
Physical Examinations ◽  
Traffic Speed ◽  
Evaluation Mechanism ◽  
Congestion Index ◽  
The Impact ◽  
Important Basis

The construction of healthy transportation is an important ingredient for promoting the healthy development of cities. The establishment of an urban traffic evaluation mechanism can provide an important basis for the construction of healthy transportation. This study focused on the impact of precipitation on traffic speed and developed an urban traffic vulnerability index. This index reflects the degree of traffic affected by precipitation, which is calculated based on the traffic congestion index under different rainfall intensities. The traffic vulnerability indices of 41 major cities in China under rainfall conditions were evaluated. Based on the above traffic vulnerability indexes, the impact of socioeconomic factors on urban traffic vulnerability was analyzed. The three key findings of this study are as follows: there was a positive correlation between the vulnerability index and the gross domestic product (GDP); the urban population (POP) had a significant impact on the urban traffic vulnerability; and urban car ownership had little impact on traffic vulnerability. Based on these findings, possible measures to improve urban traffic vulnerability are proposed. The construction of an index system provides a basis for enhancing the urban traffic assessment mechanism, promoting the development of urban physical examinations and building healthy transportation and healthy cities.

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.

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