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Identification of Factors Influencing the Operational Effect of the Green Wave on Urban Arterial Roads Based on Association Analysis.

Authors :
Liang, Zijun
Zhan, Xuejuan
Wang, Ruihan
Li, Yuqi
Xiao, Yun
Source :
Applied Sciences (2076-3417); Jul2023, Vol. 13 Issue 14, p8372, 19p
Publication Year :
2023

Abstract

Green wave control is an important technology that synchronizes traffic signals to improve traffic flow on urban arterial roads. Current research has focused on optimizing and evaluating control schemes; however, their operational effect is easily affected by a variety of traffic and travel factors. This means it is important to study methods to identify the factors influencing the operational effect of the green wave on arterial roads. In this study, we conducted innovative research to identify these factors and made breakthroughs in optimizing and evaluating schemes of green wave control. We use the number of stops, travel time, and delays as representative evaluation indicators to assess the effects of four influencing factors: design speed, signal timing, pedestrian crossing, and heavy vehicles. An association analysis that combines sensitivity analysis and grey relational analysis was used to rank these factors in their degree of correlation. A case study was conducted based on the traffic data on Eshan Road in Wuhu City to verify the proposed method. The results of simulations in Vissim 7.0 showed that pedestrian crossing and heavy vehicles were the more important factors influencing the operational effect of the green wave. Moreover, implementing measures related to traffic management helped improve the effect to an extent greater than by optimizing the scheme for green wave control alone. Additionally, optimizing control schemes in the context of implementing measures related to traffic management significantly improved the operational effect of the green wave. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
13
Issue :
14
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
168600126
Full Text :
https://doi.org/10.3390/app13148372