Literature DB >> 26896300

Exploring stop-go decision zones at rural high-speed intersections with flashing green signal and insufficient yellow time in China.

Keshuang Tang1, Yanqing Xu2, Fen Wang2, Takashi Oguchi3.   

Abstract

The objective of this study is to empirically analyze and model the stop-go decision behavior of drivers at rural high-speed intersections in China, where a flashing green signal of 3s followed by a yellow signal of 3s is commonly applied to end a green phase. 1, 186 high-resolution vehicle trajectories were collected at four typical high-speed intersection approaches in Shanghai and used for the identification of actual stop-go decision zones and the modeling of stop-go decision behavior. Results indicate that the presence of flashing green significantly changed the theoretical decision zones based on the conventional Dilemma Zone theory. The actual stop-go decision zones at the study intersections were thus formulated and identified based on the empirical data. Binary Logistic model and Fuzzy Logic model were then developed to further explore the impacts of flashing green on the stop-go behavior of drivers. It was found that the Fuzzy Logic model could produce comparably good estimation results as compared to the traditional Binary Logistic models. The findings of this study could contribute the development of effective dilemma zone protection strategies, the improvement of stop-go decision model embedded in the microscopic traffic simulation software and the proper design of signal change and clearance intervals at high-speed intersections in China.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Dilemma Zone; Flashing green; Fuzzy Logic; High-speed intersections; Stop-go decision behavior

Mesh:

Year:  2016        PMID: 26896300     DOI: 10.1016/j.aap.2016.01.011

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  1 in total

1.  Empirical Analysis and Modeling of Stop-Line Crossing Time and Speed at Signalized Intersections.

Authors:  Keshuang Tang; Fen Wang; Jiarong Yao; Jian Sun
Journal:  Int J Environ Res Public Health       Date:  2016-12-23       Impact factor: 3.390

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.