Literature DB >> 27505098

Exploring factors affecting pedestrians' red-light running behaviors at intersections in China.

Weihua Zhang1, Kun Wang2, Lei Wang3, Zhongxiang Feng4, Yingjie Du1.   

Abstract

Pedestrians' Red-light running behavior is one of the most critical factors for pedestrian involved traffic crashes at intersections in China. The primary objective of this study is to explore how various factors affect pedestrians' red-light running behaviors at intersection areas, using the data collected from Hefei, China. A questionnaire was well designed aiming at collecting pedestrians' socio-economic characteristics, trip related features, and attribute variables in different crossing facilities. Based on 631 valid samples, a binomial logistic model was established to evaluate the impacts of contributing factors on pedestrians' red-light running behavior. The modeling results show that four variables significantly affect the probability of pedestrians' red-light running behavior, which are the trip purpose, time period in one day, pedestrian's attitude towards whether to run a red light when in hurry, and pedestrian's attitude towards whether quality of road facility affects crossing behavior. With those variables, the probability of pedestrians' red-light running behavior at intersections could be predicted. Findings of this study can help understand why pedestrians in China run red-lights and identify which pedestrian groups and intersections are more likely to have such behaviors. This study can also help propose countermeasures more efficiently to reduce pedestrian-related crashes at intersections in China.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Keywords:  Behavior; Factors; Pedestrians; Red-light running; Safety

Mesh:

Year:  2016        PMID: 27505098     DOI: 10.1016/j.aap.2016.07.038

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


  1 in total

1.  Analysis of the Effect of Human-Machine Co-Driving Vehicle on Pedestrian Crossing Speed at Uncontrolled Mid-Block Road Sections: A VR-Based Case Study.

Authors:  Kun Wang; Liang Xu; Han Jiang
Journal:  Int J Environ Res Public Health       Date:  2022-06-12       Impact factor: 4.614

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.