Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Investigating consecutive conflicts of pedestrian crossing at unsignalized crosswalks using the bivariate logistic approach

Zheng, Lai ; Wen, Cheng ; Guo, Yanyong and Laureshyn, Aliaksei LU orcid (2021) In Accident Analysis and Prevention 162.
Abstract

Pedestrians confront risky situations at unsignalized crosswalks when they are consecutively interacting with motorized vehicles and non-motorized vehicles while crossing. This study aims to investigate the safety of pedestrians with a new perspective that focuses on consecutive conflicts occurring during pedestrian crossing. Based on about 9 h video data collected by an unmanned aerial vehicle from six unsignalized crosswalks of a roundabout, consecutive conflicts were identified, and an integrated severity index that combines post encroachment time, jerk and yaw rate ratio was proposed to measure the severity of consecutive conflicts. Moreover, bivariate logistic models that account for and not account for the correlation between the... (More)

Pedestrians confront risky situations at unsignalized crosswalks when they are consecutively interacting with motorized vehicles and non-motorized vehicles while crossing. This study aims to investigate the safety of pedestrians with a new perspective that focuses on consecutive conflicts occurring during pedestrian crossing. Based on about 9 h video data collected by an unmanned aerial vehicle from six unsignalized crosswalks of a roundabout, consecutive conflicts were identified, and an integrated severity index that combines post encroachment time, jerk and yaw rate ratio was proposed to measure the severity of consecutive conflicts. Moreover, bivariate logistic models that account for and not account for the correlation between the pedestrian-motorized vehicle (P-MV) conflict and the pedestrian-non-motorized vehicle (P-NV) conflict of a consecutive conflict were developed, and speed-, count-, time to zebra-related factors and other factors of involved road users were considered in the models. A total of 899 consecutive conflicts were identified and on average one in six pedestrians encountered consecutive conflicts. The bivariate logistic modeling results show that the model accounting for the correlation significantly outperform its counterpart. A negative correlation is found between the severities of P-MV conflict and P-NV conflict, and the P-NV conflict is more likely to be the serious one. It is also found that speed of motorized vehicle and time to zebra for the first conflicting subject are the common factors that affect the severities of both P-NV conflicts and P-MV conflicts, while speed of pedestrian, speed of non-motorized vehicle, number of motorized vehicles, number of non-motorized vehicles, group and direction of pedestrians have significant effects on the severity of either P-MV conflicts or P-NV conflicts.

(Less)
Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Bivariate logistic model, Consecutive conflict, Pedestrian crossing, Unsignalized crosswalk
in
Accident Analysis and Prevention
volume
162
article number
106402
publisher
Elsevier
external identifiers
  • pmid:34560506
  • scopus:85115298019
ISSN
0001-4575
DOI
10.1016/j.aap.2021.106402
language
English
LU publication?
yes
id
5ba8f63f-db12-4f91-91cd-c18769a937ed
date added to LUP
2021-10-01 12:25:14
date last changed
2024-06-15 17:09:39
@article{5ba8f63f-db12-4f91-91cd-c18769a937ed,
  abstract     = {{<p>Pedestrians confront risky situations at unsignalized crosswalks when they are consecutively interacting with motorized vehicles and non-motorized vehicles while crossing. This study aims to investigate the safety of pedestrians with a new perspective that focuses on consecutive conflicts occurring during pedestrian crossing. Based on about 9 h video data collected by an unmanned aerial vehicle from six unsignalized crosswalks of a roundabout, consecutive conflicts were identified, and an integrated severity index that combines post encroachment time, jerk and yaw rate ratio was proposed to measure the severity of consecutive conflicts. Moreover, bivariate logistic models that account for and not account for the correlation between the pedestrian-motorized vehicle (P-MV) conflict and the pedestrian-non-motorized vehicle (P-NV) conflict of a consecutive conflict were developed, and speed-, count-, time to zebra-related factors and other factors of involved road users were considered in the models. A total of 899 consecutive conflicts were identified and on average one in six pedestrians encountered consecutive conflicts. The bivariate logistic modeling results show that the model accounting for the correlation significantly outperform its counterpart. A negative correlation is found between the severities of P-MV conflict and P-NV conflict, and the P-NV conflict is more likely to be the serious one. It is also found that speed of motorized vehicle and time to zebra for the first conflicting subject are the common factors that affect the severities of both P-NV conflicts and P-MV conflicts, while speed of pedestrian, speed of non-motorized vehicle, number of motorized vehicles, number of non-motorized vehicles, group and direction of pedestrians have significant effects on the severity of either P-MV conflicts or P-NV conflicts.</p>}},
  author       = {{Zheng, Lai and Wen, Cheng and Guo, Yanyong and Laureshyn, Aliaksei}},
  issn         = {{0001-4575}},
  keywords     = {{Bivariate logistic model; Consecutive conflict; Pedestrian crossing; Unsignalized crosswalk}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Accident Analysis and Prevention}},
  title        = {{Investigating consecutive conflicts of pedestrian crossing at unsignalized crosswalks using the bivariate logistic approach}},
  url          = {{http://dx.doi.org/10.1016/j.aap.2021.106402}},
  doi          = {{10.1016/j.aap.2021.106402}},
  volume       = {{162}},
  year         = {{2021}},
}