Risk Area Identification Model of Bus Bay Stops Based on Distribution of Conflicts

Effective identification of the risk area of the bus bay stop is a prerequisite for the enhancement of traffic safety. This study proposes a method of identifying the risk area based on the distribution of traffic conflicts. Firstly, the traffic flow data of the bus stop is collected by drones and v...

Full description

Saved in:
Bibliographic Details
Main Authors: Weiwei Qi, Lianjie Ruan, Yue Zhi, Bin Shen
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2021/9663966
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832566322691571712
author Weiwei Qi
Lianjie Ruan
Yue Zhi
Bin Shen
author_facet Weiwei Qi
Lianjie Ruan
Yue Zhi
Bin Shen
author_sort Weiwei Qi
collection DOAJ
description Effective identification of the risk area of the bus bay stop is a prerequisite for the enhancement of traffic safety. This study proposes a method of identifying the risk area based on the distribution of traffic conflicts. Firstly, the traffic flow data of the bus stop is collected by drones and video recognition software, and the traffic flow characteristics of the bus stop are analyzed by the mathematical and statistical methods. Secondly, using the gray clustering evaluation theory, on the basis of the rasterization of the functional area of the bus bay stop, a risk level model based on the index system of conflict rate, conflict severity, and potential conflict risk is proposed. Finally, take a bus stop in Guangzhou as an example to verify the solution. The results show that the constructed model can effectively identify the risk areas of bus bay stops. The risk areas of the bus bay stops are concentrated in the middle and lower reaches of the bus stop, which proves that the impact of bus exiting the stop on the surrounding traffic is greater than the process of bus entering the stop; the traffic risk areas of lanes near the bus stop are concentrated, and the severity of conflicts is low. The traffic risk zone of the lane far away from the bus stop is widely distributed, and the severity of conflict is higher. The research results can provide a basis for the micro safety performance evaluation and safety optimization of bus bay stops, which has strong theoretical and practical significance.
format Article
id doaj-art-1a44f6ad2a4644f59967c7e1971d647b
institution Kabale University
issn 1607-887X
language English
publishDate 2021-01-01
publisher Wiley
record_format Article
series Discrete Dynamics in Nature and Society
spelling doaj-art-1a44f6ad2a4644f59967c7e1971d647b2025-02-03T01:04:20ZengWileyDiscrete Dynamics in Nature and Society1607-887X2021-01-01202110.1155/2021/9663966Risk Area Identification Model of Bus Bay Stops Based on Distribution of ConflictsWeiwei Qi0Lianjie Ruan1Yue Zhi2Bin Shen3School of Civil Engineering and TransportationSchool of Civil Engineering and TransportationSchool of Rehabilitation EngineeringUrban Planning Design Institute of GanzhouEffective identification of the risk area of the bus bay stop is a prerequisite for the enhancement of traffic safety. This study proposes a method of identifying the risk area based on the distribution of traffic conflicts. Firstly, the traffic flow data of the bus stop is collected by drones and video recognition software, and the traffic flow characteristics of the bus stop are analyzed by the mathematical and statistical methods. Secondly, using the gray clustering evaluation theory, on the basis of the rasterization of the functional area of the bus bay stop, a risk level model based on the index system of conflict rate, conflict severity, and potential conflict risk is proposed. Finally, take a bus stop in Guangzhou as an example to verify the solution. The results show that the constructed model can effectively identify the risk areas of bus bay stops. The risk areas of the bus bay stops are concentrated in the middle and lower reaches of the bus stop, which proves that the impact of bus exiting the stop on the surrounding traffic is greater than the process of bus entering the stop; the traffic risk areas of lanes near the bus stop are concentrated, and the severity of conflicts is low. The traffic risk zone of the lane far away from the bus stop is widely distributed, and the severity of conflict is higher. The research results can provide a basis for the micro safety performance evaluation and safety optimization of bus bay stops, which has strong theoretical and practical significance.http://dx.doi.org/10.1155/2021/9663966
spellingShingle Weiwei Qi
Lianjie Ruan
Yue Zhi
Bin Shen
Risk Area Identification Model of Bus Bay Stops Based on Distribution of Conflicts
Discrete Dynamics in Nature and Society
title Risk Area Identification Model of Bus Bay Stops Based on Distribution of Conflicts
title_full Risk Area Identification Model of Bus Bay Stops Based on Distribution of Conflicts
title_fullStr Risk Area Identification Model of Bus Bay Stops Based on Distribution of Conflicts
title_full_unstemmed Risk Area Identification Model of Bus Bay Stops Based on Distribution of Conflicts
title_short Risk Area Identification Model of Bus Bay Stops Based on Distribution of Conflicts
title_sort risk area identification model of bus bay stops based on distribution of conflicts
url http://dx.doi.org/10.1155/2021/9663966
work_keys_str_mv AT weiweiqi riskareaidentificationmodelofbusbaystopsbasedondistributionofconflicts
AT lianjieruan riskareaidentificationmodelofbusbaystopsbasedondistributionofconflicts
AT yuezhi riskareaidentificationmodelofbusbaystopsbasedondistributionofconflicts
AT binshen riskareaidentificationmodelofbusbaystopsbasedondistributionofconflicts