摘要
针对判断交通溢流严重程度的模糊性和随机性问题,提出了基于云模型的交通溢流严重程度评价方法.首先,选择周溢流天数、周平均日溢流次数、周平均日溢流时长3项指标构建溢流严重程度评价因数集,采用层次分析法得到3项评价指标的权重;然后,分别构建各项评价指标的正向云模型,并计算待评价交叉口各指标的等级隶属度,在此基础上结合指标权重计算综合评价值,依据最大隶属度原则确定待评价交叉口的交通溢流严重程度;最后,以北京市西大望路平乐园交叉口为例进行了验证.该评价方法简单且易实现,具有较好的实用性.
Aiming at the problem of fuzziness and randomness in judging the severity of traffic overflow,this paper proposed a method of evaluating the severity of traffic overflow based on cloud model.First,three indexes,namely,the number of overflow days per week,the average number of overflow days per week and the average duration of overflow days per week,are selected to construct the evaluation factor set of overflow severity.The weights of the three evaluation indexes are obtained by using the analytic hierarchy process.Then,the forward cloud model of each evaluation index is constructed,and the grade of each index at the intersection to be evaluated is calculated.Based on the membership degree,the comprehensive evaluation value is calculated with the index weight,and the traffic overflow severity of the intersection to be evaluated is determined according to the principle of maximum membership degree.Finally,an empirical study was performed to validate the proposed method using the Pingleyuan intersection on Xidawang Road in Beijing.The evaluation method is simple and easy to implement,and has good practicability.
作者
曹政
李华明
卓为
李振龙
CAO Zheng;LI Huaming;ZHUO Wei;LI Zhenlong(Beijing Key Laboratory of Traffic Engineering (Beijing University of Technology),Beijing 100124,China;Beijing Municipal Commission of Transport,Beijing 100073,China;Beijing Traffic Management Bureau,Beijing 100037,China)
出处
《交通工程》
2019年第1期14-18,共5页
Journal of Transportation Engineering
基金
北京市交通行业科技项目(2018-kjc-01-169)
关键词
交通溢流
云模型
隶属度
评价
traffic overflow
cloud model
membership
evaluate
作者简介
曹政(1994—),男,硕士,研究方向为智能交通,E-mail:caozheng0629@163.com.
