吉林大学学报(工学版) ›› 2023, Vol. 53 ›› Issue (7): 1951-1961.doi: 10.13229/j.cnki.jdxbgxb.20211061

• 交通运输工程·土木工程 • 上一篇    

基于BPR函数的城市道路间断流动态路阻模型

王殿海(),胡佑薇,蔡正义,曾佳棋,姚文彬   

  1. 浙江大学 智能交通研究所,杭州 310058
  • 收稿日期:2021-10-18 出版日期:2023-07-01 发布日期:2023-07-20
  • 作者简介:王殿海(1962-),男,教授,博士.研究方向:交通控制.E-mail: wangdianhai@zju.edu.cn
  • 基金资助:
    国家自然科学基金项目(52072340)

Dynamic road resistance model of intermittent flow on urban roads based on BPR function

Dian-hai WANG(),You-wei HU,Zheng-yi CAI,Jia-qi ZENG,Wen-bin YAO   

  1. Intelligent Transportation Research Institute,Zhejing University,Hangzhou 310058,China
  • Received:2021-10-18 Online:2023-07-01 Published:2023-07-20

摘要:

针对BPR函数在过饱和情况下难以应用、不符合城市间断流特性的局限性进行了改进,重新定义交通需求,提出考虑上下游信号配时影响的城市道路间断流动态路阻函数形式。基于VISSIM路段仿真数据,采用SMOTE过采样算法平衡仿真数据集,标定改进路阻函数。研究表明,在BPR函数中加入绿波宽度占比ω、下游研究相位绿信比gs、转向因子变量sl,能够同时反映信号配时、交通需求对于行程时间的影响。路段自由流行驶时间并非固定值,而是与ω有关,随着ω的增大,可协调程度增加,路段自由流行驶时间减小。

关键词: 交通运输规划与管理, 交通需求, 动态路阻, 信号配时, 协调, 行程时间

Abstract:

In view of the limitation of BPR (Bereau of Public Roads) function that it is not suitable for oversaturated traffic flow and does not meet the characteristics of urban intermittent flow, some improvements have been made. The paper redefines the traffic demand, and proposes a dynamic resistance function form of urban road intermittent flow that takes into account the influence of upstream and downstream signal timing. Based on the data obtained by VISSIM road section simulation, the SMOTE oversampling algorithm is used to balance the simulation data set, and the improved road resistance function is calibrated. Our research shows that adding three variables which include percentage of green wave ω, green split for downstream research phase sg, and steering factor sl into the BPR function can simultaneously reflect the influence of signal timing and traffic demand on travel time. In the case of zero traffic flow, the zero-flow travel time is related with the percentage of green wave ω. With the increase of ω, the degree of coordination increases, and the zero-flow travel time decreases.

Key words: transportation planning and management, traffic demand, dynamic road resistance, signal timing, coordination, travel time

中图分类号: 

  • U491

图1

某路段各个时段流量与行程时间的统计分布"

图2

交通需求定义图示"

图3

上下游交叉口之间绿波宽度占比"

图4

模型应用流程图"

图5

研究路段"

表1

仿真路段流量输入"

流量方案方向1方向2方向3
14642754
293854107
31391280161
4(真实情况)1851707214
52312134268
62782561321
73242987375
83703414428
94163841482
104634268535
119242754
12186854107
132781280161
143701707214
154622134268
165562561321
176482987375
187403414428
198323841482
209264268535
2110184694589

表2

信号配时方案"

上游直行相位绿灯时长/s

上游周

期时长

/s

下游直行相位绿灯时长/s

下游周

期时长

/s

直行相位的相位差

/s

8018050180[0,10,20,…,180]
8018060180[0,10,20,…,180]
8018070180[0,10,20,…,180]
8018080180[0,10,20,…,180]
7018080180[0,10,20,…,180]

图6

仿真数据散点图"

图7

仿真结果拟合图"

表3

误差比较"

项目自变量R2MAEMAPERMSE
BPR函数流量0.21926.8960.39937.816
交通需求0.73219.6340.25826.015
本文模型流量0.61215.3270.23023.723
交通需求0.8589.8350.16114.327

图8

平均行程时间计算结果对比图"

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