[1]钱国敏,凡俊生,章立辉,等.混行交叉口网联自动车专用道布设方案评价模型[J].长安大学学报(自然科学版),2022,42(2):115-126.
　QIAN Guo min,FAN Jun sheng,ZHANG Li hui,et al.Evaluation model for configuration schemes of dedicated connected andautonomous lanes at intersections with heterogeneous traffic flows[J].Journal of Chang’an University (Natural Science Edition),2022,42(2):115-126.
点击复制

混行交叉口网联自动车专用道布设方案评价模型()
分享到：

长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
第42卷
期数:
2022年2期
页码:
115-126
栏目:
交通工程
出版日期:
2022-03-15

文章信息/Info

Title:
Evaluation model for configuration schemes of dedicated connected andautonomous lanes at intersections with heterogeneous traffic flows
作者:
钱国敏; 凡俊生; 章立辉; 王殿海
1. 浙江大学 建筑工程学院，浙江 杭州 310058; 2. 浙江大学 平衡建筑研究中心，浙江 杭州 310014;3. 银江技术股份有限公司，浙江 杭州 311422; 4. 浙江大学建筑设计研究院有限公司，浙江 杭州 310014
Author(s):
QIAN Guomin1; 2; 3;  FAN Junsheng1; 4;  ZHANG Lihui1; 4;  WANG Dianhai1
1. College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, Zhejiang, China;2. Center for Balance Architecture, Zhejiang University, Hangzhou 310014, Zhejiang, China;3. ENJOYOR Technology Co., Ltd, Hangzhou 311422, Zhejiang, China; 4. Architecture Design &Research Institute of Zhejiang University Co., Ltd, Hangzhou 310014, Zhejiang, China
关键词:
交通工程; 网联自动车; 混行车流; 专用道; 交叉口; 车道渠化; 信号配时; 通行能力
Keywords:
traffic engineering;  connected and autonomous vehicle;  mixed traffic flow;  dedicated lane;  intersection;  lane channelization;  signal timing;  capacity
文献标志码:
A
摘要:
为评价混行交叉口网联自动车专用道的布设方案，分析了不同专用道布设情况下网联自动车流和人工车流在交叉口内的各种冲突，根据是否受专用道布设位置影响，将其分为基本冲突、左冲突和右冲突。在此基础上，以混行交叉口通行能力最大为目标，构建了一套混合整数线性规划模型，包括车道渠化、流量分配和信号配时相应约束，在给定的专用道布设方案下，协同优化专用道和普通车道的渠化方案以及相应的信号配时方案，消除上述3种车流冲突。以典型四车道十字交叉口为例，选取5种不同的专用道布设方案进行比较，分析网联自动车占比、交通量水平和左右转车流比例3个因素对不同专用道布设方案下交叉口最大通行能力的影响。结果表明：网联自动车专用道数量和位置的改变，及由此带来的最优渠化方案和信号配时方案的改变，都将影响交叉口的最大通行能力；当网联自动车占比较小时，专用道数量越少则交叉口最大通行能力越大；当网联自动车占比较大时，专用道数量越多则交叉口最大通行能力越大；交通量水平影响不同专用道布设方案下最大通行能力的差值大小，但不影响不同布设方案的优劣顺序；交叉口车流转向比例发生变化后，不同专用道布设方案下交叉口最大通行能力以及优劣顺序均会发生改变。
Abstract:
To evaluate the configuration schemes of dedicated connected and autonomous lanes at intersections with heterogeneous traffic flows, the conflicts among connected and autonomous vehicles (CAVs) and humandriven vehicles (HVs) at intersections with dedicated CAV lanes were analyzed. These conflicts were categorized into basic conflicts, left conflicts and right conflicts according to whether or not affected by the location of dedicated lanes. On this basis, a mixedinteger linear programming model was built, with an objective to maximize the intersection reserve capacity. The constraints mainly included those regarding lane channelization, flow distribution and signal timing settings. Under given dedicated lane configurations, the model could simultaneously optimize the channelization schemes for dedicated lanes and regular lanes, as well as the corresponding signal timing plan to eliminate the above three flow conflicts. A typical fourlane fourway intersection was taken as an example, five configuration schemes with different numbers and locations of dedicated lanes were selected for comparison. The impacts of CAV penetration rate, traffic demand level and turning ratios on the maximum capacity of intersection under the five configuration schemes were analyzed. The results show that the changes in both the numbers and locations of dedicated CAV lanes, and the resulted changes in the channelization scheme and signal timing scheme, will all influence the maximum capacity of intersection. When CAV penetration rate is small, the smaller number of dedicated lanes leads to larger maximum capacity of intersection. When CAV penetration rate is large, the larger number of dedicated lanes leads to greater maximum capacity of intersection. Traffic demand level affects the differences of the maximum capacities of intersection under the five configuration schemes, rather than their order. And the maximum capacities of intersection and their order under all the five configuration schemes vary with the traffic turning ratios at the intersection. 2 tabs, 8 figs, 30 refs.

相似文献/References:

[1]王建伟,李娉,高洁,等.中国交通运输碳减排区域划分[J].长安大学学报(自然科学版),2012,32(01):0.
[2]李曙光,周庆华.具有破坏排队的离散时间动态网络装载算法[J].长安大学学报(自然科学版),2012,32(01):0.
[3]凌海兰,郗恩崇.基于随机波动条件的公交客运量预测模型[J].长安大学学报(自然科学版),2012,32(01):0.
[4]田娥,肖庆,陆小佳,等.安全驾驶的横向安全预警报警阈值的确定[J].长安大学学报(自然科学版),2012,32(01):0.
[5]侯贻栋,赵炜华,魏 朗,等.驾驶人空间距离判识规律心理学分析[J].长安大学学报(自然科学版),2012,32(03):86.
　HOU Yi-dong,ZHAO Wei-hua,WEI Lang,et al.Analysis on psychology in cognitive distance about drivers[J].Journal of Chang’an University (Natural Science Edition),2012,32(2):86.
[6]赵跃峰,张生瑞,魏 华.隧道群路段运行速度特性分析[J].长安大学学报(自然科学版),2012,32(06):67.
　ZHAO Yue-feng,ZHANG Sheng-rui,WEI hua.Operating speed characteristics of tunnel group section[J].Journal of Chang’an University (Natural Science Edition),2012,32(2):67.
[7]林 杉,许宏科,刘占文.一种高速公路隧道交通流元胞自动机模型[J].长安大学学报(自然科学版),2012,32(06):73.
　LIN Shan,XU Hong-ke,LIU Zhan-wen.One cellular automaton traffic flow model for expressway tunnel[J].Journal of Chang’an University (Natural Science Edition),2012,32(2):73.
[8]刘俊德,徐 兵,梁永东,等.交通事故下高速公路行车安全评估[J].长安大学学报(自然科学版),2012,32(06):78.
　LIU Jun-de,XU bing,LIANG Yong-dong,et al.Traffic safety assessment of expressway in the accident[J].Journal of Chang’an University (Natural Science Edition),2012,32(2):78.
[9]芮海田,吴群琪,赵跃峰,等.公路建设对区域经济发展的影响分析——以陕西省为例[J].长安大学学报(自然科学版),2012,32(06):83.
　RUI Hai-tian,WU Qun-qi,ZHAO Yue-feng,et al.Influence of highway construction on regional economy development——taking Shaanxi as an example[J].Journal of Chang’an University (Natural Science Edition),2012,32(2):83.
[10]彭 辉,续宗芳,韩永启,等.城市群城际运输结构配置客流分担率模型[J].长安大学学报(自然科学版),2012,32(02):91.
　PENG Hui,XU Zong-fang,HAN Yong-qi,et al.Sharing ratios model of passenger flows in intercity transportation structure configuration among urban agglomeration[J].Journal of Chang’an University (Natural Science Edition),2012,32(2):91.

更新日期/Last Update: 2022-04-27