可变标线干预下的快速路交织区运行

陈纪龙; 陈丰; 张婷; 李璜; 潘晓东

doi:10.3969/j.issn.0258-2724.20240077

可变标线干预下的快速路交织区运行

doi: 10.3969/j.issn.0258-2724.20240077

陈纪龙^1,,
陈丰^1, ,,
张婷¹,
李璜²,
潘晓东¹

1.
同济大学道路与交通工程教育部重点实验室，上海 201804
2.
中国铁路广州局集团有限公司，广州 510030

基金项目: 国家自然科学基金项目（51978522）

详细信息

作者简介:
陈纪龙（2000—），男，博士研究生，研究方向为交通安全，E-mail：chenjilong1225@tongji.edu.cn

通讯作者:
陈丰（1982—），男，教授，研究方向为交通安全，E-mail：fengchen@tongji.edu.cn

中图分类号: U491.1
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- 文章访问数: 27
- HTML全文浏览量: 15
- PDF下载量: 9
- 被引次数: 0
出版历程
- 收稿日期: 2024-02-19
- 修回日期: 2024-06-13
- 网络出版日期: 2026-01-05

Operation of Expressway Weaving Sections under Variable Marking Intervention

1.
Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
2.
China Railway Guangzhou Group Co., Ltd., Guangzhou 510030, China

摘要

摘要:
针对城市快速路交织区内固定标线控制存在的缺陷，本文提出基于元胞自动机的快速路交织区可变标线干预，以根据交通场景需要灵活变换标线形式，体现多标线控制策略的优势. 首先，基于三相交通流理论建立元胞自动机模型，为模糊控制器的建立提供基础；其次，生成可变标线主动干预的策略库并构建模糊控制器，以实现可变标线控制下交织区场景的全时段仿真；然后，通过选取上海市交织区线圈数据和典型高峰期交通流量数据作为交通流输入进行全时段仿真，输出得到标线控制方案；最后，从运行效率、潜在事故风险和污染物排放共3个方面对干预效果进行评价. 研究结果表明：在可变标线干预下，现实工况与设计工况场景的平均延误相比普通标线显著降低，其中，设计工况从71 s降低至48 s；现实工况中可变标线干预下的危险场景数量相比普通标线降低了23.4%；车辆排放的几类重要污染物均值均有明显减小.
- 城市交通 /
- 可变标线 /
- 元胞自动机 /
- 快速路交织区 /
- 微观仿真
Abstract:
Variable marking intervention in expressway weaving sections based on the cellular automaton was proposed by combining the advantage that variable markings can flexibly change the marking form according to the needs of traffic scenarios and provide more marking control strategies to solve the problems of fixed marking control in the weaving sections of urban expressways, with the intervention effect evaluated. First, the cellular automaton model was built based on the three-phase traffic flow theory to provide a basis for fuzzy controller building. Second, the strategy library of active variable marking intervention was generated, and the fuzzy controller was constructed to realize the full-time simulation of weaving section scenarios under variable marking control. By selecting the coil data of weaving sections and typical traffic flow data during peak periods in Shanghai as the traffic flow input for full-time simulation, the output was obtained for the marking control scheme. Finally, the intervention effect was evaluated in terms of operation efficiency, potential accident risk and pollutant emission. The results show that the average delays of the scenarios of real working conditions and designed working conditions are significantly reduced under variable marking intervention compared with ordinary markings, with the average delay of the designed working conditions decreasing from 71 to 48 s. The number of hazardous scenarios under variable marking intervention in real working conditions is reduced by 23.4% compared with ordinary markings. The mean values of several important pollutants emitted by the vehicles are significantly reduced.
- urban traffic /
- variable marking /
- cellular automaton /
- expressway weaving section /
- microsimulation

HTML全文

图 1 上海市延安高架交织区卫星图

Figure 1. Satellite map of Yan’an elevated weaving sections in Shanghai

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图 2 城市快速路交织区结构示意

Figure 2. Structure of urban expressway weaving sections

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图 3 仿真场景交织区内车道形式

Figure 3. Lane form of weaving sections in simulated scenarios

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图 4 实线控制的道路元胞场景

Figure 4. Real line-controlled road cellular scenarios

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图 5 虚线控制的道路元胞场景

Figure 5. Dotted line-controlled road cellular scenarios

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图 6 车辆交互逻辑

Figure 6. Vehicle interaction logic

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图 7 标线输出隶属度函数

Figure 7. Membership function output by marking

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图 8 Scenario_VL_18时空演化图

Figure 8. Spatio-temporal evolution of Scenario_VL_18

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图 9 车道1、2拥堵仿真

Figure 9. Congestion simulation of Lanes 1 and 2

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图 10 延安高架北线茂名路-华山路交织区线圈布设

Figure 10. Coil laying in Maoming Road-Huashan Road weaving section of Yan’an elevated north line

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图 11 典型工作日全时段真实交通流数据

Figure 11. Full-time real traffic flow data of typical weekdays

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图 12 典型工作日全时段设计交通流数据

Figure 12. Full-time designed traffic flow data of typical weekdays

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图 13 真实交通流输出控制方案

Figure 13. Output control scheme of real traffic flow

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图 14 设计交通流输出控制方案

Figure 14. Output control scheme of designed traffic flow

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表 1 交通流时空图对比

Table 1. Spatio-temporal map of traffic flow

L_C/m	标线类型	车道 1	车道 2	车道 3	车道 4
100	传统路面标线	①	②	③	④
100	可变木标线	⑤	⑥	⑦	⑧
500	传统路面标线	⑨	⑩	⑪	⑫
500	可变木标线	⑬	⑭	⑮	⑯

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表 2 L_R影响下的交通流时空图

Table 2. Spatio-temporal map of traffic flow under influence of L_R

随机慢化概率	车道 1	车道 2	车道 3	车道 4
传统路面标线（0.3）	①	②	③	④
可变木标线（0.4）	⑤	⑥	⑦	⑧
传统路面标线（0.3）	⑨	⑩	⑪	⑫
可变木标线（0.4）	⑬	⑭	⑮	⑯

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表 3 模糊变量$\beta_{\mathrm{express}} $赋值表

Table 3. Fuzzy variable $\beta_{\mathrm{express}} $ assignment

$ \beta_{\mathrm{express}} $		$ \beta_{\text{ramp}} $
$ \beta_{\mathrm{express}} $		US	VS	QS	QL	VL	UL
$ {p}_{{\mathrm{DR}}} $	US	1	1	1	0	0	0
	VS	1	1	0/1/1/1/1	0	0	0
	QS	1	1	0/1/0/1/0	0	0	0
	QL	1	1	0	0	0	0
	VL	1	1/0/0/1/0	0	0	0	0
	UL	0/0/0/1/0	0	0	0	0	0

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表 4 平均延误计算结果

Table 4. Average delay calculations

交通流类型	平均延误/s
交通流类型	可变标线干预	普通标线（实线）
现实交通流	12	18
设计交通流	48	71

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表 5 现实交通流工况下冲突场景统计

Table 5. Conflict scenarios statistics for realistic traffic flow

标线类型	场景数量/个
标线类型	危险	严重冲突	轻度冲突
可变标线干预	341	229	912
普通标线	445	341	771

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表 6 设计交通流工况下冲突场景统计

Table 6. Conflict scenario statistics for designed traffic flow

标线类型	场景数量/个
标线类型	危险	严重冲突	轻度冲突
可变标线干预	883	748	1 967
普通标线	775	992	2 094

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表 7 现实交通流工况下污染物排放率

Table 7. Pollutant emission rates for r realistic traffic flow

标线类型	污染物排放率/（mg·s⁻¹）
标线类型	CO	HC	NO_x
可变标线干预	97.625 8	5.342 5	19.513 6
普通标线	105.698 4	6.220 6	22.301 1

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表 8 设计交通流工况下污染物排放率

Table 8. Pollutant emission rates for designed traffic flow

标线类型	污染物排放率/（mg·s⁻¹）
标线类型	CO	HC	NO_x
可变标线干预	100.298 7	6.790 5	20.531 7
普通标线	117.117 0	7.012 2	24.910 5

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