[1]张驰,宁子尧,张敏,等.高速公路互通立交交织段硬路肩开放策略[J].长安大学学报(自然科学版),2026,46(2):106-116.[doi:10.19721/j.cnki.1671-8879.2026.02.008]
 ZHANG Chi,NING Zi-yao,ZHANG Min,et al.Hard shoulder opening strategy for weaving sections of expressway interchanges[J].Journal of Chang’an University (Natural Science Edition),2026,46(2):106-116.[doi:10.19721/j.cnki.1671-8879.2026.02.008]
点击复制

高速公路互通立交交织段硬路肩开放策略()
分享到:

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

卷:
第46卷
期数:
2026年2期
页码:
106-116
栏目:
交通工程
出版日期:
2026-04-18

文章信息/Info

Title:
Hard shoulder opening strategy for weaving sections of expressway interchanges
文章编号:
1671-8879(2026)02-0106-11
作者:
张驰1宁子尧1张敏2宋金明1国廷玉1
(1. 长安大学 公路学院,陕西 西安 710064; 2. 长安大学 运输工程学院,陕西 西安 710064)
Author(s):
ZHANG Chi1 NING Zi-yao1 ZHANG Min2 SONG Jin-ming1 GUO Ting-yu1
(1. School of Highway, Chang'an University, Xi'an 710064, Shaanxi, China; 2. School of Transportation Engineering, Chang'an University, Xi'an 710064, Shaanxi, China)
关键词:
交通工程 硬路肩开放 核密度估计 交织区 无人机航拍
Keywords:
traffic engineering hard shoulder opening KDE interchange area UAV
分类号:
U491
DOI:
10.19721/j.cnki.1671-8879.2026.02.008
文献标志码:
A
摘要:
为缓解高峰期间绕城高速公路互通立交交织区的拥堵与安全风险,聚焦硬路肩临时开放策略的安全性与通行效率影响,在定量评估的基础上提出决策建议。利用无人机航拍获取包含主线与匝道全视角的高分辨率车辆轨迹视频,通过DataFromSky 视觉识别软件自动提取车辆路径,并进行数据坐标转换处理,统一度量各车道车辆的运动特征。在此基础上,引入改进的事故时间指数(ITA)以增强对速度差异情境的敏感性,并采用核密度估计方法对车辆合流、分流点进行空间聚类,对比分析硬路肩关闭与开放2种工况下的风险分布。研究结果表明:在硬路肩未开放时,交织区潜在冲突集中于主线内侧一、二车道,风险峰值高达1.8×10-3; 启用硬路肩后,风险热点向外侧车道及硬路肩转移,峰值降至7.0×10-4,主线内侧车道风险显著减小,但当匝道与主线流量比超过0.25或匝道与三车道流量比高于1时,外侧车道和硬路肩容易形成新的拥堵与冲突集聚; 核密度与ITA结果高度相关,揭示了外侧车速差异大和频繁换道是高风险区出现的主要原因; 基于流量比阈值划分,提出按匝道与主线或三车道流量比分段控制硬路肩启闭的策略,并建议配合限速、车道引导等措施,指导在不同流量状态下合理动态开放硬路肩,为城市绕城高速的交通安全管理和效率提升提供科学依据。
Abstract:
To alleviate congestion and safety risks in weaving sections of ring expressway interchanges during peak periods, a quantitative evaluation was carried out to examine the safety and efficiency impacts of temporarily opening the hard shoulder, and decision making recommendations were derived. High resolution vehicle trajectory videos covering the mainline and ramps were obtained by using unmanned aerial vehicles(UAVs). Vehicle paths were automatically extracted via the DataFromSky vision recognition software, and the trajectory data were transformed into a Frenet coordinate system to standardize the motion characteristics across lanes. On this basis, a modified incident time analysis(ITA)index was introduced to enhance sensitivity to speed difference scenarios, and kernel density estimation(KDE)was employed to cluster the spatial distribution of merging and diverging points, so that risk distributions under hard shoulder closed and hard shoulder open conditions were compared. The results show that when the hard shoulder is closed, potential conflicts in the weaving area are concentrated on the first and second inner lanes of the mainline, with risk peaks up to 1.8×10-3, After the hard shoulder is opened, risk hots pots shift toward the outer lane and shoulder, the peak decreases to 7.0×10-4 and the risk on the inner lanes significantly reduces. But when the ramp to mainline flow ratio exceeds 0.25 or the ramp to three lane flow ratio exceeds 1.0, new clusters of congestion and conflicts tend to form on the outer lane and hard shoulder. In addition, the kernel density and ITA results are highly correlated, revealing that large speed difference and frequent lane change in the outer lane are the main reasons for the occurrence of high risk areas. Based on flow ratio thresholds, a segmented control strategy was proposed to open or close the hard shoulder according to the ramp to mainline or ramp to three lane flow ratios. It is suggested that such control should be coordinated with speed limits and lane guidance measures, providing a scientific basis for dynamically opening the hard shoulder under different traffic conditions and improving traffic safety and efficiency on ring expressways.1 tab, 7 figs, 35 refs.

参考文献/References:

[1] 徐金凤.基于交通冲突的快速路合流区安全评价研究[D].西安:长安大学,2024.
XU Jin-feng. Research on safety evaluation of merging sections of expressways based on traffic conflicts[D]. Xi'an: Chang'an University, 2024.
[2]李熙莹,梁靖茹,张伟斌,等.基于航拍视频构建风险指数的交织区拥堵识别方法[J].铁道科学与工程学报,2023,20(2):494-505.
LI Xi-ying, LIANG Jing-ru, ZHANG Wei-bin, et al. Congestion identification method for weaving sections based on a risk index from aerial photography[J]. Journal of Railway Science and Engineering, 2023, 20(2): 494-505.
[3]HU Y, LI Y, HUANG H, et al. A high-resolution trajectory data driven method for real-time evaluation of traffic safety[J]. Accident Analysis and Prevention, 2022, 165: 1-10.
[4]KAR P, VENTHURUTHIYIL S, CHUNCHU M. Crash risk estimation of heavy commercial vehicles on horizontal curves in mountainous terrain using proactive safety method[J].Accident Analysis and Prevention, 2024, 199: 1-9.
[5]王 博,刘昌赫,张 驰,等.基于道路监控的高速公路作业区碰撞风险预警[J].浙江大学学报(工学版),2024,58(6):1221-1232.
WANG Bo, LIU Chang-he, ZHANG Chi, et al. Collision risk early-warning for expressway work zones based on roadway monitoring[J]. Journal of Zhejiang University(Engineering Science), 2024, 58(6): 1221-1232.
[6]DIXON K, FITZPATRICK K, AVELAR R. Operational and safety trade-offs: Reducing freeway lane and shoulder width to permit an additional lane[J]. Journal of the Transportation Research Board, 2016, 2588(1): 89-97.
[7]孙 颖.高速公路硬路肩缓解拥堵的措施[J].中国交通信息化,2014(11):28-30.
SUN Ying. Measures for alleviating congestion by using hard shoulders on expressways[J]. China Transportation Informatization, 2014(11): 28-30.
[8]刘星良,谢 厅,刘唐志,等.基于HNAC-FD的高速公路网应急疏导措施效用评估[J].中国安全科学学报,2023,33(7):222-229.
LIU Xing-liang, XIE Ting, LIU Tang-zhi, et al. Effectiveness evaluation of emergency diversion measures for expressway network based on HNAC-FD[J]. China Safety Science Journal, 2023, 33(7): 222-229.
[9]COFFEY S, PARK S. Part-time shoulder use operational impact on the safety performance of interstate 476[J]. Traffic Injury Prevention, 2020, 21(7): 470-475.
[10]李瑞敏,叶 朕,李 斌.高速公路临时路肩使用措施优化控制与仿真[J].系统仿真学报,2018,30(3):1036-1045.
LI Rui-min, YE Zhen, LI Bin. Optimization control and simulation of temporary shoulder use measures on expressways[J]. Journal of System Simulation, 2018, 30(3): 1036-1045.
[11]王李轩.基于KDE与GWR的城市出租车载客出行特征研究——以西安市为例[D].西安:长安大学,2021.
WANG Li-xuan. Research on urban taxi passenger trip characteristics based on KDE and GWR: A case study of Xi'an[D]. Xi'an: Chang'an University, 2021.
[12]马小龙,余 强,刘建蓓,等.基于无人机视频拍摄的高速公路小型车换道行为特性[J].中国公路学报,2020,33(6):95-105.
MA Xiao-long, YU Qiang, LIU Jian-bei, et al. Lane-changing behavior of passenger cars on expressways based on UAV video analysis[J]. China Journal of Highway and Transport, 2020, 33(6): 95-105.
[13]孙 璐,李颜平,钱 军,等.基于交通冲突技术的交织区交通安全评价[J].中国安全科学学报,2013,23(1):55-60.
SUN Lu, LI Yan-ping, QIAN Ju, et al. Traffic safety evaluation of weaving areas based on traffic conflict technology[J]. China Safety Science Journal, 2013, 23(1): 55-60.
[14]胡立伟,陈 琛,赵雪亭,等.基于行车风险场的快速路短交织区车辆交互风险识别[J].交通运输系统工程与信息,2024,24(3):221-231.
HU Li-wei, CHEN Chen, ZHAO Xue-ting,et al. Identification of vehicle interaction risk in short weaving sections of urban expressways based on driving risk field[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(3): 221-231.
[15]CHEN P, ZENG W, YU G. Assessing right-turning vehicle-pedestrian conflicts at intersections using an integrated microscopic simulation model[J]. Accident Analysis and Prevention, 2019, 129: 211-224.
[16]KAMEL A, SAYED T, FU C. Real-time safety analysis using autonomous vehicle data: A Bayesian hierarchical extreme value model[J]. Transportmetrica B: Transport Dynamics, 2023, 11(1): 826-846.
[17]马 菲.基于轨迹数据的快速路交织区交通风险评估[D].济南:山东大学,2024.
MA Fei. Traffic risk assessment of expressway weaving sections based on trajectory data[D]. Jinan: Shandong University, 2024.
[18]ZHONG G, DU S, ZHANG H, et al. Demarcation method of safety separations for sUAV based on collision risk estimation[J]. Reliability Engineering & System Safety, 2024, 242: 109738.
[19]YU R, HAN L, ZHANG H. Trajectory data based freeway high-risk events prediction and its influencing factors analyses[J]. Accident Analysis and Prevention, 2021, 154: 106085.
[20]夏号杰.基于车辆轨迹的城市快速路合流区危险驾驶行为识别方法研究[D].重庆:重庆交通大学,2023.
XIA Hao-jie. Study on methods for identifying dangerous driving behavior in urban expressway merging sections based on vehicle trajectories[D]. Chongqing: Chongqing Jiaotong University, 2023.
[21]徐汉清.高速公路典型区段交通冲突及安全性评价研究[D].哈尔滨:哈尔滨工业大学,2014.
XU Han-qing. Research on traffic conflicts and safety evaluation of typical expressway segments[D]. Harbin: Harbin Institute of Technology, 2014.
[22]段鑫鹏.基于合流区通行效率的超多车道高速交通组织方式选用研究[D].西安:长安大学,2022.
DUAN Xin-peng. Study on the selection of multi-lane expressway traffic organization schemes based on merging section efficiency[D]. Xi'an: Chang'an University, 2022.
[23]仲媛媛.基于交通冲突的公路平面交叉口模糊安全评价研究[D].哈尔滨:哈尔滨工业大学,2007.
ZHONG Yuan-yuan. Fuzzy safety evaluation of highway at-grade intersections based on traffic conflicts[D]. Harbin: Harbin Institute of Technology, 2007.
[24]MAHAJAN V, KATRAKAZAS C, ANTONIOU C. Crash risk estimation due to lane changing: A data-driven approach using naturalistic data[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(4): 1-11.
[25]田润泽.高速公路交通拥堵识别和预判方法研究[D].桂林:桂林电子科技大学,2024.
TIAN Run-ze. Research on recognition and prediction methods for expressway traffic congestion[D]. Guilin: Guilin University of Electronic Technology, 2024.
[26]谢 寒,蒋阳升,蒋若曦,等.城市快速路交织区换车道次数与车速、密度的关系实证研究[J].武汉理工大学学报,2012,34(8):75-81.
XIE Han, JIANG Yang-sheng, JIANG Ruo-xi, et al. Empirical study on correlation among lane-changing frequency, speed, and density in urban expressway weaving sections[J]. Journal of Wuhan University of Technology, 2012, 34(8): 75-81.
[27]GARCIA M, LIZARAZO J, MANGONES S, et al. Safety performance of dedicated and preferential bus lanes using multivariate negative binomial models for Bogota, Colombia[J]. Accident Analysis and Prevention, 2024, 202: 1-10.
[28]BROOKS-RUSSELL A, BROWN T, FRIEDMAN K, et al. Simulated driving performance among daily and occasional cannabis users[J]. Accident Analysis and Prevention, 2021, 160: 106326.
[29]张 菁,巨永锋.快速路交织区交通流模型研究[J].中国公路学报,2011,24(5):89-93.
ZHANG Jing, JU Yong-feng. Study on traffic flow modeling for urban expressway weaving sections[J]. China Journal of Highway and Transport, 2011, 24(5): 89-93.
[30]ABDELRAHMAN A. Safety evaluation of innovative intersection designs: Diverging diamond interchanges and displaced Left-turn Intersections[D]. Lincoln: University of Nebraska-Lincoln, 2019.
[31]陈纪龙,陈 丰,张 婷,等.可变标线干预下的快速路交织区运行研究[J/OL].西南交通大学学报,2024.https://link.cnki.net/urlid/51.1277.U.20240
704.1405.002.
CHEN Ji-long, CHEN Feng, ZHANG Ting, et al. Study on urban expressway weaving sections under variable marking intervention[J/OL]. Journal of Southwest Jiaotong University, 2024. https://link.cnki.net/urlid/51.1277.U.20240704.1405.002.
[32]尚永毅,何廷全,卢国华,等.微观交通仿真参数校正下高速公路合流区交通运行状态研究[J].交通工程,2024,24(8):31-37.
SHANG Yong-yi, HE Ting-quan, LU Guo-hua, et al. Study on traffic operation status in freeway merging sections under microscopic simulation parameter calibration[J]. Traffic Engineering, 2024, 24(8): 31-37.
[33]戴骏晨.基于交通冲突技术的高速公路互通立交交织区交通安全评价[D].南京:东南大学,2017.
DAI Jun-chen. Traffic safety evaluation of expressway interchange weaving segments based on traffic conflict technology[D]. Nanjing: Southeast University, 2017.
[34]张 驰,高艳阳,杨榕玮,等.基于航拍数据的互通隧道小净距路段运行速度模型[J].长安大学学报(自然科学版),2024,44(2):136-150.
ZHANG Chi, GAO Yan-yang, YANG Rong-wei, et al. Operating speed model for short-clearance sections of interchange tunnels based on aerial photography data[J]. Journal of Chang'an University(Natural Science Edition), 2024, 44(2): 136-150.
[35]张 敏,陈嘉乐,张 驰,等.基于航拍数据的高速公路出口环圈匝道行车安全性评价方法[J].长安大学学报(自然科学版),2024,44(4):108-118.
ZHANG Min, CHEN Jia-le, ZHANG Chi, et al. Driving safety evaluation method for highway exit loop ramps based on aerial photography data[J]. Journal of Chang'an University(Natural Science Edition), 2024, 44(4): 108-118.

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.

备注/Memo

备注/Memo:
收稿日期:2025-08-22
基金项目:国家重点研发计划项目(2020YFC1512005); 四川省科技计划项目(2022YFG0048); 陕西省社会科学基金项目(2025R018)
作者简介:张 驰(1981-),男,四川宜宾人,教授,工学博士,从事公路路线安全研究,E-mail:zhangchi@chd.edu.cn。
更新日期/Last Update: 2026-04-20