基于多点线圈联合数据的高速公路匝道影响范围识别

doi:10.16097/j.cnki.1009-6744.2022.03.007

交通运输系统工程与信息 ›› 2022, Vol. 22 ›› Issue (3): 53-62.DOI: 10.16097/j.cnki.1009-6744.2022.03.007

• 智能交通系统与信息技术 • 上一篇下一篇

基于多点线圈联合数据的高速公路匝道影响范围识别

李岩，曾明哲，朱才华，汪帆^*，邓亚娟

长安大学，运输工程学院，西安 710064

收稿日期:2021-11-21 修回日期:2022-03-04 接受日期:2022-03-10 出版日期:2022-06-25 发布日期:2022-06-22
作者简介:李岩(1983- )，男，河北衡水人，教授，博士。
基金资助:
国家自然科学基金;陕西省自然科学基础研究计划项目

Identification of Freeway Ramp Influence Areas Based on Multi-point Loop Data

LI Yan, ZENG Ming-zhe, ZHU Cai-hua, WANG Fan^* , DENG Ya-juan

College of Transportation Engineering, Chang'an University, Xi'an 710064, China

Received:2021-11-21 Revised:2022-03-04 Accepted:2022-03-10 Online:2022-06-25 Published:2022-06-22
Supported by:
National Natural Science Foundation of China (51408049)；Natural Science Basic Research Plan in Shaanxi Province (2020JM-237)。

摘要/Abstract

摘要： 为准确识别高速公路匝道对主线车流的影响等级和范围，本文提出基于速度波动特性的高速公路匝道影响量化方法。通过建立改进加权速度排列熵指标以量化各服务水平下匝道对高速公路主线车流的影响，对建立的指标进行谱聚类分析来确定匝道的影响阈值。应用京昆高速及二广高速的99个平行式合流匝道和直接式分流匝道多点主线线圈检测器数据的分析结果表明，所提出方法可识别高速公路主线车流受匝道的影响程度。合流匝道对主线最外侧车道的影响比次外侧车道高4%~69%；A~C级服务水平下，分流匝道对上游主线最外侧车道影响程度比次外侧车道高6%~29%，D~F级服务水平下，最外侧车道受影响程度比次外侧车道低10%~13%。合流匝道的影响范围是合流点上游350m至下游550m；其中上游160m至下游100m和下游180~ 270m为核心影响范围。分流匝道影响范围为分流点至主线上游850m，其中750~850m、450~ 600m、100~300m为核心影响范围。研究成果可为高速公路匝道交通设计、管控策略和提升仿真可靠性提供依据，可有效降低设置匝道带来的影响。

关键词: 交通工程, 匝道影响范围, 速度波动特性, 改进加权速度排列熵, 多点线圈联合数据

Abstract: To accurately identify the influence of the freeway ramp on mainline traffic, a quantitative method is proposed based on the speed fluctuation characteristics. The improved weighted speed permutation entropy (IWSPE) is established to quantify the influence of freeway ramp under various levels of services (LOSs). The spectral clustering method is selected to determine the impact threshold of the freeway ramp using the proposed indicators. Using the data from 99 loop detectors located at parallel merge ramp and direct diverge ramp in G5 and G55 freeway of China, the results show that the proposed method can identify the influence brought by the ramp. The influence of the merge ramp to the outermost lane is 4%~69% higher than it to the secondary outer lane. The diverge ramp has an influence of 6%~ 29% higher to the outermost lane than the secondary outer lane under LOS A to C, while this influence is 10%~13% lower under LOS D to F. The influence area of the merge ramp ranges from 350 m upstream to 550 m downstream, with the core influence areas of 160 m upstream to 100 m downstream and 180~270 m downstream. The influence of diverge ramp to mainline traffic ranges from diverging point to 850 m upstream, with the core influence areas of 750~ 850 m, 450~600 m, and 100~300 m. The proposed method can contribute to the design, management and control, and reliability of traffic simulation of freeway ramp areas, which can effectively reduce the impact of the ramp.

Key words: traffic engineering, freeway ramp influence areas, speed fluctuation characteristic, improved weighted speed permutation entropy, multi-point loop data

中图分类号:

U491

李岩, 曾明哲, 朱才华, 汪帆, 邓亚娟. 基于多点线圈联合数据的高速公路匝道影响范围识别[J]. 交通运输系统工程与信息, 2022, 22(3): 53-62.

LI Yan, ZENG Ming-zhe, ZHU Cai-hua, WANG Fan , DENG Ya-juan. Identification of Freeway Ramp Influence Areas Based on Multi-point Loop Data[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(3): 53-62.

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基于多点线圈联合数据的高速公路匝道影响范围识别

Identification of Freeway Ramp Influence Areas Based on Multi-point Loop Data

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