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考虑OD需求聚类的区域多层公路交通网络混合路径诱导模型

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随着交通出行需求的快速增长,我国高速公路网络面临的运输压力日渐增加,经常出现严重的交通拥堵现象.为了缓解高速公路交通拥堵,并实施更有针对性的交通管控措施,提出了考虑OD需求聚类的区域多层公路交通网络混合路径诱导模型.首先,利用湖南省高速公路以及国道、省道的地理信息数据构建区域多层公路交通网络.然后,根据OD对间距离和OD交通量的差异,利用K-均值聚类算法对OD对进行聚类分析,将OD对划分为3个不同的类别.最后,应用遗传算法筛选出各类OD对中对拥堵贡献较大的出行群体,并建立有针对性的混合路径诱导模型,对拥堵贡献较大和拥堵贡献较小的出行群体分别应用不同的路径诱导方案.当OD需求扩样系数设置为6时,对OD对聚类可以将总出行成本进一步降低35 186.03 min.在不进行OD对聚类时,使用规划路径的出行总数为79 140,而实施OD对聚类后,使用规划路径的出行总数为70 374.使用诱导路径的出行的平均出行时间由121.47 min下降为85.61 min,极少数出行(3.75%)的时间增加,且增加最大值低于3 min.对多个不同扩样系数进行敏感性分析进一步说明了考虑OD需求聚类的混合路径诱导模型具有良好的拥堵缓解效果.考虑OD需求聚类的区域多层公路交通网络混合路径诱导模型可以用于识别对拥堵贡献较大的关键出行群体,进而制定有针对性的路径诱导策略,在缓解高速公路交通拥堵的同时能够减少对大多数出行者的影响,降低路径诱导策略的实施难度.另外,研究结果还表明:对出行距离较长的出行群体实施路径诱导能够更加有效地缓解区域多层公路交通网络中的交通拥堵.
Hybrid routing model of regional multi-layer highway transportation network considering the OD demand clustering
With the rapid growth of travel demand,the transportation pressure posed on the highway networks of China is increasing gradually,and serious traffic congestion occurs frequently.In order to alleviate traffic congestion on highways and implement more targeted traffic control strategies,a hybrid routing model considering the OD demand clustering for regional multi-layer highway transportation networks was proposed.First,the regional multi-layer highway transportation network was generated using the geographic information data of Hunan expressway and national and provincial highway.Next,based on the distance and traffic volume of each OD pair,the K-means clustering algorithm was used to conduct clustering analysis on OD pairs,dividing them into three categories.Finally,the genetic algorithm was used to select the travelers contributing to major traffic congestion and generate the hybrid routing model,and different routing schemes were applied to the travelers who contribute to major traffic congestion and the travelers who do not contribute to major traffic congestion.When the OD demand expansion coefficient was set to 6,the total travel cost is further reduced by 35 186.03 minutes after clustering OD pairs.Without OD pair clustering,the total number of trips using the planned path is 79 140,while after OD pair clustering,the total number of trips using the planned path is 70 374.The average travel time of trips using the planned path decreases from 121.47 minutes to 85.61 minutes.The average travel time of very few trips(3.75%)increases,with the maximum increase being less than 3 minutes.Sensitivity analysis on multiple expansion coefficients further demonstrates that the hybrid routing model considering the OD demand clustering can achieve a good congestion mitigation effect.The proposed model can be used to identify the key travelers contributing to major traffic congestion,thereby develop targeted routing strategies,which can alleviate traffic congestion on expressways,reduce the influence on most travelers and the implementation difficulty of the routing strategies.In addition,the results show that implementing route guidance for long-distance travelers can more effectively alleviate traffic congestion in regional multi-layer highway transportation networks.

multi-layer networkcongestion alleviationcluster analysishybrid routing modelgenetic algorithm

王璞、王天浩、阳虎

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中南大学 交通运输工程学院,湖南 长沙 410075

多层网络 拥堵缓解 聚类分析 混合路径诱导模型 遗传算法

湖南省自然科学基金杰出青年基金湖南省交通厅科技进步与创新项目

2022JJ10077202102

2024

铁道科学与工程学报
中南大学 中国铁道学会

铁道科学与工程学报

CSTPCD北大核心EI
影响因子:0.837
ISSN:1672-7029
年,卷(期):2024.21(4)
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