交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (3): 22-31.DOI: 10.16097/j.cnki.1009-6744.2025.03.003

• 多式联运与综合运输 • 上一篇    下一篇

基于客流争夺与补充的轨交对公交非对称竞合关系评价

王殿海1,徐梦丹1,张萌1,曾佳棋*1,2,蔡正义1   

  1. 1. 浙江大学,建筑工程学院,智能交通研究所,杭州310058;2.浙江大学,中原研究院,郑州450001
  • 收稿日期:2024-12-18 修回日期:2025-03-08 接受日期:2025-03-20 出版日期:2025-06-25 发布日期:2025-06-19
  • 作者简介:王殿海(1962—),男,吉林大安人,教授,博士。
  • 基金资助:
    国家自然科学基金(52131202, 52402391)。

Evaluation of Asymmetric Competitive and Cooperative of Rail Transit to Bus Transit Based on Passenger Competition and Complementarity

WANG Dianhai1, XU Mengdan1, ZHANG Meng1, ZENG Jiaqi*1,2, CAI Zhengyi1   

  1. 1. Institute of Intelligent Transportation Systems, College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China; 2. Zhongyuan Institute, Zhejiang University, Zhengzhou 450001, China
  • Received:2024-12-18 Revised:2025-03-08 Accepted:2025-03-20 Online:2025-06-25 Published:2025-06-19
  • Supported by:
    National Natural Science Foundation of China (52131202, 52402391)。

摘要: 对轨交(轨道交通)与公交间的竞合关系进行准确量化是促进公交线路合理规划的前提,本文考虑公交与轨交之间的非对称影响,从客流争夺和补充的角度分析轨交对公交客流的抑制和促进作用。在同一评价维度下,提出竞争度、合作度和竞合度概念,进而建立“站点对-公交站-公交线”三个层次的竞争度、合作度和竞合度评价模型。在此基础上,采用居民出行方式离散选择模型以定量计算竞合指标。基于杭州市4条典型公交线路展开案例研究,对比了考虑客流因素前后各线路的竞合指标分布情况。结果显示,在考虑客流因素后,部分线路的竞合评价结果产生了显著变化,其中143路公交线与轨交2号线的关系由合作变为竞争,竞合度由0.069上升至0.999。最后,本文通过出行需求分布的可视化结果验证了这一变化的合理性,表明所提竞合模型能够有效量化轨交对公交在三个层次上的竞争与合作关系,获得更加真实合理的评价结果。研究结果可用于识别与轨道交通竞争关系显著或者合作程度较低的公交线路,为城市公共交通系统的协调优化提供科学依据。

关键词: 城市交通, 竞合关系, 离散选择模型, 常规公交, 轨道交通, 线网评价

Abstract: Accurately quantifying the competitive and cooperative relationships between rail transit and bus services is a prerequisite for rational public transport route planning. From the perspectives of passenger competition and complementarity, this paper analyzes the suppressive and facilitative effects of rail transit on bus ridership. The concepts of Competition Degree, Cooperation Degree and Coopetition Degree are developed within a unified dimension, and an evaluation model is constructed across three hierarchical levels: station pair, bus station, and bus route. On this basis, the discrete choice model of residents' travel mode is designed to quantitatively calculate the indicators. A case study on four typical bus routes in Hangzhou was conducted, comparing the distribution changes of these indicators before and after incorporating passenger flow factors. The results showed that incorporating passenger flow factors significantly altered the evaluation outcomes for some routes. Specifically, the relationship between bus route 143 and subway line 2 has shifted from cooperation to competition, with the coopetition degree rising from 0.069 to 0.999. In addition, this paper verifies the rationality of this change through the visualization results of travel demand distribution, indicating that the proposed competition and cooperation model can effectively quantify the competitive and cooperative relationships between rail transit and bus transit at three levels, and obtain more realistic and reasonable evaluation results. The research findings can be used to identify bus routes that exhibit significant competition or low cooperation with rail transit, providing a scientific basis for coordinated optimization of the urban public transportation system.

Key words: urban traffic, competitive and cooperative relationships, discrete choice model, bus transit, rail transit, network evaluation

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