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于澎, 张维伦, 何娟, 冯菲, 杨瑿. 基于铁路客票系统MaaS+智能服务平台的多模式行程规划方法初步研究[J]. 铁路计算机应用, 2023, 32(8): 73-78. DOI: 10.3969/j.issn.1005-8451.2023.08.13
引用本文: 于澎, 张维伦, 何娟, 冯菲, 杨瑿. 基于铁路客票系统MaaS+智能服务平台的多模式行程规划方法初步研究[J]. 铁路计算机应用, 2023, 32(8): 73-78. DOI: 10.3969/j.issn.1005-8451.2023.08.13
YU Peng, ZHANG Weilun, HE Juan, FENG Fei, YANG Yi. Preliminary study on multimodal journey planning based on MaaS + intelligent service platform of China railway ticketing and reservation system[J]. Railway Computer Application, 2023, 32(8): 73-78. DOI: 10.3969/j.issn.1005-8451.2023.08.13
Citation: YU Peng, ZHANG Weilun, HE Juan, FENG Fei, YANG Yi. Preliminary study on multimodal journey planning based on MaaS + intelligent service platform of China railway ticketing and reservation system[J]. Railway Computer Application, 2023, 32(8): 73-78. DOI: 10.3969/j.issn.1005-8451.2023.08.13

基于铁路客票系统MaaS+智能服务平台的多模式行程规划方法初步研究

Preliminary study on multimodal journey planning based on MaaS + intelligent service platform of China railway ticketing and reservation system

  • 摘要: 多模式行程规划是中国智能高速铁路2.0运营技术的重要组成部分,是促进客运服务高质量发展和多种交通融合发展的关键技术手段。文章借鉴国内外多种交通模式行程规划先进经验,结合铁路客票发售和预订系统(简称:铁路客票系统)在多式联运方面的实践,依托铁路客票系统出行即服务(MaaS,Mobility as a Service)+智能服务平台,提出多模式行程规划方法框架;该方法划分为数据收集、信息处理和行程优化3个阶段,充分利用各种交通模式已有的路径计算方案,实现多模式行程动态规划。后续将对该方法持续迭代优化,以生成精简、高效的多模式路径集合,使平台推荐的多模式路径方案更贴近旅客实际出行需求。

     

    Abstract: Multimodal journey planning is an important part of operation technologies for China's intelligent high-speed railway 2.0 , and is a key technical means to promote the high-quality development of passenger service and the integrated development of multimodal transportation. Based on the advanced experience of journey planning in multimodal transportation abroad, combined with the practices of China railway ticketing and reservation system in multimodal transport, this paper proposes the framework of multi-mode trip planning method based on the intelligent MaaS+ platform of the system, which is divided into three stages: data collection, data processing and journey optimization, and makes full use of the existing route calculation schemes of different transportations to realize dynamic multimodal journey planning. Subsequently, this method will continue to be iteratively optimized to generate a simple and efficient multi-mode path set so that the multi-mode path scheme recommended by the platform is more close to the actual travel needs of passengers.

     

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