交通运输系统工程与信息 ›› 2015, Vol. 15 ›› Issue (3): 13-18.

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基于非集计理论的高速铁路旅客乘车选择行为研究

王文宪a,b,倪少权*a,b,吕红霞a,b,郭经纬a   

  1. 西南交通大学a. 交通运输与物流学院;b. 全国铁路列车运行图编制研发培训中心成都610031
  • 收稿日期:2014-11-25 修回日期:2015-03-09 出版日期:2015-06-25 发布日期:2015-06-29
  • 作者简介:王文宪(1986-),男,湖北孝感人,博士生.
  • 基金资助:

    国家自然基金项目(61273242,61403317);中国铁路总公司科技研究计划项目(2013X006-A)

Boarding Choice for High-speed Railway Passengers Based on Disaggregate Theory

WANGWen-xiana,b, NI Shao-quana,b, LV Hong-xiaa,b, GUO Jing-weia   

  1. a. School of Traffic and Transportation; b. National Railway Train Diagram Research and Training Center, Southwest Jiaotong University, Chengdu 610031, China
  • Received:2014-11-25 Revised:2015-03-09 Online:2015-06-25 Published:2015-06-29

摘要:

为研究高速铁路旅客乘车行为选择机理,以非集计离散选择模型理论为依据,分析旅客乘车选择的影响因素,结合2013 年京沪高速铁路旅客出行RP调查数据,以G类高速列车和D类高速列车作为旅客乘车方式选择肢,设置影响旅客乘车选择的特性变量,即旅客主体特性、出行特性、列车服务特性及相应的取值方法,建立旅客乘车方案选择MNL模型.运用SPSS对模型参数进行标定,结果表明,公费出行、月收入较高及出差的旅客偏好选择G类高速列车;自费出行、月收入较低及旅游探亲的旅客偏好选择D类高速列车.上述结论与调查结果基本一致,命中率等参数的计算亦验证了模型的有效性.

关键词: 铁路运输, 非集计离散选择模型, 旅客乘车选择, RP 调查数据, MNL模型, 命中率

Abstract:

In order to comprehend the boarding choice mechanism of railway passengers, this paper analyzes major factors on the base of disaggregate discrete choice theory. Referring to the survey data of travel of Beijing-Shanghai high-speed railway in 2013, three travel ways including G and D high-speed trains are selected as a alternative set, and characteristic variables affecting mode choice and the method of getting its values are determined, then a multinomial Logit model (MNL) is developed finally. The model’s parameters are calibrated by applying SPSS. The results show that passengers on business with government scholarship and higher monthly income prefer G high-speed trains, and passengers on visit with own scholarship and lower monthly income prefer D high-speed trains. This completion is consistent with the survey results. Finally, model’s validity is testified by calculating the hit ratio and other parameters.

Key words: railway transportation, disaggregate discrete choice model, boarding choice of railway passenger, RP survey data, multinomial Logit model, hit radio

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