Volume 42 Issue 6
Dec.  2024
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ZHANG Rui, XUE Ziwei, LIU Xinrui. Level of Service Optimization Method for Airport Rail Transit Considering Travel Behavior[J]. Journal of Transport Information and Safety, 2024, 42(6): 143-151. doi: 10.3963/j.jssn.1674-4861.2024.06.015
Citation: ZHANG Rui, XUE Ziwei, LIU Xinrui. Level of Service Optimization Method for Airport Rail Transit Considering Travel Behavior[J]. Journal of Transport Information and Safety, 2024, 42(6): 143-151. doi: 10.3963/j.jssn.1674-4861.2024.06.015
shu

Level of Service Optimization Method for Airport Rail Transit Considering Travel Behavior

doi: 10.3963/j.jssn.1674-4861.2024.06.015
  • 1.

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

  • 2.

    Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China

  • Received Date: 2023-12-07
    Available Online: 2025-03-08
    Abstract
  • This paper aims to balance the utilization rate of transport capacity, level of service and operational profit for airport rail transit, a level of service optimization method for airport rail transit is proposed, considering travel behavior. Specifically, a nested Logit (NL) model considering behavior inertia is established to simulate the landside travel mode choice behavior of passengers accessing the airport. The model includes variables related to behavioral inertia, such as revealed preference (RP) dependence, stated preference (SP) dependence, local residency, and transfer difficulty. On this basis, a level of service optimization model for airport rail transit is built to investigate the relationships among level of service factors, such as ticket price, departure interval, peak hour load factor, as well as market share of rail transit and operation profit of rail transit. Corresponding level of service optimization proposals are then presented. The results of case study conducted in Xi' an city show that: ① SP survey results are influenced by behavioral inertia. Specifically, the current SP questionnaire survey results of respondents are positively dependent on their actual travel choice behaviors and the previous SP survey results, while the dependence on actual travel choice behavior is higher than that on previous SP survey results. ②The proposed NL model, which considers behavioral inertia, outperforms the conventional multinomial Logit (MNL) model that does not account for behavioral inertia. The R-squared value of the NL model is improved by 40.86% compared to the MNL model. ③The proposed optimization model can be solved using enumeration method. If the congestion degree of the current airport rail transit ("somewhat crowded") in the case city is expected to reach the "critical state" threshold, to avoid a decrease in the market share of rail transit and maximize ticket revenue, it is recommended that the ticket price be increased by 3 yuan, provided that the departure interval is reduced by 1 minute.

     

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    • References(21)
  • [1]
    刘晓庆, 孙继营, 杨晓飞, 等. 北京大兴国际机场轨道交通专线延时运营方案设计研究[J]. 铁道运输与经济, 2022, 44 (1): 127-133.

    LIU X Q, SUN J Y, YANG X F, et al. Design of operation extension plan for Beijing Daxing international airport express at night[J]. Railway Transport and Economy, 2022, 44(1): 127-133. (in Chinese)
    [2]
    何文晖, 孙克洋, 王兵, 等. 考虑空铁联运的城市轨道交通时刻表优化研究[J]. 铁道科学与工程学报, 2022, 19(2): 351-358.

    HE W H, SUN K Y, WANG B, et al. Optimization of urban rail transit timetable considering air-rail intermodal transportation[J]. Journal of Railway Science and Engineering, 2022, 19 (2): 351-358. (in Chinese)
    [3]
    罗强, 陈军华, 高国飞. 基于不同功能定位的轨道交通机场线规划与运营问题研究[J]. 铁道标准设计, 2021, 65(7): 59-64.

    LUO Q, CHEN J H, GAO G F. Research on the planning and operation of airport rail transit based on different functional positioning[J]. Railway Standard Design, 2021, 65(7): 59-64. (in Chinese)
    [4]
    郭东博, 姚恩建, 卢天伟, 等. 同台换乘场景下考虑不均匀发车间隔的地铁接驳市域铁路时刻优化[J]. 北京交通大学学报, 2022, 46 (6): 18-26.

    GUO D B, YAO E J, LU T W, et al. Timetable optimization for feeder subway in urban railway and subway single-platform-interchange considering uneven departure interval[J]. Journal of Beijing Jiaotong University, 2022, 46(6): 18-26. (in Chinese)
    [5]
    李岩, 巩亮, 许得杰, 等. 基于虚拟编组的城轨列车时刻表优化方法[J]. 交通信息与安全, 2024, 42 (3): 74-84. doi: 10.3963/j.jssn.1674-4861.2024.03.008

    LI Y, GONG L, XU D J, et al. A timetable optimization method for urban train transit based on virtual coupling[J]. Journal of Transport Information and Safety, 2024, 42(3): 74-84. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2024.03.008
    [6]
    梁金鹏, 赵莲芳, 李利鸣, 等. 兼顾效率与公平的城市轨道交通客流控制优化[J/OL]. (2024-07-06)[2024-11-20]. http://kns.cnki.net/kcms/detail/11.4520.U.20240926.0942.002.html.

    LIANG J P, ZHAO L F, LI L M, et al. Optimizing urban rail transit passenger flow control for efficiency and fairness[J/OL]. (2024-07-06) [2024-11-20]. http://kns.cnki.net/kcms/detail/11.4520.U.20240926.0942.002.html. (in Chinese)
    [7]
    陈治亚, 苏慧杰, 徐光明, 等. 基于大小交路的城轨列车开行频率与票价综合优化方法[J]. 铁道科学与工程学报, 2023, 20 (1): 94-104.

    CHEN Z Y, SU H J, XU G M, et al. Comprehensive optimization method of urban rail line operation frequency and ticket price based on full-length and short-turn routing[J]. Journey of Railway Science and Engineering, 2023, 20(1): 94-104. (in Chinese)
    [8]
    汪晴, 邓连波, 许景. 城市轨道交通差异化票价和补贴优化[J]. 交通运输系统工程与信息, 2022, 22 (5): 26-36.

    WANG Q, DENG L B, XU J. Optimization of differentiated fares and subsidies for urban rail transit[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22 (5): 26-36. (in Chinese)
    [9]
    程苑, 宋素娟, 马毅林, 等. 轨道交通机场专线定价模型研究[J]. 铁道运输与经济, 2023, 45 (12): 122-130.

    CHENG Y, SONG S J, MA Y L, et al. Research on pricing models for urban rail airport express lines[J]. Railway Transport and Economy, 2023, 45 (12): 122-130. (in Chinese)
    [10]
    冯社苗. 基于机场轨道交通快慢线共存的航空出发旅客选择行为研究[J]. 城市轨道交通研究, 2023, 26 (5): 289-292

    FENG S M. Research on choice behavior of air departure passengers based on the coexistence of airport rail transit fast and slow lines[J]. Urban Mass Transit, 2023, 26(5): 289-292. (in Chinese)
    [11]
    WANG Z J, JIA H H, DAI F Z, et al. Understanding the ground access and airport choice behavior of air passengers using transit payment transaction data[J]. Transport Policy, 2022, 127: 179-190.
    [12]
    刘锴, 王静, 王江波, 等. 考虑个体偏好异质性的定制公交选择行为[J]. 中国公路学报, 2024, 37 (6): 279-287.

    LIU K, WANG J, WANG J B, et al. Study on customized bus choice behavior considering individual preference heterogeneity[J]. China Journal of Highway and Transport, 2024, 37 (6): 279-287. (in Chinese)
    [13]
    GAO K, YANG Y, SUN L J, et al. Revealing psychological inertia in mode shift behavior and its quantitative influences on commuting trips[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2020, 71: 272-287. http://www.sciencedirect.com/science/article/pii/S1369847820304022
    [14]
    BHAT C R, CASTELAR S. A unified mixed Logit framework for modeling revealed and stated preferences: formulation and application to congestion pricing analysis in the San Francisco Bay Area[J]. Transportation Research Part B: Methodological, 2002, 36(7): 593-616. http://www.sciencedirect.com/science/article/pii/S0191261501000200
    [15]
    PASHAM M, HICKMAN M D, PRATO C G. Modeling mode choice of air passengers' ground access to Brisbane airport[J]. Transportation Research Record, 2020, 2674 (11): 1-12.
    [16]
    GUNAY G, GOKASAR I. Market segmentation analysis for airport access mode choice modeling with mixed Logit[J]. Journal of Air Transport Management, 2021, 91: 102001. http://www.sciencedirect.com/science/article/pii/S0969699720305834
    [17]
    李林波, 郭晓凡, 傅佳楠, 等. 基于云模型的城市轨道交通乘客满意度评价[J]. 同济大学学报(自然科学版), 2019, 47 (3): 378-385.

    LI L B, GUO X F, FU J N, et al. Evaluation approach of passenger satisfaction for urban rail transit based on cloud model[J]. Journal of Tongji University (Natural Science), 2019, 47 (3): 378-385. (in Chinese)
    [18]
    李磊, 张曙阳, 李彤. 基于嵌套Logit模型的竞争性选址问题研究[J]. 系统工程学报, 2021, 36 (4): 524-538.

    LI L, ZHANG S Y, LI T. A new competitive facility location model based on nested Logit model[J]. Journal of Systems Engineering, 2021, 36 (4): 524-538. (in Chinese)
    [19]
    VACCAA, PRATO C G, MELONI I. Should I stay or should I go? Investigating route switching behavior from revealed preferences data[J]. Transportation, 2019, 46 (1): 75-93.
    [20]
    姚恩建, 张茜, 张锐. 公共交通票价对通勤走廊出行结构的影响[J]. 交通运输工程学报, 2017, 17 (6): 104-114.

    YAO E J, ZHANG Q, ZHANG R. Impact of public transport fare on travel mode structure of commuter corridor[J]. Journal of Traffic and Transportation Engineering, 2017, 17(6): 104-114. (in Chinese)
    [21]
    孙林祥. 地铁运行发车间隔和旅行速度指标下降的分析[J]. 都市快轨交通, 2007 (2): 6-9.

    SUN X L. Analyses for the indices decline of departure intervals and travel speeds in metro operation[J]. Urban Rapid Rail Transit, 2007 (2): 6-9. (in Chinese)
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