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轨道交通与常规公交交互胁迫关系验证分析

焦柳丹 罗凤莲 吴雅 张羽

焦柳丹, 罗凤莲, 吴雅, 张羽. 轨道交通与常规公交交互胁迫关系验证分析[J]. 交通信息与安全, 2021, 39(6): 126-134. doi: 10.3963/j.jssn.1674-4861.2021.06.015
引用本文: 焦柳丹, 罗凤莲, 吴雅, 张羽. 轨道交通与常规公交交互胁迫关系验证分析[J]. 交通信息与安全, 2021, 39(6): 126-134. doi: 10.3963/j.jssn.1674-4861.2021.06.015
JIAO Liudan, LUO Fenglian, WU Ya, ZHANG Yu. A Validation Study of Interactive Stress Relationship Between Urban Rail and Regular Bus Transportation Systems[J]. Journal of Transport Information and Safety, 2021, 39(6): 126-134. doi: 10.3963/j.jssn.1674-4861.2021.06.015
Citation: JIAO Liudan, LUO Fenglian, WU Ya, ZHANG Yu. A Validation Study of Interactive Stress Relationship Between Urban Rail and Regular Bus Transportation Systems[J]. Journal of Transport Information and Safety, 2021, 39(6): 126-134. doi: 10.3963/j.jssn.1674-4861.2021.06.015

轨道交通与常规公交交互胁迫关系验证分析

doi: 10.3963/j.jssn.1674-4861.2021.06.015
基金项目: 

国家自然科学基金青年项目 71901043

国家自然科学基金青年项目 72004187

详细信息
    通讯作者:

    焦柳丹(1989—),博士,副教授.研究方向:城市轨道交通.E-mail:jld06171@126.com

  • 中图分类号: U491.17

A Validation Study of Interactive Stress Relationship Between Urban Rail and Regular Bus Transportation Systems

  • 摘要: 为了揭示城市轨道交通与常规公交之间的交互胁迫的演化特点, 通过借鉴城市化水平与生态环境之间的交互胁迫理论, 构建轨道交通与常规公交交互胁迫模型, 以我国2009年之前开通运营城市轨道交通的10个城市为样本, 基于轨道交通与常规公交之间的客运总量、线路长度及运营车辆3个维度的历史演化规律分析基础上, 验证轨道交通与常规公交之间交互胁迫关系, 进而对不同城市轨道交通与常规公交演化特点进行分类分析。研究结果表明: ①城市轨道交通与常规公交之间存在交互胁迫关系, 演变轨迹符合双指数曲线。②不同城市的轨道交通与常规公交在3个维度的演变轨迹上存在不均衡性, 客运总量的拐点出现早于运营线路长度和运营车辆数。③根据拐点的出现情况, 将10个城市分为5类, 其中, 重庆的轨道交通与常规公交在客运总量、线路长度及运营车辆3个维度的拐点出现均较晚, 表明重庆的公交发展模式较为协调, 常规公交在轨道交通的胁迫下仍然保持了一定的竞争力。

     

  • 图  1  城市常规公交与轨道交通交互关系双指数曲线

    Figure  1.  Double exponential curve for interactive stress effect between urban bus and rail transport system

    表  1  2009年及2019年城市公共交通发展状况

    Table  1.   Development of urban public transportation of 2009 and 2019

    城市 公共汽(电)车 轨道交通
    客运总量/(万人·次) 线路长度/km 运营车辆/辆 客运总量/(万人·次) 线路长度/km 运营车辆/辆
    2009年 2019年 2009年 2019年 2009年 2019年 2009年 2019年 2009年 2019年 2009年 2019年
    北京 516 517 313 366 18 270 27 632 21 716 23 010 142 268 396 238 228 699 2 014 6 449
    长春 63 897 75 194 899 6 405 4 212 5 087 2 954 23 204 39 118 140 895
    重庆 150 056 257 088 3 896 29 745 8 077 14 276 4 181 104 187 19 328 136 2 130
    大连 96 151 92 212 941 5 492 4 811 5 683 6 885 21 967 87 181 143 628
    广州 242 200 224 090 16 604 24 368 10 715 15 388 67 520 330 994 147 523 722 2 854
    南京 104 178 91 518 3 119 12 018 6 081 8 700 11 353 115 730 22 394 120 1 736
    上海 270 600 208 500 23 033 24 780 16 272 17 899 131 837 388 445 355 705 1 833 5 911
    深圳 213 603 158 973 2 270 21 606 11 928 17 110 13 823 203 216 25 316 162 2 598
    天津 116 425 111 058 11 832 25 526 7 897 12 746 5 271 54 578 71 231 228 1 220
    武汉 165 610 142 954 5 463 9 724 7 241 9 631 1 317 122 373 10 335 48 2 416
    下载: 导出CSV

    表  2  城市常规公交与轨道交通客流量交互胁迫双指数函数方程

    Table  2.   Double exponential function for interactive stress effect on passenger flows of urban bus and rail transport system

    城市 交互胁迫函数关系式 m n b a p R2
    北京 z=0.993 3-0.171 6(10(y-0.824 6)/0.613 5-0.749 8)2 0.993 3 0.171 6 0.824 6 0.613 5 0.749 8 0.927 2
    长春 z=0.026 4-5.830 2 (10(y-0.794 2)/0.278 9-0.630 9)2 0.026 4 5.830 2 0.794 2 0.278 9 0.630 9 0.210 9
    重庆 z=0.457 6-0.975 8(10(y-0.584 3)/0.289 0-1.427 1)2 0.457 6 0.975 8 0.584 3 0.289 0 1.427 1 0.944 4
    大连 z=0.174 0-0.909 0(10(y-0.663 7)/0.433 2-0.213 6)2 0.174 0 0.909 0 0.663 7 0.433 2 0.213 6 0.621 7
    广州 z=0.423 5-0.016 7(10(y-0.679 3)/0.337 9-1.970 4)2 0.423 5 0.016 7 0.679 3 0.337 9 1.970 4 0.767 3
    南京 z=0.104 5-0.032 4(10(y-0.476 3)/0.375 9-0.477 2)2 0.104 5 0.032 4 0.476 3 0.375 9 0.477 2 0.846 1
    上海 z=0.479 3-0.021 4 (10(y-0.751 3)/0.492 2-0.523 9)2 0.479 3 0.021 4 0.751 3 0.492 2 0.523 9 0.950 0
    深圳 z=0.357 7-0.232 3(10(y-0.741 9)/0.540 7-0.231 6)2 0.357 7 0.232 3 0.741 9 0.540 7 0.231 6 0.853 1
    天津 z=0.175 6-1.565 0(10(y-0.633 4)/0.187 0-1.458 0)2 0.175 6 1.565 0 0.633 4 0.187 0 1.458 0 0.803 7
    武汉 z=0.175 6-3.070 9(10(y-0.856 7)/0.156 7-1.040 8)2 0.175 6 3.070 9 0.856 7 0.156 7 1.040 8 0.577 9
    下载: 导出CSV

    表  3  城市常规公交与轨道交通运营线路长度交互胁迫双指数函数方程

    Table  3.   Double exponential function for interactive stress effect on the length of operating lines of urban bus and rail transport system

    城市 交互胁迫函数关系式 m n b a p R2
    北京 z=1.349 0-0.511 5(10(y-1.114 7)/1.234 4-1.513 3)2 1.349 0 0.511 5 1.114 7 1.234 4 1.513 3 0.947 1
    长春 z=1.116 0-1.055 7(10(y-0.647 6)/2.596 7-1.104 1)2 1.116 0 1.055 7 0.647 6 2.596 7 1.104 1 0.592 7
    重庆 z=1.506 0-1.209 7(10(y-0.591 7)/1.513 3-1.211 9)2 1.506 0 1.209 7 0.591 7 1.513 3 1.211 9 0.827 2
    大连 z=0.689 2-0.891 0(10(y-0.768 0)/1.323 4-1.003 1)2 0.689 2 0.891 0 0.768 0 1.323 4 1.003 1 0.753 7
    广州 z=6.349 1-2.382 5(10(y-0.823 2)/14.205 2-1.585 1)2 6.349 1 2.382 5 0.823 2 14.205 2 1.585 1 0.600 1
    南京 z=0.387 3-0.781 2(10(y-0.789 0)/0.557 0-0.910 2)2 0.387 3 0.781 2 0.789 0 0.557 0 0.910 2 0.822 1
    上海 z=0.934 3-0.213 1 (10(y-1.317 0)/1.841 5-0.984 7)2 0.934 3 0.213 1 1.317 0 1.841 5 0.984 7 0.942 2
    深圳 z=0.745 9-1.641 3(10(y-0.738 9)/0.396 4-1.051 1)2 0.745 9 1.641 3 0.738 9 0.396 4 1.051 1 0.751 7
    天津 z=1.592 0-1.469 5(10(y-0.579 9)/1.187 1-1.192 8)2 1.592 0 1.469 5 0.579 9 1.187 1 1.192 8 0.906 3
    武汉 z=0.351 7-0.498 4(10(y-0.935 2)/0.679 1-0.782 7)2 0.351 7 0.498 4 0.935 2 0.679 1 0.782 7 0.824 5
    下载: 导出CSV

    表  4  城市常规公交与轨道交通运营车辆交互胁迫双指数函数方程

    Table  4.   Double exponential function for interactive stress effect on the number of operating vehicles of urban bus and rail transport system

    城市 交互胁迫函数关系式 m n b a p R2
    北京 z=0.887 8-4.965 2(10(y-0.981 9)/0.818 4-1.137 8)2 0.887 8 4.965 2 0.981 9 0.818 4 1.137 8 0.669 3
    长春 z=4.106 2-1.907 1(10(y-0.657 8)/11.448 1-1.468 7)2 4.016 2 1.907 1 0.657 8 11.448 1 1.468 7 0.502 2
    重庆 z=0.484 8-1.466 6(10(y-0.638 4)/0.400 3-1.067 4)2 0.484 8 1.466 6 0.638 4 0.400 3 1.067 4 0.884 3
    大连 z=0.084 6-0.768 1(10(y-0.762 3)/0.389 9-0.718 6)2 0.084 6 0.768 1 0.762 3 0.389 9 0.718 6 0.773 5
    广州 z=0.534 0-0.877 7(10(y-0.787 2)/0.579 5-0.877 0)2 0.534 0 0.877 7 0.787 2 0.579 5 0.877 0 0.980 6
    南京 z=0.225 5-1.254 5(10(y-0.654 3)/0.410 7-0.906 3)2 0.225 5 1.254 5 0.654 3 0.410 7 0.906 3 0.922 4
    上海 z=0.746 2-1.515 2(10(y-2.408 9)/0.341 9-0.364 2)2 0.746 2 1.515 2 2.408 9 0.341 9 0.364 2 0.563 9
    深圳 z=0.603 4-0.935 5(10(y-0.737 0)/0.512 4-0.864 5)2 0.603 4 0.935 5 0.737 0 0.512 4 0.864 5 0.914 1
    天津 z=0.432 1-2.724 1(10(y-0.602 0)/0.376 7-1.032 1)2 0.432 1 2.724 1 0.602 0 0.376 7 1.032 1 0.835 6
    武汉 z=0.258 4-0.694 1(10(y-0.785 1)/0.457 6-0.774 7)2 0.258 4 0.694 1 0.785 1 0.457 6 0.774 7 0.976 9
    下载: 导出CSV

    表  5  拐点分类情况

    Table  5.   Classification of inflection points

    分类情况 城市 拐点较早 拐点较晚 未有拐点
    北京 客运总量 运营车辆 线路长度
    南京 客运总量 运营车辆 线路长度
    天津 客运总量 运营车辆 线路长度
    大连 客运总量 线路长度、运营车辆
    广州 客运总量 线路长度、运营车辆
    上海 客运总量 线路长度、运营车辆
    武汉 客运总量 线路长度、运营车辆
    长春 客运总量 线路长度、运营车辆
    深圳 客运总量 线路长度 运营车辆
    重庆 客运总量、线路长度、运营车辆
    下载: 导出CSV
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  • 收稿日期:  2021-04-22
  • 网络出版日期:  2022-01-12

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