搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

通道中行人-机动车相互作用机理的建模和模拟

张稷 韦艳芳 董力耘

引用本文:
Citation:

通道中行人-机动车相互作用机理的建模和模拟

张稷, 韦艳芳, 董力耘

Modeling and simulation on interaction between pedestrians and a vehicle in a channel

Zhang Ji, Wei Yan-Fang, Dong Li-Yun
PDF
导出引用
  • 本文研究了通道中行人与车辆同向或反向运动时的人车相互作用.车辆运动的描述采用细化的确定性元胞自动机模型,而行人流则采用考虑背景场的格子气模型.车辆及其影响区被视为一种可移动的障碍物,形成动态变化的背景场,可以更好地反映人车之间的相互作用.通过数值模拟得到典型参数下的行人流基本图以及平均车速随行人密度的变化曲线.人车反向时行人流基本图中存在两个临界密度,其间的行人流量-密度曲线呈线性分布,曲线斜率k主要依赖于车辆宽度和行人预判时间,而平均车速近似为k,即反向车辆形成的移动瓶颈和行人拥堵向上游传播的速度是一致的.文中进一步考察了行人预判时间、车辆宽度及限速对人车混合交通流的影响.人车同向时,这三个参数的影响都不明显.人车反向时,当车辆宽度较小,即使在很高密度下,车辆仍可以前行,而更大的行人预判时间也有助于车辆的运动.
    The mixed traffic flow composed of pedestrians and vehicles shows distinct features that a single kind of traffic flow does not have. In this paper, the motion of a vehicle is described by the finer deterministic Nagel-Schreckenberg model, while the motion of pedestrians is mimicked by the lattice gas model with taking the floor field into account. Then the interaction between a certain vehicle and pedestrians in a narrow channel is investigated in two cases, i.e., pedestrians move in the same as or opposite to the direction of vehicle. The direction of the pedestrian movement is determined by the floor field, and the vehicle (and its influential area), regarded as a movable obstacle, and thus causing the floor field to change. Because of the timely change of vehicle speed and the size of impact area, the floor field must be calculated at each time step. Through numerical simulation, the fundamental diagram for pedestrian flow under the typical parameters is obtained together with the average speed of the vehicle as a function of pedestrian density. It is found that there are two critical densities, i.e., ρ1 and ρ2. When ρ1ρρ2, the fundamental diagrams in the two cases are significantly different. This is due to the reverse movement of pedestrian and vehicle, the congestion ahead of the vehicle makes the average speed of pedestrians significantly lowered. In this case, the flux of pedestrians is a linear function of pedestrian density, and its slope indicates the speed at which pedestrian congestion propagates upstream. It can also represent the speed of the moving bottleneck formed by the vehicle. The slope mainly depends on the width of the vehicle and the anticipation time of pedestrians. When ρ < ρ1 and ρ > ρ2, there is no obvious difference between the two cases. We further investigate the effect of three parameters, i.e., the anticipation time of pedestrians, the width and the speed limit of the vehicle. When pedestrians have the same direction as the vehicle, these parameters only have negligible effects. However, in the case that pedestrians move oppositely to the vehicle, the width of the vehicle influences the mixed traffic significantly. When the width of the vehicle is small, even in rather high pedestrian density, the vehicle can move forward. In addition, larger anticipation time of pedestrians is helpful in improving the speed of vehicle, while the effect of the speed limit of vehicle is relatively small. The spatial distribution of pedestrians and the vehicle and the short time average speed of the vehicle are also provided to reveal more information about both pedestrians and the vehicle.
    [1]

    Chowdhury D, Santen L, Schadschneider A 2000 Phys. Rep. 329 199

    [2]

    Maerivoet S, Moor B D 2005 Phys. Rep. 419 1

    [3]

    Schadschneider A, Klingsch W, Klüpfel H, Kretz T, Rogsch C, Seyfried A 2009 Encyclopedia of Complexity and Systems Science (New York: Springer) pp3142-3176

    [4]

    Helbing D, Johansson A 2009 Encyclopedia of Complexity and Systems Science (New York: Springer) pp6476-6495

    [5]

    Nagel K, Schreckenberg M 1992 J. Phys. I 2 2221

    [6]

    Knospe W, Santen L, Schadschneider A, Schreckenberg M 2000 J. Phys. A 33 L477

    [7]

    Kerner B S, Klenov S L, Wolf D E 2002 J. Phys. A 35 9971

    [8]

    Burstedde C, Klauck K, Schadschneider A, Zittartz J 2001 Physica A 295 507

    [9]

    Kirchner A, Schadschneider A 2002 Physica A 312 260

    [10]

    Muramatsu M, Irie T, Nagatani T 1999 Physica A 267 487

    [11]

    Varas A, Cornejo M D, Mainemer D, Toledo B, Valdivia J A 2007 Physica A 382 631

    [12]

    Huang H J, Guo R Y 2008 Phys. Rev. E 78 021131

    [13]

    Helbing D, Jiang R, Treiber M 2005 Phys. Rev. E 72 046130

    [14]

    Zheng Y N, Chase T, Elefteriadou L, Schroeder B, Sisiopiku V P 2015 Simul. Modell. Pract. Theory 59 89

    [15]

    Li X, Sun J Q 2015 Physica A 438 251

    [16]

    Gorrini A, VizzarI G, Bandini S 2016 Pedestrian and Evacuation Dynamics Hefei, China, October 17-21, 2016 p42

    [17]

    Chen P, Wu C, Zhu S 2016 Saf. Sci. 82 68

    [18]

    Lu L L, Ren G, Wang W, Chan C Y, Wang J 2016 Accid. Anal. Prev. 95 425

    [19]

    Khallouk A, Echab H, Ez-Zahraouy H, Lakouari N 2018 Phys. Lett. A 382 566

    [20]

    Jiang R, Wu Q S 2006 Physica A 364 457

    [21]

    Jiang R, Wu Q S 2006 Physica A 368 239

  • [1]

    Chowdhury D, Santen L, Schadschneider A 2000 Phys. Rep. 329 199

    [2]

    Maerivoet S, Moor B D 2005 Phys. Rep. 419 1

    [3]

    Schadschneider A, Klingsch W, Klüpfel H, Kretz T, Rogsch C, Seyfried A 2009 Encyclopedia of Complexity and Systems Science (New York: Springer) pp3142-3176

    [4]

    Helbing D, Johansson A 2009 Encyclopedia of Complexity and Systems Science (New York: Springer) pp6476-6495

    [5]

    Nagel K, Schreckenberg M 1992 J. Phys. I 2 2221

    [6]

    Knospe W, Santen L, Schadschneider A, Schreckenberg M 2000 J. Phys. A 33 L477

    [7]

    Kerner B S, Klenov S L, Wolf D E 2002 J. Phys. A 35 9971

    [8]

    Burstedde C, Klauck K, Schadschneider A, Zittartz J 2001 Physica A 295 507

    [9]

    Kirchner A, Schadschneider A 2002 Physica A 312 260

    [10]

    Muramatsu M, Irie T, Nagatani T 1999 Physica A 267 487

    [11]

    Varas A, Cornejo M D, Mainemer D, Toledo B, Valdivia J A 2007 Physica A 382 631

    [12]

    Huang H J, Guo R Y 2008 Phys. Rev. E 78 021131

    [13]

    Helbing D, Jiang R, Treiber M 2005 Phys. Rev. E 72 046130

    [14]

    Zheng Y N, Chase T, Elefteriadou L, Schroeder B, Sisiopiku V P 2015 Simul. Modell. Pract. Theory 59 89

    [15]

    Li X, Sun J Q 2015 Physica A 438 251

    [16]

    Gorrini A, VizzarI G, Bandini S 2016 Pedestrian and Evacuation Dynamics Hefei, China, October 17-21, 2016 p42

    [17]

    Chen P, Wu C, Zhu S 2016 Saf. Sci. 82 68

    [18]

    Lu L L, Ren G, Wang W, Chan C Y, Wang J 2016 Accid. Anal. Prev. 95 425

    [19]

    Khallouk A, Echab H, Ez-Zahraouy H, Lakouari N 2018 Phys. Lett. A 382 566

    [20]

    Jiang R, Wu Q S 2006 Physica A 364 457

    [21]

    Jiang R, Wu Q S 2006 Physica A 368 239

  • [1] 陶亦舟, 韦艳芳, 高庆飞, 董力耘. 基于精细微观交通流模型的信号交叉口人-车相互干扰研究. 物理学报, 2019, 68(24): 240505. doi: 10.7498/aps.68.20191306
    [2] 梁经韵, 张莉莉, 栾悉道, 郭金林, 老松杨, 谢毓湘. 多路段元胞自动机交通流模型. 物理学报, 2017, 66(19): 194501. doi: 10.7498/aps.66.194501
    [3] 杨晓芳, 茅威, 付强. 基于动态地场和元胞自动机的自行车流建模. 物理学报, 2013, 62(24): 240511. doi: 10.7498/aps.62.240511
    [4] 永贵, 黄海军, 许岩. 菱形网格的行人疏散元胞自动机模型. 物理学报, 2013, 62(1): 010506. doi: 10.7498/aps.62.010506
    [5] 孙泽, 贾斌, 李新刚. 基于元胞自动机的行人和机动车相互干扰机理研究. 物理学报, 2012, 61(10): 100508. doi: 10.7498/aps.61.100508
    [6] 陈然, 李翔, 董力耘. 地铁站内交织行人流的简化模型和数值模拟. 物理学报, 2012, 61(14): 144502. doi: 10.7498/aps.61.144502
    [7] 郑亮, 马寿峰, 贾宁. 基于驾驶员行为的元胞自动机模型研究. 物理学报, 2010, 59(7): 4490-4498. doi: 10.7498/aps.59.4490
    [8] 盛鹏, 赵树龙, 王俊峰, 左航. 基于元胞自动机模型的道路突发瓶颈现象研究. 物理学报, 2010, 59(6): 3831-3840. doi: 10.7498/aps.59.3831
    [9] 温坚, 田欢欢, 康三军, 薛郁. 混合交通流元胞自动机FI模型的能耗研究. 物理学报, 2010, 59(11): 7693-7700. doi: 10.7498/aps.59.7693
    [10] 田欢欢, 薛郁, 康三军, 梁玉娟. 元胞自动机混合交通流模型的能耗研究. 物理学报, 2009, 58(7): 4506-4513. doi: 10.7498/aps.58.4506
    [11] 彭莉娟, 康瑞. 考虑驾驶员特性的一维元胞自动机交通流模型. 物理学报, 2009, 58(2): 830-835. doi: 10.7498/aps.58.830
    [12] 康瑞, 彭莉娟, 杨凯. 考虑驾驶方式改变的一维元胞自动机交通流模型. 物理学报, 2009, 58(7): 4514-4522. doi: 10.7498/aps.58.4514
    [13] 单博炜, 林鑫, 魏雷, 黄卫东. 纯物质枝晶凝固的元胞自动机模型. 物理学报, 2009, 58(2): 1132-1138. doi: 10.7498/aps.58.1132
    [14] 梅超群, 黄海军, 唐铁桥. 城市快速路系统的元胞自动机模型与分析. 物理学报, 2009, 58(5): 3014-3021. doi: 10.7498/aps.58.3014
    [15] 李庆定, 董力耘, 戴世强. 公交车停靠诱发交通瓶颈的元胞自动机模拟. 物理学报, 2009, 58(11): 7584-7590. doi: 10.7498/aps.58.7584
    [16] 梅超群, 黄海军, 唐铁桥. 高速公路入匝控制的一个元胞自动机模型. 物理学报, 2008, 57(8): 4786-4793. doi: 10.7498/aps.57.4786
    [17] 郭四玲, 韦艳芳, 薛 郁. 元胞自动机交通流模型的相变特性研究. 物理学报, 2006, 55(7): 3336-3342. doi: 10.7498/aps.55.3336
    [18] 吴可非, 孔令江, 刘慕仁. 双车道元胞自动机NS和WWH交通流混合模型的研究. 物理学报, 2006, 55(12): 6275-6280. doi: 10.7498/aps.55.6275
    [19] 花 伟, 林柏梁. 考虑行车状态的一维元胞自动机交通流模型. 物理学报, 2005, 54(6): 2595-2599. doi: 10.7498/aps.54.2595
    [20] 牟勇飚, 钟诚文. 基于安全驾驶的元胞自动机交通流模型. 物理学报, 2005, 54(12): 5597-5601. doi: 10.7498/aps.54.5597
计量
  • 文章访问数:  4159
  • PDF下载量:  14
  • 被引次数: 0
出版历程
  • 收稿日期:  2018-08-07
  • 修回日期:  2018-10-08
  • 刊出日期:  2019-12-20

/

返回文章
返回