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多路段元胞自动机交通流模型

梁经韵 张莉莉 栾悉道 郭金林 老松杨 谢毓湘

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多路段元胞自动机交通流模型

梁经韵, 张莉莉, 栾悉道, 郭金林, 老松杨, 谢毓湘

Multi-section cellular automata model of traffic flow

Liang Jing-Yun, Zhang Li-Li, Luan Xi-Dao, Guo Jin-Lin, Lao Song-Yang, Xie Yu-Xiang
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  • 在经典单路段元胞自动机交通流模型的基础上,将多个路段视为一个道路系统,提出并研究了多路段条件下的交通流问题.针对多路段道路的特点,通过引入车辆流入规则、路口随机慢化规则和路口车辆流入规则,控制车辆从上一路段流入下一路段.首先提出了汽车池的概念,来控制每一路口车辆的流入;然后通过路口随机慢化,来模拟路口对交通的影响;最后,当车辆离开时,依直行率进入下一路段,实现车流的继续流动.同时,通过数值模拟,仿真了不同条件下的交通情况,对重要参数进行了研究.结果表明,出现了混合流这一新的现象,拥堵地段与非拥堵地段间存在明显的界限.拥堵往往最先从路口开始,然后蔓延到整个路段.多路段道路还存在临界突变的特性.随着车辆流入概率的增大,路口对平均速度和车流密度的影响愈加明显.当流入概率超过一定阈值时,车辆缓慢地增加也会引起整体道路通行能力的迅速下降.
    It is more common for drivers to pass through multiple sections to reach destinations instead of single road section. Howerver, most of researches concentrate on improving the effect in an independent section. Based on traditional cellular automata traffic model, a multi-section model is proposed by regarding serverl road sections as a traffic system. In this model, different sections of the road might have different lengths, numbers of lanes or maximal speeds. And vehicles travel from one section to another. The main difficulty lies in dealing with the relationships among the traffic flows of different sections. Besides basic rules in NaSch model, the vehicle inflow rule, crossroad randomization brake rule and crossroad inflow rule is added in this paper to enable vehicles to flow between sections. At the beginning of section, to avoid conflicting at crossroads under open boundary condition, the concept of car pool is introduced when new vehicles enter into sections. Before arriving at the end of section, crossroad randomization brake is used to simulate the influences of crossroads. Speed decreases in probability until lower than a maximal crossroad speed. When leaving the section, vehicles go to the next section with a straight ratio. Also, new vehicles may enter according to traffic condition. Therefore, cellular automata of different sections can be connected in series.Finally, numerical simulation is demonstrated to study the influences of important parameters, including traffic inflow probability, maximal crossroad speed and crossroad randomization brake probability. Compared with traditional models, this model focuses on connecting sections. And improvements of basic models can be implanted easily, thereby increasing the accuracy of the whole model in the future. The experimental result are as follows. 1) According to space-time graphs of different inflow probabilities, there is a new kind of traffic flow called mixed flow. Traffic congestion often starts from crossroads, and spreads to the whole section. And traffic jams in previous section might relieve traffic pressure in latter section. 2) With the increase of traffic inflow probability, crossroads tends to have a greater influence on average speed as well as average traffic density. What is more, the moderate increase of vehicle numbers could cause the road capacity to drop rapidly if it exceeds the threshold value.
      通信作者: 栾悉道, xidaoluan@ccsu.cn
    • 基金项目: 国家自然科学基金(批准号:61571453)、湖南省自然科学基金(批准号:14JJ3010)和湖南省教育厅重点项目(批准号:15A020)资助的课题.
      Corresponding author: Luan Xi-Dao, xidaoluan@ccsu.cn
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 61571453), the Natural Science Foundation of Hunan Province, China (Grant No. 14JJ3010), and the Research Foundation of Education Bureau of Hunan Province, China(Grant No. 15A020).
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    Tan H L, Liu M R, Kong L J 2002 Acta Phys. Sin. 51 2713 (in Chinese)[谭惠丽, 刘慕仁, 孔令江 2002 51 2713]

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    Peng L, Tian H L, Kong L J, Liu M R 2003 Acta Phys. Sin. 52 3007 (in Chinese)[彭麟, 谭惠丽, 孔令江, 刘慕仁 2003 52 3007]

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    Kerner B S, Rehborn H 1996 Phy. Rev. E 53 4275

  • [1]

    Hua X D, Wang W, Wang H 2016 Acta Phys. Sin. 65 084503 (in Chinese)[华雪东, 王炜, 王昊 2016 65 084503]

    [2]

    Wen J, Tian H H, Kang S J, Xue Y 2010 Acta Phys. Sin. 59 7693 (in Chinese)[温坚, 田欢欢, 康三军, 薛郁 2010 59 7693]

    [3]

    Nagatani T 2015 Physica A 419 1

    [4]

    Gao Y, Liu Y, Hu H, Ge Y 2016 J. Adv. Transport. 50 1470

    [5]

    Tang T Q, Shi W F, Yang X B, Wang Y P, Lu G Q 2013 Physica A 392 6300

    [6]

    Qian Y S, Feng X, Zeng J W 2017 Physica A 479 509

    [7]

    Hua X D, Wang W, Wang H 2011 Acta Phys. Sin. 60 084502 (in Chinese)[华雪东, 王炜, 王昊 2011 60 084502]

    [8]

    Jing M, Deng W, Wang H, Ji Y J 2012 Acta Phys. Sin. 61 244502 (in Chinese) [敬明, 邓卫, 王昊, 季彦婕 2012 61 244502]

    [9]

    Zhang B, Zhao H Y 2016 J. Kunming Univ. Sci. Technol. (Natural Science Edition) 4 45 (in Chinese) [张博,赵慧英 2016 昆明理工大学学报自然科学版 4 45]

    [10]

    Tang T Q, He J, Yang S C, Shang H Y 2014 Physica A 413 583

    [11]

    Tang T Q, Lou C, Wu Y H, Huang H J, Yang X B 2014 J. Adv. Transport. 48 304

    [12]

    Lakouari N, Bentaleb K, Ez-Zahraouy H, Benyoussef A 2015 Physica A 439 132

    [13]

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

    [14]

    Fukui M, Ishibashi Y 1996 J. Phys. Soc. Jpn. 65 1868

    [15]

    Wang L, Wang B H, Xu B M, Hu B B 2000 Acta Phys. Sin. 49 1926 (in Chinese)[王雷, 汪秉宏, 许伯铭, 胡斑比 2000 49 1926]

    [16]

    Lei L, Xue Y, Dai S Q 2003 Acta Phys. Sin. 52 2121 (in Chinese)[雷丽, 薛郁, 戴世强 2003 52 2121]

    [17]

    Peng L J, Kang R 2009 Acta Phys. Sin. 58 830 (in Chinese)[彭莉娟, 康瑞 2009 58 830]

    [18]

    Zhang N X, Zhu H B, Lin H, Huang M Y 2015 Acta Phys. Sin. 64 024501 (in Chinese)[张柠溪, 祝会兵, 林亨, 黄梦圆 2015 64 024501]

    [19]

    Lrraga M E, Luis A I 2014 Chin. Phys. B 23 057101

    [20]

    Chen Q, Wang Y 2016 J. Adv. Transport. 50 949

    [21]

    Zhao H T, Yang S, Chen X X 2016 Physica A 462 1301

    [22]

    Qiu X P, Ma L N, Zhou X X, Yang D 2016 J. Transport.Syst. Engineer. Inform. Technol. 16 101 (in Chinese) [邱小平, 马丽娜, 周小霞, 杨达2016 交通运输系统工程与信息16 101]

    [23]

    Qiu X P, Yu D, Sun R X, Yang D 2016 Appl. Res. Comput.33 2611 (in Chinese) [邱小平, 于丹, 孙若晓, 杨达2016 计算机应用研究33 2611]

    [24]

    Bouadi M, Jetto K, Benyoussef A, Kenz A E 2017 Physica A 469 1

    [25]

    Zhang X Q, Wang Y, Hu Q H 2014 Acta Phys. Sin. 63 010508 (in Chinese) [张兴强, 汪滢, 胡庆华 2014 63 010508]

    [26]

    Zhao H T, Mao H Y 2013 Acta Phys. Sin. 62 060501 (in Chinese) [赵韩涛, 毛宏燕 2013 62 060501]

    [27]

    Dong L Y, Xue Y, Dai S Q 2002 Appl. Math. Mech. 23 331 (in Chinese) [董力耘, 薛郁, 戴世强 2002 应用数学和力学 23 331]

    [28]

    Ge H X, Meng X P, Zhu H B, Li Z P 2014 Physica A 408 28

    [29]

    Gipps P G 1981 Transportation Research Part B Methodological 15 105

    [30]

    Tan H L, Liu M R, Kong L J 2002 Acta Phys. Sin. 51 2713 (in Chinese)[谭惠丽, 刘慕仁, 孔令江 2002 51 2713]

    [31]

    Peng L, Tian H L, Kong L J, Liu M R 2003 Acta Phys. Sin. 52 3007 (in Chinese)[彭麟, 谭惠丽, 孔令江, 刘慕仁 2003 52 3007]

    [32]

    Kerner B S, Rehborn H 1996 Phy. Rev. E 53 4275

  • [1] 张兴强, 汪滢, 胡庆华. 交叉口混合交通流元胞自动机模型及仿真研究.  , 2014, 63(1): 010508. doi: 10.7498/aps.63.010508
    [2] 赵韩涛, 毛宏燕. 有应急车辆影响的多车道交通流元胞自动机模型.  , 2013, 62(6): 060501. doi: 10.7498/aps.62.060501
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    [14] 陈时东, 朱留华, 孔令江, 刘慕仁. 优先随机慢化及预测间距对交通流的影响.  , 2007, 56(5): 2517-2522. doi: 10.7498/aps.56.2517
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    [17] 花 伟, 林柏梁. 考虑行车状态的一维元胞自动机交通流模型.  , 2005, 54(6): 2595-2599. doi: 10.7498/aps.54.2595
    [18] 牟勇飚, 钟诚文. 基于安全驾驶的元胞自动机交通流模型.  , 2005, 54(12): 5597-5601. doi: 10.7498/aps.54.5597
    [19] 薛郁, 董力耘, 戴世强. 一种改进的一维元胞自动机交通流模型及减速概率的影响.  , 2001, 50(3): 445-449. doi: 10.7498/aps.50.445
    [20] 吕晓阳, 孔令江, 刘慕仁. 一维元胞自动机随机交通流模型的宏观方程分析.  , 2001, 50(7): 1255-1259. doi: 10.7498/aps.50.1255
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  • 被引次数: 0
出版历程
  • 收稿日期:  2017-05-27
  • 修回日期:  2017-08-18
  • 刊出日期:  2017-10-05

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