雨天过街行人流自组织行为特性及其仿真建模

杨海飞; 卢素情; 李昀轩; 陈娴; 王柳; 古乐

doi:10.3963/j.jssn.1674-4861.2024.02.014

雨天过街行人流自组织行为特性及其仿真建模

doi: 10.3963/j.jssn.1674-4861.2024.02.014

杨海飞^1,,
卢素情¹,
李昀轩^2, ,,
陈娴¹,
王柳¹,
古乐¹

1.
河海大学土木与交通学院南京 210024
2.
北京工业大学城市建设学部北京 100124

基金项目:

国家自然科学基金青年项目 71801080

详细信息

作者简介:
杨海飞（1984—），博士，副教授. 研究方向：交通行为建模、交通流理论. E-mail: yanghaifei@hhu.edu.cn

通讯作者:
李昀轩（1989—），博士，讲师. 研究方向：交通管理与控制. E-mail: liyunxuan@bjut.edu.cn

中图分类号: U491.2
计量
- 文章访问数: 111
- HTML全文浏览量: 80
- PDF下载量: 4
- 被引次数: 0
出版历程
- 收稿日期: 2023-10-06
- 网络出版日期: 2024-09-14

Characteristics and a Simulation Model of Self-organizing Behavior of Pedestrian Flow at Crosswalk under Rainy Condition

YANG Haifei^1
,,
LU Suqing¹,
LI Yunxuan^{2
, ,},
CHEN Xian¹,
WANG Liu¹,
GU Le¹

1.
College of Civil and Transportation Engineering, Hohai University, Nanjing 210024, China
2.
Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China

摘要

摘要: 为改善降雨环境下城市过街设施的交通安全与效率，研究了雨天行人流过街的自组织行为特性并对其进行仿真建模。结合现场采集的晴、雨天行人流过街轨迹数据，对比分析常见中、小雨天气下过街行人流的速度统计分布、避让位移偏量以及空间溢出幅度；在此基础上通过改进社会力模型建立雨天行人流过街运动模型；应用实测数据标定模型参数并进行仿真验证。特性分析结果显示：雨天行人流过街速度在0.5~1.25 m/s区间的占比较晴天增加了58.80%，而在1.25~2.0 m/s区间占比降低了24.37%，表明其分布向低速范围显著偏移（p < 0.001），同时由于未撑伞或溢出行人的紧迫心理，仍有8.05%的行人以2.0~2.5 m/s的较高步速过街；雨天对向行人避让的位移偏量较晴天平均增幅达46.80%，其整体趋势显著增大（p < 0.001）；雨天行人流空间溢出的临界过街等待人数和人流量较晴天分别下降7人与3人/分钟，溢出幅度为5.07%~24.80%。仿真验证结果表明：所建立的行人流过街运动模型，其模拟的雨天行人过街轨迹精度与晴天达到同量级，其中晴天单向前行与对向避让轨迹均方根误差分别为0.245和0.483，而雨天则为0.329和0.702；模拟的过街速度统计分布与实测分布无显著差异（晴天p =0.620，雨天p =0.649），且能够还原未撑伞或溢出行人的高速过街行为；模拟典型场景下雨天行人流溢出幅度与实测值的绝对误差为2.08%，而晴天均未发生溢出现象，与实测结果相符。
- 交通安全 /
- 过街行人流 /
- 社会力模型 /
- 仿真 /
- 降雨
Abstract: To enhance traffic safety and efficiency of urban street-crossing facilities during rainfall, the self-organizing behavior of pedestrian flows crossing streets in the rain is investigated. A corresponding simulation model is also developed. More specifically, the crossing trajectory data of pedestrian flows in both sunny and rainy conditions are collected through on-site observation. Next, a comparative analysis is employed to determine pedestrian flow's distribution of speed, displacement offset for avoidance, and magnitude of spatial overflow with moderate and light rainfalls. Based on these findings, a pedestrian flow movement model for rainy conditions is proposed by modifying the social force model. The model parameters are calibrated and simulation verification is performed using the collected data. The results of the characteristic analysis reveal that: Due to rainfalls, the proportion of pedestrian's speeds ranging between 0.5 and 1.25 m/s increases by 58.80%; while it decreases by 24.37% in the range of 1.25 to 2.0 m/s. This indicates a significant shift of speed towards a lower range (p < 0.001). However, there are 8.05% of the pedestrians, without umbrellas or in an overflow situation, crossing streets at higher speeds in the range of 2.0 to 2.5 m/s. A notable increase (46.8%) in displacement offset is observed when pedestrians encounter each other in rainy conditions, a change that is statistically significant (p < 0.001). The thresholds of the number and flow rate of waiting pedestrians triggering overflow situations decreases by 7 people and 3 people/min, respectively, and the corresponding overflow magnitude ranges from 5.07% to 24.80%. The simulation results indicate that: The proposed model exhibits an accuracy in rainy condition that is comparable to that in sunny conditions. Specifically, the root mean square errors of forward movement in one direction and avoidance movement in opposite directions for sunny conditions are 0.245 and 0.483 respectively, while those for rainy conditions are 0.329 and 0.702 respectively. No significant difference between the simulated speed distribution and the measured one is observed (p =0.620 for sunny conditions, p =0.649 for rainy conditions). The model is able to reproduce the urgent behavior of crossing streets of pedestrians without umbrellas or in an overflow situation. The absolute error of overflow magnitude of pedestrian flows between the simulated and measured situations is 2.08% in typical rainy conditions, while no overflow situations are observed in sunny conditions, which aligns with the empirical findings.
- traffic safety /
- crossing-street pedestrian flow /
- social force model /
- simulation /
- rainfall

HTML全文

图 1 行人过街数据提取与处理流程

Figure 1. Data extraction and processing for pedestrian crossing

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图 2 晴、雨天视频拍摄画面

Figure 2. Video shooting scenes under sunny and rainy conditions

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图 3 晴、雨天环境下过街行人流速度频率分布

Figure 3. Frequency distribution of pedestrian crossing speed under sunny and rainy conditions

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图 4 晴、雨天单、双向过街行人流速度空间分布

Figure 4. Spatial distribution of speed for one-way and two-way crossing under sunny and rainy conditions

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图 5 晴、雨天行人避让位移图

Figure 5. Pedestrian avoidance displacement under sunny and rainy conditions

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图 6 晴、雨天过街行人流轨迹分布图

Figure 6. Trajectories of pedestrian under sunny and rainy conditions

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图 7 晴、雨天条件下典型行人过街轨迹对比

Figure 7. Comparison of typical pedestrian crossing trajectories under sunny and rainy conditionsunder sunny and rainy conditions

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图 8 晴、雨天实际与仿真过街行人流速度分布对比

Figure 8. Comparison of actual and simulated pedestrian crossing speed distribution under sunny and rainy conditions

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图 9 晴、雨天过街行人流仿真与实测轨迹分布对比

Figure 9. Comparison of simulated and actual trajectories of pedestrian under sunny and rainy conditions

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图 10 晴、雨天过街行人流空间覆盖面积对比

Figure 10. Comparison of the covered area of pedestrian crossing under sunny and rainy conditions

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表 1 调查地点交通环境

Table 1. Traffic environment of the survey site

交叉口名称	人行横道长度/m	人行横道宽度/m	降雨量/mm	调查时间段	高峰（平峰）时段人流量（/ 人/h）
交叉口名称	人行横道长度/m	人行横道宽度/m	降雨量/mm	调查时间段	雨	晴
江东北路交叉口1	29	6	6~9.9 10~15	12：30—14：30 14：30—18：30	532~588 （263~302）	562~608 （312~358）
江东北路交叉口2	21	6			559~602 （296~347）	623~673 （352~383）
黄河路与太湖路交叉口1	15	4			633~689 （423~462）	776~891 （492~553）
黄河路与太湖路交叉口2	12	4			579~623 （407~442）	706~732 （473~545）

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表 2 过街行人流速度统计分布情况

Table 2. Statistical distributions of pedestrian crossing speed 单位: m/s

天气	平均速度	最小速度	速度中位数	最大速度	标准差
晴天	1.52	0.66	1.36	2.79	0.40
雨天	1.43	0.61	1.27	2.28	0.31

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表 3 晴、雨天行人纵向偏移量统计结果

Table 3. Statistical results of longitudinal offset of pedestrians under sunny and rainy conditions 单位: m

天气	平均	中位数	最小值	最大值	标准差
晴天	0.47	0.47	0.35	0.56	0.12
雨天	0.69	0.68	0.62	0.78	0.15

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表 4 行人避让行为频率

Table 4. Pedestrian avoidance behavior frequency 单位：%

场景	晴天	雨天
江东北路交叉口1	19	26.4
江东北路交叉口2	18.8	23.8
黄河路与太湖路交叉口1	17.7	26.8
黄河路与太湖路交叉口2	20.5	25.6

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表 5 晴、雨天过街行人流溢出幅度统计结果

Table 5. Statistical results of overflow magnitude of crossing pedestrian flow under sunny and rainy days 单位: %

天气	平均	中位数	标准差	最小值	最大值
雨天	15.3	15.4	5.52	5.07	24.84
晴天	14.79	15.13	5.74	5.03	24.97

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表 6 行人溢出行为频率

Table 6. Frequency of pedestrian overflowing the crosswalk 单位: %

场景	晴天	雨天
江东北路交叉口1	14.3	25
江东北路交叉口2	19.7	32.55
黄河路与太湖路交叉口1	10.4	28.6
黄河路与太湖路交叉口2	31.7	16.1

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表 7 晴天场景参数取值

Table 7. Calibrated parameter values under sunny situation

参数	估计值	参数	估计值
A_ij	1.305	r_i	0.3
B_ij	1.112	A_iw	0.035
A_ib^r	2.186	B_iw	2.832
B_ib^r	3.158	v_i⁰(t)	1.52
A_ib^a	2.278	m	1
B_ib^a	3.081	τ_i	0.5
A_b	0.21	K	2.4×105
B_b	0.021	k	1.2×105
v_max	2.79

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表 8 雨天场景参数取值

Table 8. Calibrated parameter values under rainy situation

参数	估计值		参数	估计值
参数	打伞	未打伞	参数	打伞	未打伞
A_ij	2.074	2.074	r_i	0.42	0.3
B_ij	0.749	0.749	A_iw	0.322	0.168
A_ib^r	1.139	1.139	B_iw	0.651	2.249
B_ib^r	6.176	6.176	v_i⁰(t)	1.43	1.58
A_ib^a	0.753	0.753	m	1	1
B_ib^a	6.264	6.264	τi	0.5	0.5
A_b	0.47	0.47	K	2.4×105	2.4×105
B_b	0.035	0.035	k	1.2×105	1.2×105
v_max	2.28	2.28

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表 9 行人轨迹的仿真精度

Table 9. Simulation accuracy of pedestrian crossing trajectories

场景	天气	RMSE
单向直行	晴天	0.245
单向直行	雨天	0.329
对向避让	晴天	0.483
对向避让	雨天	0.702

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表 10 晴天配对t检验分析结果

Table 10. The results of paired t - test under sunny condition

名称	配对（平均值±标准差）		差值（配对1-配对2）	t	p
名称	配对1	配对2	差值（配对1-配对2）	t	p
晴天实际
配对	1.52±0.29	1.55±0.25	-0.03	0.452	0.689
晴天模拟
注：* p < 0.05 ** p < 0.001

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表 11 雨天配对t检验分析结果

Table 11. The results of paired t - test under rainy condition

名称	配对（平均值±标准差）		差值（配对1-配对2）	t	p
名称	配对1	配对2	差值（配对1-配对2）	t	p
雨天实际
配对	1.43±0.31	1.33±0.28	0.10	0.483	0.630
雨天模拟
注：* p < 0.05 ** p < 0.001

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表 12 行人流过街溢出幅度仿真的统计结果

Table 12. Statistical results of simulated overflow magnitude of crossing pedestrian flow 单位: %

天气	平均	中位数	标准差	最小值	最大值
晴天	12.38	12.56	4.38	5.04	19.99
雨天	17.64	17.68	4.42	10.05	24.97

下载: 导出CSV

参考文献(27)

[1]	陆丽丽. 信号控制交叉口过街行人流仿真建模及应用[D]. 南京: 东南大学, 2016. LU L L. Simulation model for pedestrian flow at signalized crosswalk and ITS application[D]. Nanjing: Southeast University, 2016. (in Chinese)
[2]	FORDE A, DANIEL J. Pedestrian walking speed at un-signalized midblock crosswalk and its impact on urban street segment performance[J]. Journal of Traffic and Transportation Engineering, 2021, 8(1): 57-69.
[3]	ZHANG C B, CHEN F, WEI Y Y. Evaluation of pedestrian crossing behavior and safety at uncontrolled mid-block crosswalks with different numbers of lanes in China[J]. Accident Analysis and Prevention, 2019, 123: 263-273. doi: 10.1016/j.aap.2018.12.002
[4]	BENDAK S, ALNAQBIAM, ALZAROONI M Y, et al. Factors affecting pedestrian behaviors at signalized crosswalks: an empiricalstudy[J]. JournalofSafetyResearch, 2021, 76: 269-275.
[5]	周泱, 周竹萍, 徐永能, 等. 交叉口绿闪信号行人过街行为模型[J]. 交通信息与安全, 2018, 36(1): 74-80. 10.3963/j.issn.1674-4861.2018.01.010 ZHOU Y, ZHOU Z P, XU Y N, et al. A model for crossing behaviors of pedestrians at intersections during flashing green signals[J]. 2018, 36(1): 74-80. (in Chinese) 10.3963/j.issn.1674-4861.2018.01.010
[6]	GUPTA A, PUNDIR N. Pedestrian flow characteristics studies: a review[J]. Transport Reviews, 2015, 35(4): 445-465. doi: 10.1080/01441647.2015.1017866
[7]	ALHAJYASEEN W K M, NAKAMURA H. Estimating the minimum required width of signalized crosswalks considering bi-directional pedestrian flow and different age groups[J]. Asian Transport Studies, 2010, 1(2): 181-198.
[8]	NAGATANIT, MURAMATSUM. Jamming transition of pedestrian traffic at a crossing with open boundaries[J]. Physica A: StatisticalMechanics and itsApplications, 2000, 286: 377-390.
[9]	XIAO Y, GAO Z Y, QU Y C, et al. A pedestrian flow model considering the impact of local density: Voronoi diagram based heuristics approach[J], Transportation Research Part C: Emerging Technologies, 2016, 68: 566-580. doi: 10.1016/j.trc.2016.05.012
[10]	何大治, 李晓克, 李明明. 考虑视域影响的疏散行为建模及双向行人流仿真[J]. 浙江大学学报(工学报), 2020, 54(6): 1185-1193. HE D Z, LI X K, LI M M. Evacuation behaviour modelling and simulation of pedestrian counter flow considering influence of visual field[J]. Journal of Zhejiang University (Engineering Science), 2020, 54(6): 1185-1193 (in Chinese)
[11]	LI Q R, ZHANG Z, LI K, et al. Evolutionary dynamics of traveling behavior in social networks[J], Physica A: Statistical Mechanics and its Applications, 2020, 545: 8.
[12]	刘小明, 魏鹏飞, 李正熙. 无灯控行人过街元胞自动机交通模型研究[J]. 交通信息与安全, 2012, 30(2): 6-9. doi: 10.3963/j.ISSN1674-4861.2012.02.002 LIU X M, WEI P F, LI Z X. Modeling street crossing of pedestrians based on cellular automaton without signal lamp[J]. Journal of Transport Information and Safety, 2012, 30(2): 6-9. (in Chinese)) doi: 10.3963/j.ISSN1674-4861.2012.02.002
[13]	GEORGE K, IOANNA S CONSTANTINOS A. Pedestrian simulation: theoretical models vs. data driven techniques[J]. International Journal of Transportation Science and Technology, 2018.09.001.
[14]	NI Y, LI K. Modelling pedestrian behavior at signalized intersections: a case study in shanghai[C]. The 1st International Conference on Transportation Information and Safety, Wuhan, China: American Society of Civil Engineers, 2011.
[15]	ZHU Y L, QIAN D H, REN D C, et al. StarNet: Pedestrian trajectory prediction using deep neural network in star topology[C]. 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China: IEEE, 2019.
[16]	MOVAHHED M B, AYOUBINEJAD J, ASL F N, et al. The effect of rain on pedestrians crossing speed[J]. Computational Research Progress in Applied Science and Engineering (CRPASE), 2020, 6(3): 186-190.
[17]	BARFEOGOL I, GILANI V N M, HOSSEINIAN S M, et al, Pedestrians crossing and walking speeds analysis in urban areas under the influence of rain and personality characteristics, mathematical problems in engineering, 2022, 2022: 13.
[18]	GUO N, HAO Q Y, JIANG R, et al. Uni-and bi-directional pedestrian flow in the view-limited condition: experiments and modeling[J]. Transportation Research Part C: Emerging Technologies, 2016, 71: 63-85. doi: 10.1016/j.trc.2016.07.001
[19]	王承梅, 杜豫川. 基于YOLO算法的复杂交通环境中车辆目标检测方法[J]. 交通与运输, 2023, 39(2): 20-24. doi: 10.3969/j.issn.1671-3400.2023.02.006 WANG C M. DU Y C. Vehicle object detection method in complex traffic environment based on YOLO algorithm[J]. Traffic and Transportation, 2023, 39(2): 20-24 (in Chinese) doi: 10.3969/j.issn.1671-3400.2023.02.006
[20]	田顺, 田山山, 杨炜, 等. 基于车道线虚线角点检测的行车安全视距测算模型[J]. 交通信息与安全, 2022, 40(2): 30-37. doi: 10.3963/j.jssn.1674-4861.2022.02.004 TIAN S, TIAN S S, YANG W, et al. A model for estimating driving sight distances based on corner point of broken line of roadway[J]. Journal of Transport Information and Safety, 2022, 40(2): 30-37. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2022.02.004
[21]	马尚, 张蕊, 齐泽阳, 等. 对向行人避让与接触行为社会力模型改进研究[J]. 计算机仿真, 2021, 38(3): 63-67, 77. doi: 10.3969/j.issn.1006-9348.2021.03.013 MA S, ZHANG R, QI Z Y, et al. Research on improvement of social force model of opposite pedestrian avoidance and contact behavior[J]. Computer Simulation, 2021, 38(3): 63-67, 77. (in Chinese) doi: 10.3969/j.issn.1006-9348.2021.03.013
[22]	ZENG W L, PENG C, NAKAMURA H, et al. Application of social force model to pedestrian behavior analysis at signalized crosswalk[J]. Transportation Research Part C: Emerging Technologies, 2014, 40(mar. ): 143-159.
[23]	郭谨一, 刘爽, 陈绍宽, 等. 行人运动仿真研究综述[J]. 系统仿真学报, 2008, 20(9): 2237-2242. GUO J Y, LIU S, CHEN S K, et al. Review of pedestrian movement simulation studies[J]. Journal of System Simulation, 2008, 20(9): 2237-2242. (in Chinese)
[24]	王雷, 张勃, 郑则立, 等. 基于社会力模型的体育场馆人员疏散仿真研究[J]. 建筑学报, 2022, 25(增刊1): 239-245. WANG L ZHANG B, ZHENG Z L, et al. Simulation study of crowd evacuation in stadiums based on social force model[J]. Architectural Journal, 2022, 25(S1): 239-245. (in Chinese)
[25]	曹宁博, 陈永恒, 曲昭伟, 等. 基于社会力模型的行人路径选择模型[J]. 浙江大学学报(工学版), 2018, 52(2): 352-357. CAO N B, CHEN Y H, QU Z W, et al. Pedestrian route choice model based on social force model[J]. Journal of Zhejiang University (Engineering Science), 2018, 52(2): 352-357. (in Chinese)
[26]	刘博, 周晨静, 林建新. 无信号交叉口仿真模型参数标定优化与验证[J]. 公路交通科技, 2021, 38(10): 129-136. doi: 10.3969/j.issn.1002-0268.2021.10.017 LIU B, ZHOU C J, LIN J X. Optimization and verification of calibrating parameters of simulation model of unsignalized intersection[J]. Journal of Highway and Transportation Research and Development, 2021, 38(10): 129-136. (in Chinese) doi: 10.3969/j.issn.1002-0268.2021.10.017
[27]	曹宁博. 城市道路环境下行人过街微观仿真模型研究[D]. 长春: 吉林大学2018. CAO N B. Study on microscopic simulation model of pedestrian crossing in the urban road environment[D]. Changchun: Jilin University, 2018. (in Chinese)