| ELECTROMAGNETISM, OPTICS, ACOUSTICS, HEAT TRANSFER, CLASSICAL MECHANICS, AND FLUID DYNAMICS |
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Cellular automaton modeling of pedestrian movement behavior on an escalator |
| Fu-Rong Yue(岳芙蓉)1, Juan Chen(陈娟)2, Jian Ma(马剑)1,5, Wei-Guo Song(宋卫国)3, Siu-Ming Lo(卢兆明)4 |
1 School of Transportation and Logistics, National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu 610031, China;
2 Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610031, China;
3 State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230026, China;
4 Department of Architectural and Civil Engineering, City University of Hong Kong, China;
5 Beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster Prevention, Beijing 100044, China |
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Abstract As a convenient passenger transit facility between floors with different heights, escalators have been extensively used in shopping malls, metro stations, airport terminals, etc. Compared with other vertical transit facilities including stairs and elevators, escalators usually have large transit capacity. It is expected to reduce pedestrian traveling time and thus improve the quality of pedestrian's experiences especially in jamming conditions. However, it is noticed that pedestrians may present different movement patterns, e.g., queuing on each step of the escalator, walking on the left-side and meanwhile standing on the right-side of the escalator. These different patterns affect the actual escalator traffic volume and finally the passenger spatiotemporal distribution in different built environments. Thus, in the present study, a microscopic cellular automaton (CA) simulation model considering pedestrian movement behavior on escalators is built. Simulations are performed considering different pedestrian movement speeds, queuing modes, and segregation on escalators with different escalator speeds. The actual escalator capacities under different pedestrian movement patterns are investigated. It is found that walking on escalators will not always benefit escalator transit volume improvement, especially in jamming conditions.
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Received: 25 June 2018
Revised: 14 September 2018
Accepted manuscript online:
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PACS:
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45.70.Vn
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(Granular models of complex systems; traffic flow)
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87.10.Hk
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(Lattice models)
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07.05.Tp
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(Computer modeling and simulation)
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| Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 71473207 and 71871189), the Research Grant Council of the Hong Kong Administrative Region, China (Grant No. CityU118909), and the Open Fund of Beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster Prevention (Grant No. RRC201701). |
Corresponding Authors:
Jian Ma
E-mail: majian@mail.ustc.edu.cn
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Cite this article:
Fu-Rong Yue(岳芙蓉), Juan Chen(陈娟), Jian Ma(马剑), Wei-Guo Song(宋卫国), Siu-Ming Lo(卢兆明) Cellular automaton modeling of pedestrian movement behavior on an escalator 2018 Chin. Phys. B 27 124501
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| [1] |
Fang J S, El-Tawil S and Aguirre B 2016 Safety Sci. 83 40
|
| [2] |
Agnelli J P, Colasuonno F and Knopoff D 2015 Math. Models & Methods Appl. Sci. 25 109
|
| [3] |
Helbing D, Molnár P, Farkas I J and Bolay K 2001 Environment & Planning B Planning Design 28 361
|
| [4] |
Zhang D W, Zhu H T and Du L Hostikka S 2018 Phys. Lett. A 382 3172
|
| [5] |
Nagel K and Schreckenberg M 1992 Journal de Physique I 2 2221
|
| [6] |
Burstedde C, Klauck K, Schadschneider A and Zittartz J 2001 Physica A: Statistical Mechanics and its Applications 295 507
|
| [7] |
Kirchner A and Schadschneider A 2002 Physica A-Stat. Mech. Its Appl. 312 260
|
| [8] |
Shimura K, Ohtsuka K, Vizzari G, Nishinari K and Bandini S 2014 Pattern Recognition Lett. 44 58
|
| [9] |
Dias C and Lovreglio R 2018 Phys. Lett. A 382 1255
|
| [10] |
Cao S C, Fu L B and Song W G 2018 Appl. Math. Comput. 332 136
|
| [11] |
Yue H, Shao C F and Yao Z S 2009 Acta Phys. Sin. 58 4523 (in Chinese)
|
| [12] |
Ren G, Lu L L and Wang W 2012 Acta Phys. Sin. 61 255 (in Chinese)
|
| [13] |
Zheng L, Ma S F and Jia N 2010 Acta Phys. Sin. 59 4490 (in Chinese)
|
| [14] |
Fu L, Song W G and Lo S M 2016 Phys. Lett. A 380 2619
|
| [15] |
Helbing D and Molnar P 1995 Phys. Rev. E 51 4282
|
| [16] |
Johansson F, Peterson A and Tapani A 2015 Physica A-Stat. Mech. Its Appl. 419 95
|
| [17] |
Qu Y C, Xiao Y, Wu J J, Tang T and Gao Z Y 2018 Physica A-Stat. Mech. Its Appl. 492 1153
|
| [18] |
Lu L L, Chan C Y, Wang J and Wang W 2017 Transportation Res. Part. C Emerging Technol. 81 317
|
| [19] |
Liao Y J, Lo S M, Ma J, Liu S B and Liao G X 2014 Fire Technol. 50 363
|
| [20] |
Li W H, Gong J H, Yu P and Shen S 2016 Physica A-Stat. Mech. Its Appl. 444 970
|
| [21] |
Xing Y, Dissanayake S, Lu J, Long S and Lou Y 2017 Accident; analysis and prevention
|
| [22] |
Ji X F, Zhang J and Ran B 2013 Physica A-Stat. Mech. Its Appl. 392 5089
|
| [23] |
Xu X and Song W G 2009 Building Environment 44 1039
|
| [24] |
Ryus P, Vandehey M, Elefteriadou L, Dowling R G and Ostrom B K 2011 New TRB Publication: Highway Capacity Manual 2010 31-39
|
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