Simulation of bi-direction pedestrian movement in corridor

The pedestrian movement is more complex than vehicular flow for the reason that people are more flexible and intelligent than cars. Without the limit of “lanes” pedestrian movement is loose and free. Furthermore, they are easily affected by other walkers as well as the environment around. In this paper, a special technique is introduced considering human behavior to make the rules more reasonable. By simulating the two-dimension pedestrian movement in corridor, the phase transition phenomena of pedestrian movement, including the walkers moving bottom-up and top-down, are presented. Studying on the effect of possibility of exchange position between face-to-face pedestrians propose that the considerable exchange possibility is about 0.20 in the scope studied in this paper.

[1]  M. Fukui,et al.  Traffic Flow in 1D Cellular Automaton Model Including Cars Moving with High Speed , 1996 .

[2]  Michael Schreckenberg,et al.  Simulation of competitive egress behavior: comparison with aircraft evacuation data , 2003 .

[3]  Dirk Helbing,et al.  Simulating dynamical features of escape panic , 2000, Nature.

[4]  Katsuhiro Nishinari,et al.  Simulation for pedestrian dynamics by real-coded cellular automata (RCA) , 2007 .

[5]  T. Nagatani,et al.  Experiment and simulation of pedestrian counter flow , 2004 .

[6]  D. Helbing,et al.  VERKEHRSDYNAMIK. NEUE PHYSIKALISCHE MODELLIERUNGSKONZEPTE , 1997 .

[7]  Kerner,et al.  Experimental properties of complexity in traffic flow. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[8]  Dietrich E. Wolf,et al.  Cellular automata for traffic simulations , 1999 .

[9]  V. Sisiopiku,et al.  PEDESTRIAN BEHAVIORS AT AND PERCEPTIONS TOWARDS VARIOUS PEDESTRIAN FACILITIES: AN EXAMINATION BASED ON OBSERVATION AND SURVEY DATA , 2003 .

[10]  A. Schadschneider.  Statistical Physics of Traffic Flow , 2000, cond-mat/0007418.

[11]  Cuesta,et al.  Phase transitions in two-dimensional traffic-flow models. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[12]  A. Schadschneider,et al.  Simulation of pedestrian dynamics using a two dimensional cellular automaton , 2001 .

[13]  Serge P. Hoogendoorn,et al.  DYNAMIC USER-OPTIMAL ASSIGNMENT IN CONTINUOUS TIME AND SPACE , 2004 .

[14]  Nagel,et al.  Discrete stochastic models for traffic flow. , 1994, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[15]  Middleton,et al.  Self-organization and a dynamical transition in traffic-flow models. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[16]  D. Wolf,et al.  Traffic and Granular Flow , 1996 .

[17]  Michael Schreckenberg,et al.  A cellular automaton model for freeway traffic , 1992 .

[18]  Helbing,et al.  Social force model for pedestrian dynamics. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[19]  L. Leden.  Pedestrian risk decrease with pedestrian flow. A case study based on data from signalized intersections in Hamilton, Ontario. , 2002, Accident; analysis and prevention.

[20]  M Suzanne Zeedyk,et al.  Behavioural observations of adult-child pairs at pedestrian crossings. , 2003, Accident; analysis and prevention.

[21]  Victor J. Blue,et al.  Cellular automata microsimulation for modeling bi-directional pedestrian walkways , 2001 .

[22]  Lizhong Yang,et al.  Occupant evacuation model based on cellular automata in fire , 2002 .

[23]  Nagatani.  Jamming transition in the traffic-flow model with two-level crossings. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[24]  T. Nagatani,et al.  Jamming transition in pedestrian counter flow , 1999 .

[25]  Dirk Helbing,et al.  Granular and Traffic Flow ’99: Social, Traffic, and Granular Dynamics , 2000 .

[26]  Hui,et al.  Two-dimensional traffic flow problems with faulty traffic lights. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[27]  Kerner,et al.  Experimental features and characteristics of traffic jams. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[28]  Stephen Wolfram,et al.  Cellular Automata And Complexity , 1994 .

[29]  Stephen Wolfram,et al.  Theory and Applications of Cellular Automata , 1986 .

[30]  Serge P. Hoogendoorn,et al.  Pedestrian route-choice and activity scheduling theory and models , 2004 .

[31]  Shing Chung Josh Wong,et al.  Lane-based optimization of signal timings for isolated junctions , 2003 .