Intelligent Pedestrian Flow Monitoring Systems in Shopping Areas ZHENG Jianhu
YAO Dongliang
Department of Automobile Engineering Minjiang University Fuzhou, Fujian, P.R.China [email protected]
Beijing Municipal Institute of Labor Protection Beijing Academy of Science and Technology Beijing, P.R.China [email protected]
Abstract—The prerequisites of human behavior and performance research need innovative methods for the collection of human factors data. Data generated from experimental investigations of human performance in pedestrian situations have some instinctive drawbacks such as the obvious deviation from the natural pedestrian behaviors. Real-time pedestrian dynamic data obtained from on-site pedestrian flow monitoring system will help us record the genuine pedestrian situations by instruments and analyze the flow parameters such as velocity, density and flow rate. This project will help us develop a pedestrian flow prediction and risk management system (hardware and software) that may apply to many other shopping districts. Keywords-crowd massing risk; risk analysis; public venues
I.
INTRODUCTION
Environmental testing includes field experiments and laboratory experiments. (1) Laboratory experiment Laboratory experiment generally conducted in the laboratory, also known as artificial simulation that is to use the artificial means to create a certain environment. Compared to field trials, artificial simulation is identical to its simulation results in nature, but has higher efficiency. It can greatly shorten the test time, and its external environment can be strictly controlled within the tolerances to ensure that all tests to be carried out under controlled conditions which make it to be reproducible and comparable. However, its drawback is subject to equipment and environmental conditions, and sometimes the simulation of an integrated environment is far from a real-world experiment. (2) Field experiment The laboratory simulation is subject to various restrictions, or even impossible to conduct some experiments in the laboratory; if it could be tested, laboratory testing can not be completely realistic simulation of the scenario and can not be assessed. Field test contains the characteristics of real, reliable simulation and imitates the impossible scenarios that can not be conducted in laboratories. The disadvantage is that testing does not guarantee the simulation is performed under controlled conditions, so the test conditions and results are with poor reproducibility. Large department stores and busy shopping districts often hold a huge variety of activities and make visitors to
spend more time in. In addition, there are many types of pedestrian traffic facilities. The spatial complexity results in higher frequency of the occurrence of unexpected events. This is especially true in the holidays when huge crowds tend to gather in a short amount of time. At present, we are unclear about the mechanism of the occurrence of many of these unexpected events[1]. Xi Dan is a busy shopping district in Beijing. In 2006, its retailing revenue was 5.09 Billion RMB, accounting for 22.7% of the total retailing revenue of Xi Cheng District. The traffic in Xi Dan is of high volume, particularly in holidays. For example, on the China’s National Day (Oct. 1st) in 2008, from 9 am to 9 pm, the total amount of customers visiting Xi Dan was approximately 630,000. However, on a normal weekday (e.g., 1/22/2009), the amount of pedestrians was only about 30,000. Such huge variation has presented great challenges to the government in pedestrian traffic control. Although the public facilities have been improved significantly these years in Xi Dan, it should still be noted that with the current traffic network, a huge crowd is capable of being gathered in Xi Dan in a short amount of time. As a result, it is very likely that high density of crowd occurs in many places such as subway entrances, overhead pedestrian bridges, underground markets, etc. The characteristics of crush and stampede accident determines the poor effect of rescue actions after accident occurrences[2]. An early warning and prevention is almost the only effective strategy. The current information technology is able to provide strong technical support for early warning of the crowd massing and provide real-time warning of the crowd situation throughout the region. In order to ensure the continued prosperity and development of Xi Dan shopping area and solve the crowd safety issues scientifically and effectively, the local government in Xicheng district and west Changan streets introduced early warning technology to the crowd risk management, enhancing the intelligent ability of government management, which achieves the change from passivity to activity. Here, it plans to carry out in-depth investigation, analysis and summary of the crowd traffic flow laws in Xi Dan shopping area, establish a real-time monitoring and analysis system that cover the whole region. From which, we can obtain real-time and accurate safety situation of the
978-1-4244-6974-1/10/$26.00 ©2010 IEEE
crowd from the monitoring data, and provide early warning of the crush and stampede accident. II.
OBJECTIVES
This proposal aims to ensure the sustainable, logical, and efficient development of Xi Dan district by developing a crowd risk alarm system. The proposal plans to conduct field studies, data analysis, and mathematical modeling of pedestrian traffic flow in Xi Dan. The goal is to develop a real-time monitoring and analysis system for the crowd risk by employing intelligent monitoring devices, acquiring pedestrian traffic flow data, and executing realtime risk prediction and assessment algorithms. After many years development, the intelligent monitoring system for the analysis of visual information has considerable reliability, and can be used as a means of real-time alarm. The project has integrated existing video surveillance technology and massing crowd risk analysis methodology, and then provided a solution of the crowd risk alarm, early warning, thresholds and evacuation strategies. The project utilized the existing monitoring technology, established a scientifically quantitative model and integrated early warning systems. By monitoring population density, traffic flow rate and other parameters in the bridges, channels, hot spots and the entire business district, we can erect a reasonable capacity standard and provide a hierarchical early warning. From which, the decision of risk control is made reasonably. Project objectives can be summarized by building early warning systems in Xi Dan shopping area, monitoring the population density in the key positions, analyzing the crowd traffic flow, discerning the crowded level or jam, forecasting the trend of the massing crowd in a short-term, and providing hierarchical early warning information and the possible disposal strategies. III.
MAIN TASKS TO BE SOLVED
Proposed items: Developing mechanistic models for predicting pedestrian flow under emergency circumstances; Developing mathematical and statistical prediction models for pedestrian traffic in Xi Dan; Designing efficient traffic flow data acquisition protocols; Developing prediction models based on real-time traffic data; System testing and verification. Employing monitoring device: Developing a protocol for categorizing crowd risk based on the characteristics of the activities; Developing the integrated risk management system; Implementation and testing. Research Questions: How to survey pedestrian flow and develop network models?
How to quantify and categorize flow and congestion? How to develop models and solutions for predicting pedestrian flow? IV.
DETAILED IMPLEMENTATION SCHEME
The preliminary scheme of the subject included the implementation of main technologies, the construction of demonstration projects, the technical route and methods that may be taken. The following topics briefly introduced the implementation scheme. A. Survey and analysis the law of the pedestrian flow Investigate the pedestrian flow speed, density in the major roads, streets, bridges and the law of path choosing in Xi Dan shopping area normally. Analyze the traffic changes, the bottleneck and the law of relieving and spreading the traffic jam. 1) Radio frequency identification (RFID) In the sources of the pedestrian flow such as bus station or subway station, we arranged the RFID card distribution stations. Within the predefined critical time slices, the stations send out cards to pedestrian passing by. Also, the card readers are settled down in the bottlenecks or corners to record the track of pedestrian and memorize in the storage [3]. 2) Field survey In the weekend or holidays, the field survey can be carried out using monitoring camera or naked eyes. 3) Computer simulations If the parameters of pedestrian flows can be obtained, these parameters can be input into the building Exdous or STEPs code. From the simulation results, the locations that are vulnerable to the crowded pedestrians or the crowded levels in different time slices can be discerned [4-5]. B. Monitoring sites designations In the south of Xi Dan shopping area, it chose two flyovers, passages, subways and bus station to install intelligent surveillance equipments. The data acquisition used for real-time forecasting model and the real-time management of the Xi Dan shopping area through the surveillance in the crowded parts can be reached at the scene. The principles of the monitoring sites selection are: 1) Some of the mass transit railway station and bus station used for the pedestrian access to the Xi Dan shopping area; 2) Section of the crowd gathering, accident-prone bridges and stairs, escalators; 3) Main roads around shopping malls; 4) Traffic bottlenecks. C. Grading methods of early warning information Through various monitoring sites, real-time pedestrian flow data from video surveillance can be obtained. Warning criteria here is for the judgment standards and
principles in different situations serving for when alerts should be issued, as well as the extent to which the warning is issued. Considering the early warning scale, it can not be set too strict or too loose. Otherwise it leads to warning missing or false alarm. Warning missing resulted in disaster out of effective detection if it did occur. False alarm made us cast doubt to the accuracy of prediction. People would suspect to the warning system and lose confidence in the warning signal. Further, the false alarm should have lost its role in the accident prevention which can also result in losses [6-7]. Four main factors related to classification of early warning information needs to be considered, namely the types of activities, places, participants and disasters. D. A short-term forecasting model of the pedestrian flow Using the short-term traffic prediction model for modern intelligent transportation of vehicles and considering the characteristics of crowd movements and the road network in Xi Dan area, the establishment of a suitable pedestrian traffic short-term forecasting model in Xi Dan shopping area can be reached. First, the time interval for pedestrian data collection, time series analysis and forecasting in various monitoring points must be predefined. Second, in accordance with the pedestrian movement law, some adjacent monitoring points considering the people living in upstream and downstream of these monitoring points can be figured out that was used for data interdependence analysis. Third, in Xi Dan shopping area, combined with the I/O pedestrian flows, pedestrian path-choosing law and crowd density with its corresponding capacity change in different flyovers or major roads, parameters related to simulation is set up for crowd flow simulation in Xi Dan shopping area. In terms of simulation results, we can determine the counter-flow, the continued flow of high-density line, the formation of bottleneck congestion and its locations, duration and terminations, as well as its impacts on upstream and downstream congestions [8-10]. E. Equipments installation and debugging and system construction Systems’ core modules include: front-end video capture and data processing module, data transmission module, data storage module, short-term forecasting and warning module, 2.5D virtual reality display and its accessories. 1) Front-end video capture and data-processing module Video capture devices should take into account the stability of data acquisition, high-quality and maintainability. Front-end data-processing equipment must be compatible with the back-end software. 2) Data transmission module Given the intensive constructions in Xi Dan shopping area, heavy traffic is not conducive to road construction and pavement lines, so as to set up a special network of microwave wireless communication. Also public
communications resources (ADSL, IDC) can be used as a complementary and supplementary means in and around Xi Dan shopping areas and improve the data transmission quality, the feasibility of the deployment of security systems, security and scalability. 3) Data storage module It used internationally renowned brands that ensured the safe and reliable data storage. 4) Short-term forecasting and warning module Through short-term forecasting model, this system predicted the crowd status after 10 minutes in the monitoring sites and key parts of the Xi Dan commercial district. Compared to crowd density standards, the early warning information can be identified and issued 5) 2.5D virtual reality display Virtual reality technology was used to build virtual environment of 2.5D Xi Dan shopping area. 6) Accessories. Power supply and large-screen display. F. Model verification and system test In Xi Dan shopping area, the crowd flow will be affected by different seasons, festivals, kinds of promotions in shopping malls, new transport facilities and other factors. Therefore, the initially designed model needs further validation; the entire system requires necessary tests in order to more accurately reflect the crowd movement in the Xi Dan. In general, a short-term traffic prediction after 10 minutes or half an hour aims at the understanding of the traffic conditions in the near future. The crowd status and traffic flow data at the scene from the monitoring system serve for comparison with judgment in advance and the early warning signal with the true data 10 minutes later. In the debugging phase, we can constantly repeat the process and make use of the naked eyes observations at the scene to amend the forecasting model, grading methods and the monitoring data which can adjust and improve the whole system step by step and finally reach the requirements of practical applications. V.
CONCLUSIONS
Many busy shopping districts have emerged with the rapid development of the Chinese economy. This project will help us develop a pedestrian flow prediction and risk management system (hardware + software) that may apply to many other shopping districts. In the past, massing crowd research was focused on the crowd observation, how to measure the flow state, computer simulation about evacuation, building performance-based design, which lacked the whole process of dynamic risk identification and quantitative analysis methods, also a early-warning technology and risk prediction in advance was unavailable. The implementation of this project is to seek the development of dynamic risk monitoring, diagnosis and pre-exemption actions. Also it is a major emergency incident risk management techniques. It can make up for the deficiencies in the crowd risk early warning,
emergency response, decision-making and social interaction, so as to effectively prevent the occurrence of unexpected events and reduce the incidents losses and improve the level of crowd safety management. ACKNOWLEDGMENT This research was supported by the Foundation of Fujian Educational Committee (No. JB09185).
REFERENCES [1]
Lee R C and Hughes R L, “Exploring trampling and crushing in a crowd,” Journal of transportation engineering, Vol.131, No.8, pp.575-582. [2] Helbing D, Traffic and related self-driven many-particle sysetms, Reviews of Modern Physics, Vol.73, 2001, pp.1067-1141. [3] Helbing D, Farkas I and Vicsek. T, Simulating dynamical features of escape panic, Nature, Vol.407, 2000, pp.487-490. [4] Henein C M and White T, Macroscopic effects of microscopic forces between agents in crowd models, Physica A: statistical mechanics and its applications, Vol.373, 2007, pp.694-712. [5] Kirchner A and Schadschneider A. Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics, Physica A: statistical mechanics and its applications, Vol.312, 2002, pp.260-276. [6] Heigeas L, Luciani A and Thollot J, A physically-based particle model of emergent crowd behaviors. Moscow: International Conference on Computer Graphics & Vision, 2003. [7] Teknomo K, Microscopic pedestrian fow characteristics: Development of an image processing data collection and simulation model. Sendai: Tohoku University, 2002. [8] Valach L, Young R A and Lynam M J, A primer for applied research in the social science. Praeger: Westport,Conn, 2002. [9] Canetti E, Crowds and Power. London: Phoenix Press, 2000. [10] Mcphail C, The myth of the madding crowd. New York: Walter de Gruyter, 1991.
YAO Dongliang
Department of Automobile Engineering Minjiang University Fuzhou, Fujian, P.R.China [email protected]
Beijing Municipal Institute of Labor Protection Beijing Academy of Science and Technology Beijing, P.R.China [email protected]
Abstract—The prerequisites of human behavior and performance research need innovative methods for the collection of human factors data. Data generated from experimental investigations of human performance in pedestrian situations have some instinctive drawbacks such as the obvious deviation from the natural pedestrian behaviors. Real-time pedestrian dynamic data obtained from on-site pedestrian flow monitoring system will help us record the genuine pedestrian situations by instruments and analyze the flow parameters such as velocity, density and flow rate. This project will help us develop a pedestrian flow prediction and risk management system (hardware and software) that may apply to many other shopping districts. Keywords-crowd massing risk; risk analysis; public venues
I.
INTRODUCTION
Environmental testing includes field experiments and laboratory experiments. (1) Laboratory experiment Laboratory experiment generally conducted in the laboratory, also known as artificial simulation that is to use the artificial means to create a certain environment. Compared to field trials, artificial simulation is identical to its simulation results in nature, but has higher efficiency. It can greatly shorten the test time, and its external environment can be strictly controlled within the tolerances to ensure that all tests to be carried out under controlled conditions which make it to be reproducible and comparable. However, its drawback is subject to equipment and environmental conditions, and sometimes the simulation of an integrated environment is far from a real-world experiment. (2) Field experiment The laboratory simulation is subject to various restrictions, or even impossible to conduct some experiments in the laboratory; if it could be tested, laboratory testing can not be completely realistic simulation of the scenario and can not be assessed. Field test contains the characteristics of real, reliable simulation and imitates the impossible scenarios that can not be conducted in laboratories. The disadvantage is that testing does not guarantee the simulation is performed under controlled conditions, so the test conditions and results are with poor reproducibility. Large department stores and busy shopping districts often hold a huge variety of activities and make visitors to
spend more time in. In addition, there are many types of pedestrian traffic facilities. The spatial complexity results in higher frequency of the occurrence of unexpected events. This is especially true in the holidays when huge crowds tend to gather in a short amount of time. At present, we are unclear about the mechanism of the occurrence of many of these unexpected events[1]. Xi Dan is a busy shopping district in Beijing. In 2006, its retailing revenue was 5.09 Billion RMB, accounting for 22.7% of the total retailing revenue of Xi Cheng District. The traffic in Xi Dan is of high volume, particularly in holidays. For example, on the China’s National Day (Oct. 1st) in 2008, from 9 am to 9 pm, the total amount of customers visiting Xi Dan was approximately 630,000. However, on a normal weekday (e.g., 1/22/2009), the amount of pedestrians was only about 30,000. Such huge variation has presented great challenges to the government in pedestrian traffic control. Although the public facilities have been improved significantly these years in Xi Dan, it should still be noted that with the current traffic network, a huge crowd is capable of being gathered in Xi Dan in a short amount of time. As a result, it is very likely that high density of crowd occurs in many places such as subway entrances, overhead pedestrian bridges, underground markets, etc. The characteristics of crush and stampede accident determines the poor effect of rescue actions after accident occurrences[2]. An early warning and prevention is almost the only effective strategy. The current information technology is able to provide strong technical support for early warning of the crowd massing and provide real-time warning of the crowd situation throughout the region. In order to ensure the continued prosperity and development of Xi Dan shopping area and solve the crowd safety issues scientifically and effectively, the local government in Xicheng district and west Changan streets introduced early warning technology to the crowd risk management, enhancing the intelligent ability of government management, which achieves the change from passivity to activity. Here, it plans to carry out in-depth investigation, analysis and summary of the crowd traffic flow laws in Xi Dan shopping area, establish a real-time monitoring and analysis system that cover the whole region. From which, we can obtain real-time and accurate safety situation of the
978-1-4244-6974-1/10/$26.00 ©2010 IEEE
crowd from the monitoring data, and provide early warning of the crush and stampede accident. II.
OBJECTIVES
This proposal aims to ensure the sustainable, logical, and efficient development of Xi Dan district by developing a crowd risk alarm system. The proposal plans to conduct field studies, data analysis, and mathematical modeling of pedestrian traffic flow in Xi Dan. The goal is to develop a real-time monitoring and analysis system for the crowd risk by employing intelligent monitoring devices, acquiring pedestrian traffic flow data, and executing realtime risk prediction and assessment algorithms. After many years development, the intelligent monitoring system for the analysis of visual information has considerable reliability, and can be used as a means of real-time alarm. The project has integrated existing video surveillance technology and massing crowd risk analysis methodology, and then provided a solution of the crowd risk alarm, early warning, thresholds and evacuation strategies. The project utilized the existing monitoring technology, established a scientifically quantitative model and integrated early warning systems. By monitoring population density, traffic flow rate and other parameters in the bridges, channels, hot spots and the entire business district, we can erect a reasonable capacity standard and provide a hierarchical early warning. From which, the decision of risk control is made reasonably. Project objectives can be summarized by building early warning systems in Xi Dan shopping area, monitoring the population density in the key positions, analyzing the crowd traffic flow, discerning the crowded level or jam, forecasting the trend of the massing crowd in a short-term, and providing hierarchical early warning information and the possible disposal strategies. III.
MAIN TASKS TO BE SOLVED
Proposed items: Developing mechanistic models for predicting pedestrian flow under emergency circumstances; Developing mathematical and statistical prediction models for pedestrian traffic in Xi Dan; Designing efficient traffic flow data acquisition protocols; Developing prediction models based on real-time traffic data; System testing and verification. Employing monitoring device: Developing a protocol for categorizing crowd risk based on the characteristics of the activities; Developing the integrated risk management system; Implementation and testing. Research Questions: How to survey pedestrian flow and develop network models?
How to quantify and categorize flow and congestion? How to develop models and solutions for predicting pedestrian flow? IV.
DETAILED IMPLEMENTATION SCHEME
The preliminary scheme of the subject included the implementation of main technologies, the construction of demonstration projects, the technical route and methods that may be taken. The following topics briefly introduced the implementation scheme. A. Survey and analysis the law of the pedestrian flow Investigate the pedestrian flow speed, density in the major roads, streets, bridges and the law of path choosing in Xi Dan shopping area normally. Analyze the traffic changes, the bottleneck and the law of relieving and spreading the traffic jam. 1) Radio frequency identification (RFID) In the sources of the pedestrian flow such as bus station or subway station, we arranged the RFID card distribution stations. Within the predefined critical time slices, the stations send out cards to pedestrian passing by. Also, the card readers are settled down in the bottlenecks or corners to record the track of pedestrian and memorize in the storage [3]. 2) Field survey In the weekend or holidays, the field survey can be carried out using monitoring camera or naked eyes. 3) Computer simulations If the parameters of pedestrian flows can be obtained, these parameters can be input into the building Exdous or STEPs code. From the simulation results, the locations that are vulnerable to the crowded pedestrians or the crowded levels in different time slices can be discerned [4-5]. B. Monitoring sites designations In the south of Xi Dan shopping area, it chose two flyovers, passages, subways and bus station to install intelligent surveillance equipments. The data acquisition used for real-time forecasting model and the real-time management of the Xi Dan shopping area through the surveillance in the crowded parts can be reached at the scene. The principles of the monitoring sites selection are: 1) Some of the mass transit railway station and bus station used for the pedestrian access to the Xi Dan shopping area; 2) Section of the crowd gathering, accident-prone bridges and stairs, escalators; 3) Main roads around shopping malls; 4) Traffic bottlenecks. C. Grading methods of early warning information Through various monitoring sites, real-time pedestrian flow data from video surveillance can be obtained. Warning criteria here is for the judgment standards and
principles in different situations serving for when alerts should be issued, as well as the extent to which the warning is issued. Considering the early warning scale, it can not be set too strict or too loose. Otherwise it leads to warning missing or false alarm. Warning missing resulted in disaster out of effective detection if it did occur. False alarm made us cast doubt to the accuracy of prediction. People would suspect to the warning system and lose confidence in the warning signal. Further, the false alarm should have lost its role in the accident prevention which can also result in losses [6-7]. Four main factors related to classification of early warning information needs to be considered, namely the types of activities, places, participants and disasters. D. A short-term forecasting model of the pedestrian flow Using the short-term traffic prediction model for modern intelligent transportation of vehicles and considering the characteristics of crowd movements and the road network in Xi Dan area, the establishment of a suitable pedestrian traffic short-term forecasting model in Xi Dan shopping area can be reached. First, the time interval for pedestrian data collection, time series analysis and forecasting in various monitoring points must be predefined. Second, in accordance with the pedestrian movement law, some adjacent monitoring points considering the people living in upstream and downstream of these monitoring points can be figured out that was used for data interdependence analysis. Third, in Xi Dan shopping area, combined with the I/O pedestrian flows, pedestrian path-choosing law and crowd density with its corresponding capacity change in different flyovers or major roads, parameters related to simulation is set up for crowd flow simulation in Xi Dan shopping area. In terms of simulation results, we can determine the counter-flow, the continued flow of high-density line, the formation of bottleneck congestion and its locations, duration and terminations, as well as its impacts on upstream and downstream congestions [8-10]. E. Equipments installation and debugging and system construction Systems’ core modules include: front-end video capture and data processing module, data transmission module, data storage module, short-term forecasting and warning module, 2.5D virtual reality display and its accessories. 1) Front-end video capture and data-processing module Video capture devices should take into account the stability of data acquisition, high-quality and maintainability. Front-end data-processing equipment must be compatible with the back-end software. 2) Data transmission module Given the intensive constructions in Xi Dan shopping area, heavy traffic is not conducive to road construction and pavement lines, so as to set up a special network of microwave wireless communication. Also public
communications resources (ADSL, IDC) can be used as a complementary and supplementary means in and around Xi Dan shopping areas and improve the data transmission quality, the feasibility of the deployment of security systems, security and scalability. 3) Data storage module It used internationally renowned brands that ensured the safe and reliable data storage. 4) Short-term forecasting and warning module Through short-term forecasting model, this system predicted the crowd status after 10 minutes in the monitoring sites and key parts of the Xi Dan commercial district. Compared to crowd density standards, the early warning information can be identified and issued 5) 2.5D virtual reality display Virtual reality technology was used to build virtual environment of 2.5D Xi Dan shopping area. 6) Accessories. Power supply and large-screen display. F. Model verification and system test In Xi Dan shopping area, the crowd flow will be affected by different seasons, festivals, kinds of promotions in shopping malls, new transport facilities and other factors. Therefore, the initially designed model needs further validation; the entire system requires necessary tests in order to more accurately reflect the crowd movement in the Xi Dan. In general, a short-term traffic prediction after 10 minutes or half an hour aims at the understanding of the traffic conditions in the near future. The crowd status and traffic flow data at the scene from the monitoring system serve for comparison with judgment in advance and the early warning signal with the true data 10 minutes later. In the debugging phase, we can constantly repeat the process and make use of the naked eyes observations at the scene to amend the forecasting model, grading methods and the monitoring data which can adjust and improve the whole system step by step and finally reach the requirements of practical applications. V.
CONCLUSIONS
Many busy shopping districts have emerged with the rapid development of the Chinese economy. This project will help us develop a pedestrian flow prediction and risk management system (hardware + software) that may apply to many other shopping districts. In the past, massing crowd research was focused on the crowd observation, how to measure the flow state, computer simulation about evacuation, building performance-based design, which lacked the whole process of dynamic risk identification and quantitative analysis methods, also a early-warning technology and risk prediction in advance was unavailable. The implementation of this project is to seek the development of dynamic risk monitoring, diagnosis and pre-exemption actions. Also it is a major emergency incident risk management techniques. It can make up for the deficiencies in the crowd risk early warning,
emergency response, decision-making and social interaction, so as to effectively prevent the occurrence of unexpected events and reduce the incidents losses and improve the level of crowd safety management. ACKNOWLEDGMENT This research was supported by the Foundation of Fujian Educational Committee (No. JB09185).
REFERENCES [1]
Lee R C and Hughes R L, “Exploring trampling and crushing in a crowd,” Journal of transportation engineering, Vol.131, No.8, pp.575-582. [2] Helbing D, Traffic and related self-driven many-particle sysetms, Reviews of Modern Physics, Vol.73, 2001, pp.1067-1141. [3] Helbing D, Farkas I and Vicsek. T, Simulating dynamical features of escape panic, Nature, Vol.407, 2000, pp.487-490. [4] Henein C M and White T, Macroscopic effects of microscopic forces between agents in crowd models, Physica A: statistical mechanics and its applications, Vol.373, 2007, pp.694-712. [5] Kirchner A and Schadschneider A. Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics, Physica A: statistical mechanics and its applications, Vol.312, 2002, pp.260-276. [6] Heigeas L, Luciani A and Thollot J, A physically-based particle model of emergent crowd behaviors. Moscow: International Conference on Computer Graphics & Vision, 2003. [7] Teknomo K, Microscopic pedestrian fow characteristics: Development of an image processing data collection and simulation model. Sendai: Tohoku University, 2002. [8] Valach L, Young R A and Lynam M J, A primer for applied research in the social science. Praeger: Westport,Conn, 2002. [9] Canetti E, Crowds and Power. London: Phoenix Press, 2000. [10] Mcphail C, The myth of the madding crowd. New York: Walter de Gruyter, 1991.
