This paper reports observations of passenger flow in the Wuchang railway station in Wuhan, China during the Chinese Traditional Spring Festival in 2006. The data collected are used to verify a crowd dynamics model pre...This paper reports observations of passenger flow in the Wuchang railway station in Wuhan, China during the Chinese Traditional Spring Festival in 2006. The data collected are used to verify a crowd dynamics model previously developed. The crowd dynamics model is based on simulating the global movement of each individual under the influence of the surrounding crowd, and the good agreement between the predictions and observations validates the prediction model. The crowd dynamics model suggests that the crowd movement speed is dominated by two factors： the front-back inter-person effect, and the pedestrian＇s self-motive. The first effect gives logarithmic relationship between the crowd speed and crowd density. The second factor depends on the individual motive driven with which people try to divorce themselves from the control of the crowd movement. The prediction model are helpful to guide the design of public traffic systems for effective crowd dispersal.展开更多
Despite growing research for residential crowding effects on housing market and public health perspectives, relatively little attention has been paid to explore and model spatial patterns of residential crowding over ...Despite growing research for residential crowding effects on housing market and public health perspectives, relatively little attention has been paid to explore and model spatial patterns of residential crowding over space. This paper focuses upon analyzing the spatial relationships between residential crowding and socio-demographic variables in Alexandria neighborhoods, Egypt. Global and local geo-statistical techniques were employed within GIS-based platform to identify spatial?variations of residential crowding determinates. The global ordinary least squares (OLS) model?assumes homogeneity of relationships between response variable and explanatory variables?across the study area. Consequently, it fails to account for heterogeneity of spatial relationships. Local model known as a geographically weighted regression (GWR) was also employed using the same?response variable and explanatory variables to capture spatial non-stationary of residential?crowding. A comparison of the outputs of both models indicated that OLS explained 74 percent of?residential crowding variations while GWR model explained 79 percent. The GWR improvedstrength of the model and provided a better goodness of fit than OLS. In addition, the findings of this analysis revealed that residential crowding was significantly associated with different structural measures particularly social characteristics of household such as higher education and illiteracy. Similarly, population size of neighborhood and number of dwelling rooms were found to have direct impacts on residential crowding rate. The spatial relationship of these measures distinctly varies over the study area.展开更多
Many online platforms providing crowd with opportunities to participate in software development projects have been existed for a while. Meanwhile, many enterprises are using crowd source to collaboratively develop the...Many online platforms providing crowd with opportunities to participate in software development projects have been existed for a while. Meanwhile, many enterprises are using crowd source to collaboratively develop their software via these platforms in recent years. However, some software development projects in these platforms hardly attract users to join. Therefore, these project owners need a way to effectively predict the number of participants in their projects and accordingly well plan their software and project specifications, such as the program language and the size of the documentation, in order to attract more individuals to participant in the projects. Compared with the past prediction models, our proposed model can dynamically add the factors, such as number of participants in the initial stage of the project, within the project life cycle and make the adjustment to the prediction model. The proposed model was also verified by using cross validation method. The results show that: 1) The models with the factor “the number of user participation” is more accurate than the model without it. 2) The factors of crowd dimension are more influential on the prediction accuracy than those of software project and owner dimensions. It is suggested that the project owners not only just consider those factors of the software project dimension in the initial stage of the project life cycle but also those factors of crowd and interaction dimensions in the late stage to attract more participants in their projects.展开更多
This study was undertaken to examine which factors contributed to the correction of crowding in two patients who underwent nonextraction orthodontic treatment. A study model analysis was conducted to determine the eff...This study was undertaken to examine which factors contributed to the correction of crowding in two patients who underwent nonextraction orthodontic treatment. A study model analysis was conducted to determine the effects of the orthodontic treatment for crowding with high canines on crown angulation and dental arch width in two patients. The results showed that the crown angulation was significantly increased, indicating distal tipping in the maxillary dental arch. This tendency was most commonly observed in the premolars among the lateral teeth. With respect to the dental arch width, the largest change was evident in the first molar and first premolar regions in cases 1 and 2, respectively. On the basis of these results, up-righting of mesially tipped lateral teeth and expansion of narrow dental arches could prove to be the keys to the success of space regaining or correction of high canines and mild crowding.展开更多
Aircraft are profitable to their owners as long as they are in the air transporting passengers to their destinations;therefore it is vital to minimize as much as possible their preparation time on the ground.In this p...Aircraft are profitable to their owners as long as they are in the air transporting passengers to their destinations;therefore it is vital to minimize as much as possible their preparation time on the ground.In this paper we simulate different boarding strategies with the help of a model based on cellular automata parallel computational tool,attempting to find the most efficient way to deliver each passenger to her/his assigned seat.Two seat arrangements are used,a small one based on Airbus A320/ Boeing 737 and a larger one based on Airbus A380/ Boeing777-300.A wide variety of parameters,including time delay for luggage storing,the frequency by which the passengers enter the plane,different walking speeds of passengers depending on sex,age and height,and the possibility of walking past their seat,are simulated in order to achieve realistic results,as well as monitor their effects on boarding time.The simulation results indicate that the boarding time can be significantly reduced by the simple grouping and prioritizing of passengers.In accordance with previous papers and the examined strategies,the outside-in and reverse pyramid boarding methods outperform all the others for both the small and large airplane seat layout.In the latter,the examined strategies are introduced for first time in an analogous way to the initial small seat arrangement of Airbus A320/ Boeing737 aircraft family.Moreover,since in real world scenarios,the compliance of all the passengers to the suggested group division and boarding strategy cannot be guaranteed,further simulations were conducted.It is clear that as the number of passengers disregarding the priority of the boarding groups increases,the time needed for the boarding to complete tends towards that of the random boarding strategy,thus minimizing the possible advantages gained by the proposed boarding strategies.展开更多
A composite random variable is a product (or sum of products) of statistically distributed quantities. Such a variable can represent the solution to a multi-factor quantitative problem submitted to a large, diverse, i...A composite random variable is a product (or sum of products) of statistically distributed quantities. Such a variable can represent the solution to a multi-factor quantitative problem submitted to a large, diverse, independent, anonymous group of non-expert respondents (the “crowd”). The objective of this research is to examine the statistical distribution of solutions from a large crowd to a quantitative problem involving image analysis and object counting. Theoretical analysis by the author, covering a range of conditions and types of factor variables, predicts that composite random variables are distributed log-normally to an excellent approximation. If the factors in a problem are themselves distributed log-normally, then their product is rigorously log-normal. A crowdsourcing experiment devised by the author and implemented with the assistance of a BBC (British Broadcasting Corporation) television show, yielded a sample of approximately 2000 responses consistent with a log-normal distribution. The sample mean was within ~12% of the true count. However, a Monte Carlo simulation (MCS) of the experiment, employing either normal or log-normal random variables as factors to model the processes by which a crowd of 1 million might arrive at their estimates, resulted in a visually perfect log-normal distribution with a mean response within ~5% of the true count. The results of this research suggest that a well-modeled MCS, by simulating a sample of responses from a large, rational, and incentivized crowd, can provide a more accurate solution to a quantitative problem than might be attainable by direct sampling of a smaller crowd or an uninformed crowd, irrespective of size, that guesses randomly.展开更多
This paper presents a model for simulating crowd evacuation and investigates three widely recognized problems. For the space continuity problem, this paper presents two computation algorithms： one uses grid space to ...This paper presents a model for simulating crowd evacuation and investigates three widely recognized problems. For the space continuity problem, this paper presents two computation algorithms： one uses grid space to evaluate the coordinates of the obstacle＇s bounding box and the other employs the geometry rule to establish individual evacuation routes. For the problem of collision, avoidance, and excess among the individuals, this paper computes the generalized force and friction force and then modifies the direction of march to obtain a speed model based on the crowd density and real time speed. For the exit selection problem, this paper establishes a method of selecting the exits by combining the exit＇s crowd state with the individuals. Finally, a particle system is used to simulate the behavior of crowd evacuation and produces useful test results.展开更多
In recent years, modelling crowd and evacuation dynamics has become very important, with increasing huge numbers of people gathering around the world for many reasons and events. The fact that our global population gr...In recent years, modelling crowd and evacuation dynamics has become very important, with increasing huge numbers of people gathering around the world for many reasons and events. The fact that our global population grows dramatically every year and the current public transport systems are able to transport large amounts of people heightens the risk of crowd panic or crush. Pedestrian models are based on macroscopic or microscopic behaviour. In this paper, we are interested in developing models that can be used for evacuation control strategies. This model will be based on microscopic pedestrian simulation models, and its evolution and design requires a lot of information and data. The people stream will be simulated, based on mathematical models derived from empirical data about pedestrian flows. This model is developed from image data bases, so called empirical data, taken from a video camera or data obtained using human detectors. We consider the individuals as autonomous particles interacting through social and physical forces, which is an approach that has been used to simulate crowd behaviour. The target of this work is to describe a comprehensive approach to model a huge number of pedestrians and to simulate high density crowd behaviour in overcrowding places, e.g. sport, concert and pilgrimage places, and to assist engineering in the resolution of complicated problems through integrating a number of models from different research domains.展开更多
The geometrical effect is one of the most important factors in the kinetic modeling of crowd evacuation, besides the interaction between agents. More precisely, in the process of crowd evacuation, agents have the desi...The geometrical effect is one of the most important factors in the kinetic modeling of crowd evacuation, besides the interaction between agents. More precisely, in the process of crowd evacuation, agents have the desire to reach the exit, and the ability to avoid the walls or obstacles. In this study, we propose the evacuation vector field which incorporates the geometrical effects in crowd evacuation. This is useful for modeling the crowd evacuation from complex venue.展开更多
In this paper, we propose a novel method for anomalous crowd behaviour detection and localization with divergent centers in intelligent video sequence through multiple SVM (support vector machines) based appearance mo...In this paper, we propose a novel method for anomalous crowd behaviour detection and localization with divergent centers in intelligent video sequence through multiple SVM (support vector machines) based appearance model. In multi-dimension SVM crowd detection, many features are available to track the object robustly with three main features which include 1) identification of an object by gray scale value, 2) histogram of oriented gradients (HOG) and 3) local binary pattern (LBP). We propose two more powerful features namely gray level co-occurrence matrix (GLCM) and Gaber feature for more accurate and authenticate tracking result. To combine and process the corresponding SVMs obtained from each features, a new collaborative strategy is developed on the basis of the confidence distribution of the video samples which are weighted by entropy method. We have adopted subspace evolution strategy for reconstructing the image of the object by constructing an update model. Also, we determine reconstruction error from the samples and again automatically build an update model for the target which is tracked in the video sequences. Considering the movement of the targeted object, occlusion problem is considered and overcome by constructing a collaborative model from that of appearance model and update model. Also if update model is of discriminative model type, binary classification problem is taken into account and overcome by collaborative model. We run the multi-view SVM tracking method in real time with subspace evolution strategy to track and detect the moving objects in the crowded scene accurately. As shown in the result part, our method also overcomes the occlusion problem that occurs frequently while objects under rotation and illumination change due to different environmental conditions.展开更多
基金the National Natural Science Foundation of China (50478057)the Key Technologies Research and Development Program of Hubei Provice (2004AA30B05)
文摘This paper reports observations of passenger flow in the Wuchang railway station in Wuhan, China during the Chinese Traditional Spring Festival in 2006. The data collected are used to verify a crowd dynamics model previously developed. The crowd dynamics model is based on simulating the global movement of each individual under the influence of the surrounding crowd, and the good agreement between the predictions and observations validates the prediction model. The crowd dynamics model suggests that the crowd movement speed is dominated by two factors： the front-back inter-person effect, and the pedestrian＇s self-motive. The first effect gives logarithmic relationship between the crowd speed and crowd density. The second factor depends on the individual motive driven with which people try to divorce themselves from the control of the crowd movement. The prediction model are helpful to guide the design of public traffic systems for effective crowd dispersal.
基金supported by National Natural Science Foundation of China(61374055)Natural Science Foundation of Jiangsu Province(BK20131381)+4 种基金China Postdoctoral Science Foundation Funded Project(2013M541663)Jiangsu Planned Projects for Postdoctoral Research Funds(1202015C)Scientific Research Foundation for the Returned Overseas Chinese ScholarsState Education Ministry(BJ213022)Scientific Research Foundation of Nanjing University of Posts and Telecommunications(NY214075,XJKY14004)
文摘Despite growing research for residential crowding effects on housing market and public health perspectives, relatively little attention has been paid to explore and model spatial patterns of residential crowding over space. This paper focuses upon analyzing the spatial relationships between residential crowding and socio-demographic variables in Alexandria neighborhoods, Egypt. Global and local geo-statistical techniques were employed within GIS-based platform to identify spatial?variations of residential crowding determinates. The global ordinary least squares (OLS) model?assumes homogeneity of relationships between response variable and explanatory variables?across the study area. Consequently, it fails to account for heterogeneity of spatial relationships. Local model known as a geographically weighted regression (GWR) was also employed using the same?response variable and explanatory variables to capture spatial non-stationary of residential?crowding. A comparison of the outputs of both models indicated that OLS explained 74 percent of?residential crowding variations while GWR model explained 79 percent. The GWR improvedstrength of the model and provided a better goodness of fit than OLS. In addition, the findings of this analysis revealed that residential crowding was significantly associated with different structural measures particularly social characteristics of household such as higher education and illiteracy. Similarly, population size of neighborhood and number of dwelling rooms were found to have direct impacts on residential crowding rate. The spatial relationship of these measures distinctly varies over the study area.
文摘Many online platforms providing crowd with opportunities to participate in software development projects have been existed for a while. Meanwhile, many enterprises are using crowd source to collaboratively develop their software via these platforms in recent years. However, some software development projects in these platforms hardly attract users to join. Therefore, these project owners need a way to effectively predict the number of participants in their projects and accordingly well plan their software and project specifications, such as the program language and the size of the documentation, in order to attract more individuals to participant in the projects. Compared with the past prediction models, our proposed model can dynamically add the factors, such as number of participants in the initial stage of the project, within the project life cycle and make the adjustment to the prediction model. The proposed model was also verified by using cross validation method. The results show that: 1) The models with the factor “the number of user participation” is more accurate than the model without it. 2) The factors of crowd dimension are more influential on the prediction accuracy than those of software project and owner dimensions. It is suggested that the project owners not only just consider those factors of the software project dimension in the initial stage of the project life cycle but also those factors of crowd and interaction dimensions in the late stage to attract more participants in their projects.
文摘This study was undertaken to examine which factors contributed to the correction of crowding in two patients who underwent nonextraction orthodontic treatment. A study model analysis was conducted to determine the effects of the orthodontic treatment for crowding with high canines on crown angulation and dental arch width in two patients. The results showed that the crown angulation was significantly increased, indicating distal tipping in the maxillary dental arch. This tendency was most commonly observed in the premolars among the lateral teeth. With respect to the dental arch width, the largest change was evident in the first molar and first premolar regions in cases 1 and 2, respectively. On the basis of these results, up-righting of mesially tipped lateral teeth and expansion of narrow dental arches could prove to be the keys to the success of space regaining or correction of high canines and mild crowding.
文摘Aircraft are profitable to their owners as long as they are in the air transporting passengers to their destinations;therefore it is vital to minimize as much as possible their preparation time on the ground.In this paper we simulate different boarding strategies with the help of a model based on cellular automata parallel computational tool,attempting to find the most efficient way to deliver each passenger to her/his assigned seat.Two seat arrangements are used,a small one based on Airbus A320/ Boeing 737 and a larger one based on Airbus A380/ Boeing777-300.A wide variety of parameters,including time delay for luggage storing,the frequency by which the passengers enter the plane,different walking speeds of passengers depending on sex,age and height,and the possibility of walking past their seat,are simulated in order to achieve realistic results,as well as monitor their effects on boarding time.The simulation results indicate that the boarding time can be significantly reduced by the simple grouping and prioritizing of passengers.In accordance with previous papers and the examined strategies,the outside-in and reverse pyramid boarding methods outperform all the others for both the small and large airplane seat layout.In the latter,the examined strategies are introduced for first time in an analogous way to the initial small seat arrangement of Airbus A320/ Boeing737 aircraft family.Moreover,since in real world scenarios,the compliance of all the passengers to the suggested group division and boarding strategy cannot be guaranteed,further simulations were conducted.It is clear that as the number of passengers disregarding the priority of the boarding groups increases,the time needed for the boarding to complete tends towards that of the random boarding strategy,thus minimizing the possible advantages gained by the proposed boarding strategies.
文摘A composite random variable is a product (or sum of products) of statistically distributed quantities. Such a variable can represent the solution to a multi-factor quantitative problem submitted to a large, diverse, independent, anonymous group of non-expert respondents (the “crowd”). The objective of this research is to examine the statistical distribution of solutions from a large crowd to a quantitative problem involving image analysis and object counting. Theoretical analysis by the author, covering a range of conditions and types of factor variables, predicts that composite random variables are distributed log-normally to an excellent approximation. If the factors in a problem are themselves distributed log-normally, then their product is rigorously log-normal. A crowdsourcing experiment devised by the author and implemented with the assistance of a BBC (British Broadcasting Corporation) television show, yielded a sample of approximately 2000 responses consistent with a log-normal distribution. The sample mean was within ~12% of the true count. However, a Monte Carlo simulation (MCS) of the experiment, employing either normal or log-normal random variables as factors to model the processes by which a crowd of 1 million might arrive at their estimates, resulted in a visually perfect log-normal distribution with a mean response within ~5% of the true count. The results of this research suggest that a well-modeled MCS, by simulating a sample of responses from a large, rational, and incentivized crowd, can provide a more accurate solution to a quantitative problem than might be attainable by direct sampling of a smaller crowd or an uninformed crowd, irrespective of size, that guesses randomly.
基金supported by Shanghai Science and Technology Committee (No. 08515810200)Jiangsu Province Development Foundation (No. BS2007048)
文摘This paper presents a model for simulating crowd evacuation and investigates three widely recognized problems. For the space continuity problem, this paper presents two computation algorithms： one uses grid space to evaluate the coordinates of the obstacle＇s bounding box and the other employs the geometry rule to establish individual evacuation routes. For the problem of collision, avoidance, and excess among the individuals, this paper computes the generalized force and friction force and then modifies the direction of march to obtain a speed model based on the crowd density and real time speed. For the exit selection problem, this paper establishes a method of selecting the exits by combining the exit＇s crowd state with the individuals. Finally, a particle system is used to simulate the behavior of crowd evacuation and produces useful test results.
文摘In recent years, modelling crowd and evacuation dynamics has become very important, with increasing huge numbers of people gathering around the world for many reasons and events. The fact that our global population grows dramatically every year and the current public transport systems are able to transport large amounts of people heightens the risk of crowd panic or crush. Pedestrian models are based on macroscopic or microscopic behaviour. In this paper, we are interested in developing models that can be used for evacuation control strategies. This model will be based on microscopic pedestrian simulation models, and its evolution and design requires a lot of information and data. The people stream will be simulated, based on mathematical models derived from empirical data about pedestrian flows. This model is developed from image data bases, so called empirical data, taken from a video camera or data obtained using human detectors. We consider the individuals as autonomous particles interacting through social and physical forces, which is an approach that has been used to simulate crowd behaviour. The target of this work is to describe a comprehensive approach to model a huge number of pedestrians and to simulate high density crowd behaviour in overcrowding places, e.g. sport, concert and pilgrimage places, and to assist engineering in the resolution of complicated problems through integrating a number of models from different research domains.
文摘The geometrical effect is one of the most important factors in the kinetic modeling of crowd evacuation, besides the interaction between agents. More precisely, in the process of crowd evacuation, agents have the desire to reach the exit, and the ability to avoid the walls or obstacles. In this study, we propose the evacuation vector field which incorporates the geometrical effects in crowd evacuation. This is useful for modeling the crowd evacuation from complex venue.
文摘In this paper, we propose a novel method for anomalous crowd behaviour detection and localization with divergent centers in intelligent video sequence through multiple SVM (support vector machines) based appearance model. In multi-dimension SVM crowd detection, many features are available to track the object robustly with three main features which include 1) identification of an object by gray scale value, 2) histogram of oriented gradients (HOG) and 3) local binary pattern (LBP). We propose two more powerful features namely gray level co-occurrence matrix (GLCM) and Gaber feature for more accurate and authenticate tracking result. To combine and process the corresponding SVMs obtained from each features, a new collaborative strategy is developed on the basis of the confidence distribution of the video samples which are weighted by entropy method. We have adopted subspace evolution strategy for reconstructing the image of the object by constructing an update model. Also, we determine reconstruction error from the samples and again automatically build an update model for the target which is tracked in the video sequences. Considering the movement of the targeted object, occlusion problem is considered and overcome by constructing a collaborative model from that of appearance model and update model. Also if update model is of discriminative model type, binary classification problem is taken into account and overcome by collaborative model. We run the multi-view SVM tracking method in real time with subspace evolution strategy to track and detect the moving objects in the crowded scene accurately. As shown in the result part, our method also overcomes the occlusion problem that occurs frequently while objects under rotation and illumination change due to different environmental conditions.
