Crowd flows prediction is an important problem of urban computing whose goal is to predict the number of incoming and outgoing people of regions in the future.In practice,emergency applications often require less trai...Crowd flows prediction is an important problem of urban computing whose goal is to predict the number of incoming and outgoing people of regions in the future.In practice,emergency applications often require less training time.However,there is a little work on how to obtain good prediction performance with less training time.In this paper,we propose a simplified deep residual network for our problem.By using the simplified deep residual network,we can obtain not only less training time but also competitive prediction performance compared with the existing similar method.Moreover,we adopt the spatio-temporal attention mechanism to further improve the simplified deep residual network with reasonable additional time cost.Based on the real datasets,we construct a series of experiments compared with the existing methods.The experimental results confirm the efficiency of our proposed methods.展开更多
To relieve traffic congestion in urban rail transit stations,a new identification method of crowded passenger flow based on automatic fare collection data is proposed.First,passenger travel characteristics are analyze...To relieve traffic congestion in urban rail transit stations,a new identification method of crowded passenger flow based on automatic fare collection data is proposed.First,passenger travel characteristics are analyzed by observing the temporal distribution of inflow passengers each hour and the spatial distribution concerning cross-section passenger flow.Secondly,the identification method of crowded passenger flow is proposed to calculate the threshold via the probability density function fitted by Matlab and classify the early-warning situation based on the threshold obtained.Finally,a case study of Xinjiekou station is conducted to prove the validity and practicability of the proposed method.Compared to the traditional methods,the proposed comprehensive method can remove defects such as efficiency and delay.Furthermore,the proposed method is suitable for other rail transit companies equipped with automatic fare collection systems.展开更多
Urban development has progressed with economic growth in various parts of Japan.However,there are concerns for the future with respect to severe population decline,aging population,and population concentration in metr...Urban development has progressed with economic growth in various parts of Japan.However,there are concerns for the future with respect to severe population decline,aging population,and population concentration in metropolitan areas.Therefore,it is required for effective urban development in localities for sustainability.One of the practical measures is to focus on pedestrians’activity in the area.It brings revitalizing the local economy,enhancing the region's attractiveness,and bringing about fiscal consolidation.Thus,it is required to understand walking characteristics based on the actual pedestrian activity in the walking space.However,a method for grasping pedestrian activity,including pedestrians'exploratory behavior such as free-purpose behavior,rambling activity in a narrow area has not been established.The study proposes a survey proportional distribution origin-destination survey method focused on the proportion of pedestrians’route selection and the distribution of pedestrians at the time in the area,and evaluation method for urban space using PdOD method.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
基金This work was supported by the National Nature Science Foundation of China(NSFC Grant Nos.61572537,U1501252).
文摘Crowd flows prediction is an important problem of urban computing whose goal is to predict the number of incoming and outgoing people of regions in the future.In practice,emergency applications often require less training time.However,there is a little work on how to obtain good prediction performance with less training time.In this paper,we propose a simplified deep residual network for our problem.By using the simplified deep residual network,we can obtain not only less training time but also competitive prediction performance compared with the existing similar method.Moreover,we adopt the spatio-temporal attention mechanism to further improve the simplified deep residual network with reasonable additional time cost.Based on the real datasets,we construct a series of experiments compared with the existing methods.The experimental results confirm the efficiency of our proposed methods.
基金The National Key Research and Development Program of China(No.2016YFE0206800)
文摘To relieve traffic congestion in urban rail transit stations,a new identification method of crowded passenger flow based on automatic fare collection data is proposed.First,passenger travel characteristics are analyzed by observing the temporal distribution of inflow passengers each hour and the spatial distribution concerning cross-section passenger flow.Secondly,the identification method of crowded passenger flow is proposed to calculate the threshold via the probability density function fitted by Matlab and classify the early-warning situation based on the threshold obtained.Finally,a case study of Xinjiekou station is conducted to prove the validity and practicability of the proposed method.Compared to the traditional methods,the proposed comprehensive method can remove defects such as efficiency and delay.Furthermore,the proposed method is suitable for other rail transit companies equipped with automatic fare collection systems.
文摘Urban development has progressed with economic growth in various parts of Japan.However,there are concerns for the future with respect to severe population decline,aging population,and population concentration in metropolitan areas.Therefore,it is required for effective urban development in localities for sustainability.One of the practical measures is to focus on pedestrians’activity in the area.It brings revitalizing the local economy,enhancing the region's attractiveness,and bringing about fiscal consolidation.Thus,it is required to understand walking characteristics based on the actual pedestrian activity in the walking space.However,a method for grasping pedestrian activity,including pedestrians'exploratory behavior such as free-purpose behavior,rambling activity in a narrow area has not been established.The study proposes a survey proportional distribution origin-destination survey method focused on the proportion of pedestrians’route selection and the distribution of pedestrians at the time in the area,and evaluation method for urban space using PdOD method.
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.
基金National Science and Technology Major Project(No.J2019-III-0005-0048)Ministry of Science and Technology of China(Nos.2021YFA0716200/2022YFB4003900)+2 种基金Natural Science Foundation of China(Nos.51976216,51888103,52161145105/M-0139)Beijing Municipal Natural Science Foundation(No.JQ20017)Chinese Academy of Sciences(Nos.YJKYYQ20210006,GJTD-2020-07),CAS-TWAS Scholarships。
