Movement Simulation and Analysis29/12/2005 |
| Modelling Railway Passenger Activity in Tokyo |
| In a world where everyone is constantly on the move, simulation and analysis of characteristics of the movement of objects is increasingly important, not only for behaviour forecast and policy/decision-making but also for monitoring and accident prevention. The authors developed key techniques for modelling large-scale moving objects and applied the system in movement simulation and pattern analysis of railway station passengers in Tokyo. |
| Rong Xie and Ryosuke Shibasaki, The University of Tokyo, Japan |
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Technology push and application pull are leading to increasing study of simulation and analysis of the spatial and temporal behaviour of large-scale moving objects such as pedestrians, cars, buses and trains. The technology push results mainly from advances in positioning systems, in particular GPS, and wireless communication. These rapidly developing technologies enable continuous tracking and recording positions of moving objects. The application pull comes from demands for services which require (1) information on the flow density of potential visitors, (2) tracking and visualising the actual movement of objects and (3) behaviour understanding and forecast, and policy formulation.
Spatio-temporal Model Space and time are two properties inherent to any moving object. We use an object-based approach to model such moving objects and their behaviour. Each object encapsulates its spatial dimension, temporal dimension, attribute characteristic, corresponding behaviour operation and interaction with the environment. Our spatio-temporal data model, includes:
Movement Query On the basis of the above conceptual spatio-temporal data model, various application queries have been developed to capture movement characteristics. Specialised spatio-temporal operations and efficient indexing have also been developed for fast access. The index structure is based on an improved R-Tree mechanism called ST R-Tree, which considers time as another spatial dimension in 2D and uses an integrated 3D spatio-temporal index. Further, the ST R-Tree improves the efficiency of R-Tree by indexing line segments as part of trajectories, enabling special queries such as determination of the trajectory of a moving object. Our system handles four basic types of query: spatial, temporal, spatio-temporal and object-related. Spatial queries, which are formulated in terms of spatial operations, return spatial attributes; since no temporal information is used, the query covers the whole time axis. Temporal queries, which are formulated in terms of temporal operations, deal with temporal relationships between objects and with the valid time of an object; since no spatial information is used, the query covers the whole space. Spatio-temporal queries return spatial components or values at a specific time, or valid time of spatio-temporal relationships. Object queries are a special spatio-temporal type of query, which extracts information on object trajectory by selecting a spatial and temporal range. Movement Simulation Movement can be represented as a spatio-temporal relationship among moving objects. A movement-simulation model is applied for representing spatial and temporal characteristics of moving objects and for analysing the patterns of motion of a moving object, which includes four components:
Case Studies We applied the approach to movement simulation and pattern analysis of 10,000 passengers of East Japan Railway Company in JR railway stations in Tokyo. The railway network under consideration here is located within a radius of about 70km2 of Tokyo and comprises 32 major railway lines. Information about the rail travel of each passenger was recorded by questionnaire. Application queries on passenger movement included the number of movements in one day (see for an example Figure 3), the number of movements within a specific station and movements on a selected railway line. Further Reading
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| Biography of the Author(s) Both authors are with the Centre for Spatial Information Science, The University of Tokyo, Japan. Dr Rong Xie received a PhD degree in 2003 from The University of Tokyo, where she is currently a post-doctoral researcher. Her research interest covers moving-objects data modelling and simulation, spatio-temporal analysis and database, mobile agent and distributed computing. Prof. Ryosuke Shibasaki received a PhD degree from The University of Tokyo, Japan in 1987. His research interest covers 3D-data acquisition for GIS, conceptual modelling for spatial objects, and agent-based microsimulation in a GIS environment. |
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