Spatiotemporal Data Model on Urban Road Traffic Network under Adverse Weather Conditions

With the development of science and technology, the Geographic Information System (GIS) which has the function of storage, management, analysis and expression of Spatiotemporal data, has become a powerful tool in solving urban traffic problems, and the spatiotemporal data modeling on urban traffic network has become the important foundation of the new theoretic research generation on GIS-T. Based on analysis of the applicability of current international spatiotemporal data models and with considering the characteristics of urban road traffic network under adverse weather conditions, the event-based object-oriented spatiotemporal data model is brought forward. Firstly, the intrinsic law of road traffic network is depicted and the traffic supply-demand influential factors under adverse weather conditions are analyzed. Secondly, the definitions of ‘class' and ‘objects' are given based on the above analysis, and Unified Modeling Language (UML) are applied to expressing the traffic attributes and relations. The influential factors under adverse conditions are taken as ‘event' in modeling road traffic network. Finally, analysis shows that this model provides a much more clear and flexible mode for forecasting, management and decision-making in traffic supply-demand researches. This study also provides a new way to vividly study urban traffic problems.