TY - GEN
T1 - Traffic spatiotemporal data model on urban road network under adverse weather conditions
AU - Zhang, Xi Qiao
AU - Yang, Long Hai
AU - An, Shi
PY - 2012
Y1 - 2012
N2 - 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. First, the intrinsic law of road traffic network is depicted and the traffic supply-demand influential factors under adverse weather conditions are analyzed. After that, 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 spatiotemporal data modeling on urban traffic network under adverse weather conditions was got. In the end, example 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 solid foundation for studying urban traffic problems vividly and dynamically.
AB - 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. First, the intrinsic law of road traffic network is depicted and the traffic supply-demand influential factors under adverse weather conditions are analyzed. After that, 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 spatiotemporal data modeling on urban traffic network under adverse weather conditions was got. In the end, example 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 solid foundation for studying urban traffic problems vividly and dynamically.
KW - Adverse weather
KW - Spatiotemporal data model
KW - Traffic network
UR - https://www.scopus.com/pages/publications/84862936247
U2 - 10.1007/978-94-007-2169-2_99
DO - 10.1007/978-94-007-2169-2_99
M3 - 会议稿件
AN - SCOPUS:84862936247
SN - 9789400721685
T3 - Lecture Notes in Electrical Engineering
SP - 833
EP - 841
BT - Green Communications and Networks - Proceedings of the International Conference on Green Communications and Networks, GCN 2011
T2 - International Conference on Green Communications and Networks, GCN 2011
Y2 - 15 July 2011 through 17 July 2011
ER -