Exploiting Spatial Abstraction in Predictive Analytics of Vehicle Traffic

被引:12
作者
Andrienko, Natalia [1 ,2 ]
Andrienko, Gennady [1 ,2 ]
Rinzivillo, Salvatore [3 ]
机构
[1] Fraunhofer Inst IAIS, D-53757 Schloss Birlinghoven, Sankt Augustin, Germany
[2] City Univ London, Dept Comp Sci, London EC1V OHB, England
[3] CNR, Ist Sci & Tecnol Informaz, I-56124 Pisa, Italy
关键词
visual analytics; mobility; traffic modeling; traffic simulation; CROSS-SCALE ANALYSIS; DYNAMICS;
D O I
10.3390/ijgi4020591
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
By applying visual analytics techniques to vehicle traffic data, we found a way to visualize and study the relationships between the traffic intensity and movement speed on links of a spatially abstracted transportation network. We observed that the traffic intensities and speeds in an abstracted network are interrelated in the same way as they are in a detailed street network at the level of street segments. We developed interactive visual interfaces that support representing these interdependencies by mathematical models. To test the possibility of utilizing them for performing traffic simulations on the basis of abstracted transportation networks, we devised a prototypical simulation algorithm employing these dependency models. The algorithm is embedded in an interactive visual environment for defining traffic scenarios, running simulations, and exploring their results. Our research demonstrates a principal possibility of performing traffic simulations on the basis of spatially abstracted transportation networks using dependency models derived from real traffic data. This possibility needs to be comprehensively investigated and tested in collaboration with transportation domain specialists.
引用
收藏
页码:591 / 606
页数:16
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