A Multi-dimension Weighted Graph-Based Path Planning with Avoiding Hotspots

被引:2
|
作者
Jiang, Shuo [1 ,3 ]
Feng, Zhiyong [1 ,3 ]
Zhang, Xiaowang [2 ,3 ]
Wang, Xin [2 ,3 ]
Rao, Guozheng [2 ,3 ]
机构
[1] Tianjin Univ, Sch Comp Software, Tianjin 300350, Peoples R China
[2] Tianjin Univ, Sch Comp Sci & Technol, Tianjin 300350, Peoples R China
[3] Tianjin Key Lab Cognit Comp & Applicat, Tianjin 300350, Peoples R China
基金
中国国家自然科学基金;
关键词
Path planning; Avoiding hotspots; Multi-dimension weighted graph; Shortest path problem; SEMISTRUCTURED DATABASES; QUERIES;
D O I
10.1007/978-981-10-3168-7_2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the development of industrialization rapidly, vehicles have become an important part of people's life. However, transportation system is becoming more and more complicated. The core problem of the complicated transportation system is how to avoid hotspots. In this paper, we present a graph model based on a multi-dimension weighted graph for path planning with avoiding hotspots. Firstly, we extend one-dimension weighted graphs to multi-dimension weighted graphs where multi-dimension weights are used to characterize more features of transportation. Secondly, we develop a framework equipped with many aggregate functions for transforming multi-dimension weighted graphs into one-dimension weighted graphs in order to converse the path planning of multi-dimension weighted graphs into the shortest path problem of one-dimension weighted graphs. Finally, we implement our proposed framework and evaluate our system in some necessary practical examples. The experiment shows that our approach can provide "optimal" paths under the consideration of avoiding hotspots.
引用
收藏
页码:15 / 26
页数:12
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