Visual Analysis Method for Traffic Trajectory with Dynamic Topic Movement Patterns Based on the Improved Markov Decision Process

Author:

Chen Huarong1ORCID,Wu Yadong2,Tang Huaquan3,Lei Jing3,Wang Guijuan1,Zhao Weixin4,Liao Jing1,Wang Fupan1,Wang Zhong1

Affiliation:

1. School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621010, China

2. School of Computer Science and Engineering, Sichuan University of Science & Engineering, Yibin 644007, China

3. Technical Center, Mianyang Xinchen Engine Co., Ltd., Mianyang 621000, China

4. College of Computer Science, Sichuan University, Chengdu 610065, China

Abstract

The visual analysis of trajectory topics is helpful for mining potential trajectory patterns, but the traditional visual analysis method ignores the evolution of the temporal coherence of the topic. In this paper, a novel visual analysis method for dynamic topic analysis of traffic trajectory is proposed, which is used to explore and analyze the traffic trajectory topic and evolution. Firstly, the spatial information is integrated into trajectory words, calculating the dynamic trajectory topic model based on dynamic analysis modeling and, consequently, correlating the evolution of the trajectory topic between adjacent time slices. Secondly, in the trajectory topic, a representative trajectory sequence is generated to overcome the problem of the trajectory topic model not considering the word order, based on the improved Markov Decision Process. Subsequently, a set of meaningful visual codes is designed to analyze the trajectory topic and its evolution through the parallel window visual model from a spatial-temporal perspective. Finally, a case evaluation shows that the proposed method is effective in analyzing potential trajectory movement patterns.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Reference32 articles.

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