Trajectory Prediction in Heterogeneous Environment via Attended Ecology Embedding

Wei Cheng Lai, Zi Xiang Xia, Hao Siang Lin, Lien Feng Hsu, Hong Han Shuai, I. Hong Jhuo, Wen Huang Cheng

研究成果: Conference contribution同行評審

19 引文 斯高帕斯(Scopus)

摘要

Trajectory prediction is a highly desirable feature for safe navigation or autonomous vehicle in complex traffic. In this paper, we consider the practical environment of predicting trajectory in the heterogeneous traffic ecology. The proposed method has various applications in trajectory prediction problems and also in applied fields beyond tracking. One challenge stands out of the trajectory prediction-heterogeneous environment. Particularly, many factors should be considered in the environments, i.e., multiple types of road-agents, social interactions and terrains. The information is complicated and large that may result in inaccurate trajectory prediction. We propose two social and visual enforced attention modules to circumvent the problem and a variant of an Info-GAN structure to predict the trajectory with multi-modal behaviors. Experimental results show that the proposed method significantly outperforms state-of-the-art methods in both heterogeneous and homogeneous real environments.

原文English
主出版物標題MM 2020 - Proceedings of the 28th ACM International Conference on Multimedia
發行者Association for Computing Machinery, Inc
頁面202-210
頁數9
ISBN(電子)9781450379885
DOIs
出版狀態Published - 12 10月 2020
事件28th ACM International Conference on Multimedia, MM 2020 - Virtual, Online, United States
持續時間: 12 10月 202016 10月 2020

出版系列

名字MM 2020 - Proceedings of the 28th ACM International Conference on Multimedia

Conference

Conference28th ACM International Conference on Multimedia, MM 2020
國家/地區United States
城市Virtual, Online
期間12/10/2016/10/20

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