MCENET: Multi-Context Encoder Network for Homogeneous Agent Trajectory Prediction in Mixed Traffic

Hao Cheng, Wentong Liao*, Michael Ying Yang, Monika Sester, Bodo Rosenhahn

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)
3 Downloads (Pure)

Abstract

Trajectory prediction in urban mixed-traffic zones (a.k. a. shared spaces) is critical for many intelligent transportation systems, such as intent detection for autonomous driving. However, there are many challenges to predict the trajectories of heterogeneous road agents (pedestrians, cyclists and vehicles) at a microscopical level. For example, an agent might be able to choose multiple plausible paths in complex interactions with other agents in varying environments. To this end, we propose an approach named Multi-Context Encoder Network (MCENET) that is trained by encoding both past and future scene context, interaction context and motion information to capture the patterns and variations of the future trajectories using a set of stochastic latent variables. In inference time, we combine the past context and motion information of the target agent with samplings of the latent variables to predict multiple realistic trajectories in the future. Through experiments on several datasets of varying scenes, our method outperforms some of the recent state-of-the-art methods for mixed traffic trajectory prediction by a large margin and more robust in a very challenging environment. The impact of each context is justified via ablation studies.

Original languageEnglish
Title of host publication2020 IEEE 23rd International Conference on Intelligent Transportation Systems
Subtitle of host publication ITSC 2020
PublisherIEEE
Pages1-8
Number of pages8
ISBN (Electronic)9781728141497
ISBN (Print)9781728141503
DOIs
Publication statusPublished - 20 Sep 2020
Event23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020 - Virtual Conference, Greece
Duration: 20 Sep 202023 Sep 2020
Conference number: 23

Publication series

NameInternational Conference on Intelligent Transportation Systems
PublisherIEEE

Conference

Conference23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020
Abbreviated titleITSC 2020
CountryGreece
CityVirtual Conference
Period20/09/2023/09/20

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