Exploring dynamic context for multi-path trajectory prediction

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

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

19 Citations (Scopus)
37 Downloads (Pure)


To accurately predict future positions of different agents in traffic scenarios is crucial for safely deploying intelligent autonomous systems in the real-world environment. However, it remains a challenge due to the behavior of a target agent being affected by other agents dynamically and there being more than one socially possible paths the agent could take. In this paper, we propose a novel framework, named Dynamic Context Encoder Network (DCENet). In our framework, first, the spatial context between agents is explored by using self-attention architectures. Then, the two-stream encoders are trained to learn temporal context between steps by taking the respective observed trajectories and the extracted dynamic spatial context as input. The spatial-temporal context is encoded into a latent space using a Conditional Variational Auto-Encoder (CVAE) module. Finally, a set of future trajectories for each agent is predicted conditioned on the learned spatial-temporal context by sampling from the latent space, repeatedly. DCENet is evaluated on one of the most popular challenging benchmarks for trajectory forecasting Trajnet and reports a new state-of-the-art performance. It also demonstrates superior performance evaluated on the benchmark inD for mixed traffic at intersections. A series of ablation studies is conducted to validate the effectiveness of each proposed module. Our code is available at https://github.com/wtliao/DCENet.
Original languageEnglish
Title of host publication2021 IEEE International Conference on Robotics and Automation (ICRA)
Place of PublicationCham
Number of pages7
ISBN (Electronic)978-1-7281-9077-8
ISBN (Print)978-1-7281-9078-5
Publication statusPublished - 18 Oct 2021
EventIEEE International Conference on Robotics and Automation, ICRA 2021 - Xi'an, China, Virtual Event, China
Duration: 30 May 20215 Jun 2021


ConferenceIEEE International Conference on Robotics and Automation, ICRA 2021
Abbreviated titleICRA 2021
CityVirtual Event


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