Traffic3D: A new traffic simulation paradigm

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The field of Deep Reinforcement Learning has evolved significantly over the last few years. However, an important and not yet fully-attained goal is to produce intelligent agents which can be successfully taken out of the laboratory and employed in the real-world. Intelligent agents that are successfully deployable in real-world settings require substantial prior exposure to their intended environments. When this is not practical or possible, the agents benefit from being trained and tested on powerful test-beds, effectively replicating the real-world. To achieve traffic management at an unprecedented level of efficiency, in this work, we demonstrate a significantly richer new traffic simulation environment; Traffic3D, a platform to effectively simulate and evaluate a variety of 3D road traffic scenarios, closely mimicking real-world traffic characteristics, including faithful simulation of individual vehicle behavior, precise physics of movement and photo-realism. In addition to deep reinforcement learning, Traffic3D also facilitates research in several other domains such as imitation learning, learning by interaction, visual question answering, object detection and segmentation, unsupervised representation learning and procedural generation.

Original languageEnglish
Title of host publication18th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2019
PublisherACM
Pages2354-2356
Number of pages3
ISBN (Electronic)9781510892002
ISBN (Print)978-1-4503-6309-9
Publication statusPublished - 8 May 2019
Event18th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2019 - Montreal, Canada
Duration: 13 May 201917 May 2019

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume4
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference18th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2019
CountryCanada
CityMontreal
Period13/05/1917/05/19

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Bibliographical note

© 2019 International Foundation for Autonomous Agents and
Multiagent Systems (www.ifaamas.org).

Keywords

  • Intelligent transportation systems
  • Virtual reality 3d-traffic simulator

Cite this

Garg, D., Chli, M., & Vogiatzis, G. (2019). Traffic3D: A new traffic simulation paradigm. In 18th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2019 (pp. 2354-2356). (Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS; Vol. 4). ACM.