Comparing dead reckoning algorithms for distributed car simulations
Dead reckoning is an important technique used in distributed virtual environments (DVEs) to mitigate the bandwidth consumption of frequent state updates and the negative effects of network latency. This paper proposes a novel dead reckoning approach for common DVE applications such as multiplayer on...
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sg-ntu-dr.10356-884762020-11-01T04:43:49Z Comparing dead reckoning algorithms for distributed car simulations Chen, Youfu Liu, Elvis S. Interdisciplinary Graduate School (IGS) Proceedings of the 2018 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation Multi-plAtform Game Innovation Centre Dead Reckoning Distributed Virtual Environments Engineering::Computer science and engineering Dead reckoning is an important technique used in distributed virtual environments (DVEs) to mitigate the bandwidth consumption of frequent state updates and the negative effects of network latency. This paper proposes a novel dead reckoning approach for common DVE applications such as multiplayer online games. Unlike traditional dead reckoning approaches that estimate the movements of remote entities with pure kinematic models, the new approach performs extrapolations with the considerations of environmental factors and human behaviours. We have performed experiments, based on a distributed car simulator, to compare the the new approach with representative existing dead reckoning approaches. The results show that the new approach gives more accurate predictions with an acceptable overhead. MOE (Min. of Education, S’pore) Accepted version 2019-09-02T06:51:01Z 2019-12-06T17:04:08Z 2019-09-02T06:51:01Z 2019-12-06T17:04:08Z 2018 Conference Paper Chen, Y., & Liu, E. S. (2018). Comparing dead reckoning algorithms for distributed car simulations. Proceedings of the 2018 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation. doi:10.1145/3200921.3200939 https://hdl.handle.net/10356/88476 http://hdl.handle.net/10220/49837 10.1145/3200921.3200939 en © 2018 Association for Computing Machinery (ACM). All rights reserved. This paper was published in Proceedings of the 2018 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation and is made available with permission of Association for Computing Machinery (ACM). 7 p. application/pdf |
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Dead Reckoning Distributed Virtual Environments Engineering::Computer science and engineering |
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Dead Reckoning Distributed Virtual Environments Engineering::Computer science and engineering Chen, Youfu Liu, Elvis S. Comparing dead reckoning algorithms for distributed car simulations |
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Dead reckoning is an important technique used in distributed virtual environments (DVEs) to mitigate the bandwidth consumption of frequent state updates and the negative effects of network latency. This paper proposes a novel dead reckoning approach for common DVE applications such as multiplayer online games. Unlike traditional dead reckoning approaches that estimate the movements of remote entities with pure kinematic models, the new approach performs extrapolations with the considerations of environmental factors and human behaviours. We have performed experiments, based on a distributed car simulator, to compare the the new approach with representative existing dead reckoning approaches. The results show that the new approach gives more accurate predictions with an acceptable overhead. |
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Interdisciplinary Graduate School (IGS) |
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Interdisciplinary Graduate School (IGS) Chen, Youfu Liu, Elvis S. |
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Conference or Workshop Item |
author |
Chen, Youfu Liu, Elvis S. |
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Chen, Youfu |
title |
Comparing dead reckoning algorithms for distributed car simulations |
title_short |
Comparing dead reckoning algorithms for distributed car simulations |
title_full |
Comparing dead reckoning algorithms for distributed car simulations |
title_fullStr |
Comparing dead reckoning algorithms for distributed car simulations |
title_full_unstemmed |
Comparing dead reckoning algorithms for distributed car simulations |
title_sort |
comparing dead reckoning algorithms for distributed car simulations |
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2019 |
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https://hdl.handle.net/10356/88476 http://hdl.handle.net/10220/49837 |
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1683494160128016384 |