• DOI:10.1109/ITSC.2019.8917516
Corpus ID: 195584221

Modeling Multi-Vehicle Interaction Scenarios Using Gaussian Random Field

@article{Guo2019ModelingMI,
  title={Modeling Multi-Vehicle Interaction Scenarios Using Gaussian Random Field},
  author={Yaohui Guo and Vinay Varma Kalidindi and Mansur Arief and W. Wang and Jiacheng Zhu and H. Peng and Ding Zhao},
  journal={2019 IEEE Intelligent Transportation Systems Conference (ITSC)},
  year={2019},
  pages={3974-3980}
}

Yaohui Guo, Vinay Varma Kalidindi, +4 authors Ding Zhao

Published 2019

Computer Science, Mathematics

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

Autonomous vehicles are expected to navigate in complex traffic scenarios with multiple surrounding vehicles. The correlations between road users vary over time, the degree of which, in theory, could be infinitely large, thus posing a great challenge in modeling and predicting the driving environment. In this paper, we propose a method to model multi-vehicle interactions using a stochastic vector field model and apply non-parametric Bayesian learning to extract the underlying motion patterns… CONTINUE READING

View on IEEE

arxiv.org

Save to Library

Create Alert

Cite

Launch Research Feed