A Dynamic Bayesian Network Based Merge Mechanism for Autonomous Vehicles
Abstract
This work explores the design of a central collaborative driving strategy between connected cars with the objective of improving road safety in case of highway on-ramp merging scenario. Based on a suitable method for predicting vehicle motion and behavior for a central collaborative strategy, a dynamic Bayesian network method that predicts the intention of drivers in highway on-ramp is proposed. The method was validated using real data of detailed vehicle trajectories on a segment of interstate 80 in Emeryville, California.
Cite
Text
El Abidine et al. "A Dynamic Bayesian Network Based Merge Mechanism for Autonomous Vehicles." AAAI Conference on Artificial Intelligence, 2019. doi:10.1609/AAAI.V33I01.33019953Markdown
[El Abidine et al. "A Dynamic Bayesian Network Based Merge Mechanism for Autonomous Vehicles." AAAI Conference on Artificial Intelligence, 2019.](https://mlanthology.org/aaai/2019/abidine2019aaai-dynamic/) doi:10.1609/AAAI.V33I01.33019953BibTeX
@inproceedings{abidine2019aaai-dynamic,
title = {{A Dynamic Bayesian Network Based Merge Mechanism for Autonomous Vehicles}},
author = {El Abidine, Kherroubi Zine and Aknine, Samir and Rebiha, Bacha},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2019},
pages = {9953-9954},
doi = {10.1609/AAAI.V33I01.33019953},
url = {https://mlanthology.org/aaai/2019/abidine2019aaai-dynamic/}
}