@inproceedings{a70a9083003148da9d0717801fd8540e,
title = "Don't Get into Trouble! Risk-aware Decision-Making for Autonomous Vehicles",
abstract = "Risk is traditionally described as the expected likelihood of an undesirable outcome, such as a collision for an autonomous vehicle. Accurately predicting risk or potentially risky situations is critical for the safe operation of an autonomous vehicle. This work combines use of a controller trained to navigate around individuals in a crowd and a risk-based decision-making framework for an autonomous vehicle that integrates high-level risk-based path planning with a reinforcement learning-based low-level control. We evaluated our method using a high-fidelity simulation environment. We show our method results in zero collisions with pedestrians and predicted the least risky path, time to travel, or day to travel in approximately 72\% of traversals. This work can improve safety by allowing an autonomous vehicle to one day avoid and react to risky situations.",
author = "Kasra Mokhtari and Wagner, \{Alan R.\}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 31st IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2022 ; Conference date: 29-08-2022 Through 02-09-2022",
year = "2022",
doi = "10.1109/RO-MAN53752.2022.9900795",
language = "English (US)",
series = "RO-MAN 2022 - 31st IEEE International Conference on Robot and Human Interactive Communication: Social, Asocial, and Antisocial Robots",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1570--1577",
booktitle = "RO-MAN 2022 - 31st IEEE International Conference on Robot and Human Interactive Communication",
address = "United States",
}