Risk-anticipatory autonomous driving strategies considering vehicles' weights, based on hierarchical deep reinforcement learning

arXiv:2401.08661v2 Announce Type: replace-cross
Abstract: Autonomous vehicles (AVs) have the potential to prevent accidents caused by drivers errors and reduce road traffic risks. Due to the nature of heavy vehicles, whose collisions cause more serious crashes, the weights of vehicles need to be considered when making driving strategies aimed at reducing the potential risks and their consequences in the context of autonomous driving. This study develops an autonomous driving strategy based on risk anticipation, considering the weights of surrounding vehicles …

abstract accidents arxiv autonomous autonomous driving autonomous vehicles avs cs.lg cs.ro drivers driving errors hierarchical making nature reduce reinforcement reinforcement learning risk risks strategies traffic type vehicles