2 citations · 2 across the 3 of their papers we have counts for
3 papers
math.NA2022
Quantifying the Individual Differences of Driver' Risk Perception with Just Four Interpretable Parameters
Chen Chen, Zhiqian Lan, Guojian Zhan +3
There will be a long time when automated vehicles are mixed with human-driven vehicles. Understanding how drivers assess driving risks and modelling their individual differences ar…
cs.RO2021★ 2 cited
Decision-Making under On-Ramp merge Scenarios by Distributional Soft Actor-Critic Algorithm
Yiting Kong, Yang Guan, Jingliang Duan +3
Merging into the highway from the on-ramp is an essential scenario for automated driving. The decision-making under the scenario needs to balance the safety and efficiency performa…
eess.SY2020
Mixed Reinforcement Learning with Additive Stochastic Uncertainty
Yao Mu, Shengbo Eben Li, Chang Liu +4
Reinforcement learning (RL) methods often rely on massive exploration data to search optimal policies, and suffer from poor sampling efficiency. This paper presents a mixed reinfor…