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Yuan, Henan (author), Li, Penghui (author), van Arem, B. (author), Kang, Liujiang (author), Farah, H. (author), Dong, Y. (author)
Traffic scenarios in roundabouts pose substantial complexity for automated driving. Manually mapping all possible scenarios into a state space is labor-intensive and challenging. Deep reinforcement learning (DRL) with its ability to learn from interacting with the environment emerges as a promising solution for training such automated driving...
conference paper 2023
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Wang, M. (author), Li, Honghai (author), GAO, Jian (author), Huang, Zichao (author), li, Bin (author), van Arem, B. (author)
It is expected that automated vehicles will gradually penetrate on public roads, resulting in mixed traffic in the next decades. This can impact traffic flow operations, especially the roadway capacity and flow stability. It is of paramount<br/>importance to understand and predict the implications of automated driving systems on traffic flow at...
conference paper 2017