28 天前 - … the low interpretability causing a lack of trust in the technology [1]. Reinforcement
Learning (RL) is a machine learning … 2) Action space: Every ∆t seconds, the traffic signal agent …

57 天前 - … interpretable policy function can be as effective as a deep neural network in optimizing
signal actuation policy… so it has a better interpretability than the learning-based methods. …

91 天前 - … While machine learning plays a critical role in analyzing … are replicable and easily
interpretable, making them … To further enhance their adaptive management strategy, Neptune …

94 天前 - … They have their own place in the programmes of learning. However, there is a void
in a … These candidates can refer to the guide book for a quick study. Certain tips not usually …

107 天前 - … policy of traffic signals. To actualize this proposition, we introduce π-Light for traffic
signal control, which combines the adaptive features of RL methods with the interpretability …

173 天前 - … , with the aim of enhancing the interpretability and classification performance of
existing … the next study, we address the challenge of guaranteeing compliance with traffic rules …

190 天前 - … In this section, this paper proposes a frequency band selection strategy based
on frequency saliency. Since an ALS can divide the signals into four different frequency …

237 天前 - … interpretability. … strategy using YOLO v5 produces an average accuracy of
approximately 97.80% in the GTSRB dataset which is more suitable for the Indian road system…

289 天前 - … traffic scenarios. Reviewing the current lane changing decision methods of AVs,
most of them lack interpretability … method can extract interpretable rules from vehicle trajectory …

289 天前 - … -free methods, which learn value and/or policy functions directly through environment
in… sufficient for our application to traffic signal control. A (stochastic) policy π is a mapping …