2023
DOI: 10.1109/access.2023.3293122
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Implementation of a V2P-Based VRU Warning System With C-V2X Technology

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Cited by 9 publications
(2 citation statements)
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“…In the quest to fulfil this objective, two progressive deep reinforcement learning (RL) techniques, namely, the Deep Q-Network (DQN) and the Advantage Actor-Critic (A2C), are employed. Moreover, in contemplation of the temporal variability inherent to user mobility, the Long Short-Term Memory (LSTM) mechanism is integrated into the framework, providing an additional layer of analytical depth [12][13][14].…”
Section: Figure 2 Fundamental Block Diagram Of V2xmentioning
confidence: 99%
“…In the quest to fulfil this objective, two progressive deep reinforcement learning (RL) techniques, namely, the Deep Q-Network (DQN) and the Advantage Actor-Critic (A2C), are employed. Moreover, in contemplation of the temporal variability inherent to user mobility, the Long Short-Term Memory (LSTM) mechanism is integrated into the framework, providing an additional layer of analytical depth [12][13][14].…”
Section: Figure 2 Fundamental Block Diagram Of V2xmentioning
confidence: 99%
“…First, the set of ETSI standards mentioned earlier was released just recently. Second, there is no existing smartphone today supporting the dedicated frequencies for direct communication between vehicles and pedestrians [6], making it fairly complex to equip pedestrians for field tests. Third, there is currently a lack of open and customizable frameworks for testing V2X use cases with both vehicles and pedestrians in simulation and in the field.…”
Section: Introductionmentioning
confidence: 99%