Research Article
Modeling Autonomous Vehicles’ Altruistic Behavior to Human-Driven Vehicles in the Car following Events and Impact Analysis
(1) | Randomly initialize critic network and actor with weights and | (2) | Initialize target network and with weights , | (3) | Initialize replay buffer | (4) | For episode = 1, M do | (5) | Initialize a random process for action exploration | (6) | Receive initial observation state | (7) | For t = 1, T do | (8) | Select action according to current policy and exploration noise | (9) | Execute action and observe reward and observe new state | (10) | Store transition in | (11) | Sample a random minibatch of transitions from | (12) | Set | (13) | Update critic by minimizing loss: | (14) | Update actor policy using sampled policy gradient: | (15) | Update target networks:, | (16) | End for | (17) | End for |
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