en خودروهای خودران Autonomous vehicles پژوهشي Research <span style="font-size:10.0pt"><span style="line-height:115%"><span new="" roman="" style="font-family:" times="">Ensuring that ethically sound decisions are made under complex, real-world conditions is a central challenge in deploying autonomous vehicles (AVs). This paper introduces a human-centric risk mitigation framework using Deep Q-Networks (DQNs) and a specially designed reward function to minimize the likelihood of fatal injuries, passenger harm, and vehicle damage. The approach uses a comprehensive state representation that captures the AV&rsquo;s dynamics and its surroundings (including the identification of vulnerable road users), and it explicitly prioritizes human safety in the decision-making process. The proposed DQN policy is evaluated in the CARLA simulator across three ethically challenging scenarios: a malfunctioning traffic signal, a cyclist&rsquo;s sudden swerve, and a child running into the street. In these scenarios, the DQN-based policy consistently minimizes severe outcomes and prioritizes the protection of vulnerable road users, outperforming a conventional collision-avoidance strategy in terms of safety. These findings demonstrate the feasibility of deep reinforcement learning for ethically aligned decision-making in AVs and point toward a pathway for developing safer and more socially responsible autonomous transportation systems.</span></span></span> Autonomous vehicles, Ethical decision-making, Human-centric, Risk mitigation, DQN 4619 4633 http://ase.iust.ac.ir/browse.php?a_code=A-10-833-1&slc_lang=en&sid=1 Ehsan Vakili ehsan_vakili@auto.iust.ac.ir 180031947532846004780 180031947532846004780 No School of Automotive Engineering, Iran University of Science and Technology, Tehran , Iran Behrooz Mashadi b_mashhadi@iust.ac.ir 180031947532846004781 180031947532846004781 No School of Automotive Engineering, Iran University of Science and Technology, Tehran, Iran Abdollah Amirkhani amirkhani@iust.ac.ir 180031947532846004782 180031947532846004782 Yes School of Automotive Engineering, Iran University of Science and Technology, Tehran, Iran