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		<title>Deep Reinforcement Learning Teaches Autonomous Cars to Change Lanes Safely and Smoothly</title>
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		<pubDate>Mon, 19 Oct 2026 06:23:41 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Autonomous Vehicles]]></category>
		<category><![CDATA[DDPG]]></category>
		<category><![CDATA[Deep Reinforcement Learning]]></category>
		<category><![CDATA[driving risk field]]></category>
		<category><![CDATA[Frontiers in Mechanical Engineering]]></category>
		<category><![CDATA[lane changing]]></category>
		<category><![CDATA[lane-changing trajectory planning]]></category>
		<category><![CDATA[Multi-objective]]></category>
		<category><![CDATA[optimization]]></category>
		<category><![CDATA[trajectories]]></category>
		<category><![CDATA[Trajectory prediction]]></category>
		<category><![CDATA[Transformer]]></category>
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					<description><![CDATA[Researchers in China have developed an improved deep reinforcement learning framework that jointly optimizes trajectory prediction and lane-changing decisions, achieving obstacle avoidance success rates of 98.92 percent in simulation.]]></description>
		
		
		
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