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Driver lane changing behavior

机译:驾驶员换道行为

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摘要

Understanding the human behaviors in driving is a highly complex topic but on the other hand, extremely important for improving human's driving competence by developing driver assistant systems accordingly and finally accomplishing fully autonomous vehicles and road systems. There are many excellent researches in this area for decades. However, by building a comprehensive system to evaluate human driver's behavior, we found that none of the existing model can reflect the same outcome as our observation from the real world in the multiplex traffic scenario. But this is indeed important for us to find the right way to improve road traffic efficiency as well as develop autonomous vehicles. In this work, we combined couple of previous approaches to a single model with some improvements and successfully implemented it into a new simulator which can be used to evaluate other traffic applications upon the driver behavior model. We focused on lane changing decision of the driver behavior since it is the most complex part and causes the most problem and inconsistency in previous researches. After comparing the result getting from the simulation based on the new model with the real world observation, we can conclude that the new driver behavior model does reflect the real world scenario. And the model and simulator also helps us in our further researches in intelligent traffic control area.
机译:了解驾驶中的人类行为是一个非常复杂的主题,但另一方面,通过相应地开发驾驶员辅助系统并最终完成完全自动驾驶的车辆和道路系统,对于提高人类的驾驶能力极为重要。数十年来,该领域有许多出色的研究。但是,通过构建一个全面的系统来评估驾驶员的行为,我们发现,在多路交通场景中,现有模型都无法反映出与真实世界中观察到的结果相同的结果。但这对于我们找到提高道路交通效率以及开发自动驾驶汽车的正确方法确实很重要。在这项工作中,我们将先前对几个模型的改进方法结合在一起,并进行了一些改进,并将其成功实现到新的模拟器中,该模拟器可用于根据驾驶员行为模型评估其他交通应用。由于它是最复杂的部分,并且在先前的研究中引起最多的问题和不一致,因此我们专注于驾驶员行为的换道决策。将基于新模型的仿真结果与实际观察结果进行比较后,我们可以得出结论,新驾驶员行为模型确实反映了真实情况。该模型和仿真器也有助于我们在智能交通控制领域的进一步研究。

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