An online approach for intersection navigation of autonomous vehicle

Yang Bai, Z. J. Chong, M. Ang, Xueshan Gao
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引用次数: 5

Abstract

Navigation through an intersection is a fundamental task that will enable an autonomous car to operate in a real traffic environment. Previous studies about intersection navigation generally assume vehicle to vehicle communication ability for all of the vehicles. Since this is unattainable in the near future, we focus on the scenario that vehicles on the road cannot communicate with each other. A new model is presented for this kind of intersection navigation as a Partially Observable Markov Decision Process problem. The proposed model can handle multiple numbers of cars in a dynamic environment. To validate the feasibility of the model, experiments are carried out with an autonomous golf cart in the university campus.
一种自动驾驶汽车交叉口在线导航方法
通过十字路口的导航是一项基本任务,它将使自动驾驶汽车在真实的交通环境中运行。以往的交叉口导航研究一般假设所有车辆都具有车与车之间的通信能力。由于这在不久的将来是不可能实现的,因此我们将重点放在道路上的车辆无法相互通信的场景上。将这类交叉口导航作为部分可观察马尔可夫决策过程问题,提出了一种新的模型。该模型可以在动态环境中处理多个数量的汽车。为了验证该模型的可行性,在大学校园内用自动高尔夫球车进行了实验。
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