论文标题
使用预测性马尔可夫决策过程中的城市驾驶中的车道变化操作的新方法
A Novel Method for Lane-change Maneuver in Urban Driving Using Predictive Markov Decision Process
论文作者
论文摘要
对于手动驾驶和自动驾驶，尤其是在城市环境中，巷道变化一直是一项具有挑战性的任务。特别是，预测其他车辆在道路上的行为的不确定性会导致in亵行动，同时改变车道，这可能导致交通拥堵并引起安全问题。本文分析了与不确定性相关的因素，例如速度范围变化和车道变化，以设计城市环境中车道变化动作的预测性马尔可夫决策过程。开发了一个隐藏的马尔可夫模型，用于建模周围车辆的不确定性。奖励模型将崩溃概率和可行性/距离作为主要参数。完成了两种交通情况的数值模拟和分析，以证明所提出的方法的有效性。
Lane-change maneuver has always been a challenging task for both manual and autonomous driving, especially in an urban setting. In particular, the uncertainty in predicting the behavior of other vehicles on the road leads to indecisive actions while changing lanes, which, might result in traffic congestion and cause safety concerns. This paper analyzes the factors related to uncertainty such as speed range change and lane change so as to design a predictive Markov decision process for lane-change maneuver in the urban setting. A hidden Markov model is developed for modeling uncertainties of surrounding vehicles. The reward model uses the crash probabilities and the feasibility/distance to the goal as primary parameters. Numerical simulation and analysis of two traffic scenarios are completed to demonstrate the effectiveness of the proposed approach.
