基于启发式算法的高速公路入匝道合流协同规划

Ming-Chou Shen, Hanyang Hu, Bohua Sun, W. Deng
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引用次数: 5

摘要

匝道合流场景对高速公路交通的移动性和安全性至关重要。现有的规划算法主要侧重于避免碰撞的纵向运动协调。然而,研究表明,在主车道上进行横向变道可以大大提高道路通行能力。在本文中,我们提出了一个综合的变道决策和纵向运动规划框架。车辆估计到达合并区域的时间以保证避免碰撞,并计算基于最优控制的启发式算法来做出变道决策。为了达到更好的性能,我们提出了一种协同决策与规划算法。数值仿真结果表明,该规划算法在简单顺序规划策略和无变道场景下均具有较高的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Heuristics Based Cooperative Planning for Highway On-Ramp Merge
On ramp merging scenario is critical to mobility and safety of highway traffic. The existing planning algorithms mainly focus on longitudinal motion coordination for collision avoidance. However, it has been shown that with lateral lane change in main lanes, the road capacity can be greatly enhanced. In this article, we propose an integrated framework for lane change decision making and longitudinal motion planning. Vehicles estimate the time they arrive merge region to guarantee collision avoidance, and optimal control based heuristics are calculated to make lane change decisions. To achieve better performance, we propose a cooperative decision making and planning algorithm. Numerical simulations show the efficiency of the proposed planning algorithm over simple sequential planning policy and scenarios without lane change.
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