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Adaptive cooperative maneuver planning algorithm for conflict resolution in diverse traffic situations

机译:自适应协同机动计划算法,用于多种交通状况下的冲突解决

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Growing interest in Cooperative Driving within the field of Intelligent Transport Systems (ITS) put forth novel concepts for both enhanced sensing and advanced solution making. Although various approaches deal with advanced solution making, none of the concepts consider the conflict situation as a holistic situation comprising defined end states and trajectories towards them. We propose a novel algorithm for cooperative maneuver planning that is not meant to optimize a high level strategy but shall solve a conflict in the following five steps: target point generation, risk assessment, trajectory generation, combination including assessment, and execution of the maneuvers. The proposed cooperative maneuver planning algorithm is applicable to all kinds of road users' interferences (safety, comfort, time efficiency, and consumption efficiency), highly adaptive in terms of complexity and scalability, individually parameterizable, and applicable in diverse and mixed traffic situations. Simulations indicate the wide usability and performance of this approach in two different scenarios. The algorithm solves a critical overtaking maneuver on a country road and a merging maneuver onto a highway. Modifications of the initial situation lead to different solutions and thus show the adaptive nature of the algorithm.
机译:在智能交通系统(ITS)领域中,对合作驾驶的兴趣日益浓厚,提出了用于增强传感和高级解决方案制造的新颖概念。尽管各种方法都涉及高级解决方案的制作,但没有一个概念将冲突情况视为包括定义的最终状态和朝向它们的轨迹的整体情况。我们提出了一种用于协同机动计划的新颖算法,该算法并不旨在优化高级策略,而应在以下五个步骤中解决冲突:目标点生成,风险评估,轨迹生成,包括评估的组合和机动执行。提出的协同机动计划算法适用于各种道路使用者的干扰(安全性,舒适性,时间效率和消耗效率),在复杂性和可扩展性方面具有高度自适应性,可单独设置参数,并适用于各种混合交通情况。仿真表明,这种方法在两种不同的情况下具有广泛的可用性和性能。该算法解决了乡村道路上的关键超车操作和高速公路上的合并操作。初始情况的修改导致不同的解决方案,因此显示了该算法的自适应性质。

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