Understanding and Predicting Overtaking and Fold-Down Lane-Changing Maneuvers on European Highways Using Naturalistic Road User Data*

Basma Khelfa, A. Tordeux
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引用次数: 1

Abstract

Understanding and predicting lane-changing in-tents on highways is fundamental for multi-lane cruise control systems and automated driving. Many studies have been carried out using the NGSIM data-set of trajectories on US highways with symmetric lane-changing behaviors. In this contribution, we present a statistical analysis of discretionary lane-changing maneuvers on German two-lane highways imposing overtaking to the left only (highD project). We aim to separately identify the underlying mechanisms that motivate drivers to overtake and to fold-down. The analysis is done using principal component analysis and logistic regressions based on speed-difference and distance variables with the four surrounding vehicles. The results show that two different mechanisms operate in case of overtaking and fold-down. Overtaking can be explained monotonically with only three variables: the distance and speed difference with the predecessor and the speed difference with the following vehicle on the adjacent lane. Fold-down is a more complex process involving more variables and relationships. The predictions based on the logistic regression are accurate for lane-keeping but limited for lane-changing maneuver, especially for fold-down. The limitations are due to non-linear behaviors of the fold-down maneuver for which the logistic regression is insensitive.
利用自然道路用户数据理解和预测欧洲高速公路上的超车和折返变道行为*
理解和预测高速公路上的车道变化是多车道巡航控制系统和自动驾驶的基础。许多研究使用了美国高速公路上具有对称变道行为的轨迹数据集。在这篇文章中,我们对德国双车道高速公路上的任意变道机动进行了统计分析,强制向左超车(highD项目)。我们的目标是分别确定激励驾驶员超车和折车的潜在机制。分析采用主成分分析和基于与周围四辆车的速度差和距离变量的逻辑回归进行。结果表明,在超车和折叠情况下,有两种不同的工作机制。超车可以单调地用三个变量来解释:与前车的距离和速度差以及与相邻车道上的后车的速度差。折叠是一个更复杂的过程,涉及更多的变量和关系。基于逻辑回归的预测对于保持车道是准确的,但对于变道机动,特别是折叠下行时,预测是有限的。限制是由于折叠机动的非线性行为,逻辑回归是不敏感的。
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