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Modeling Lane-Changing Behavior in Freeway Off-Ramp Areas from the Shanghai Naturalistic Driving Study

机译:基于上海自然驾驶研究的高速公路匝道外区域换车行为建模

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The objective of this study is to investigate lane-changing characteristics in freeway off-ramp areas using Shanghai Naturalistic Driving Study (SH-NDS) data, considering a four-lane freeway stretch in various traffic conditions. In SH-NDS, the behavior of drivers is observed unobtrusively in a natural setting for a long period of time. We identified 433 lane-changing events with valid time series data from the whole dataset. Based on the logit model developed to analyze the choice of target lanes, a likelihood analysis of lane-changing behavior was graphed with respect to three traffic conditions free flow, medium flow, and heavy flow. The results suggested that lane-changing behavior of exiting vehicles is the consequence of the balance between route plan (mandatory incentive) and expectation to improve driving condition (discretionary incentive). In higher traffic density, the latter seems to play a significant role. Furthermore, we found that lane-change from the slow lane to the fast lane would lead to higher speed variance value, which indicates a higher crash risk. The findings contribute to a better understanding on drivers’ natural driving behavior in freeway off-ramp areas and can provide important insight into road network design and safety management strategies.
机译:这项研究的目的是利用上海自然驾驶研究(SH-NDS)的数据来研究高速公路匝道以外地区的车道变换特性,同时考虑在各种交通条件下的四车道高速公路延伸。在SH-NDS中,可以在自然环境下长时间观察驾驶员的行为。我们从整个数据集中确定了433个具有有效时间序列数据的车道变换事件。在开发用于分析目标车道选择的logit模型的基础上,针对自由流动,中等流量和大流量这三种交通状况绘制了变道行为的可能性分析图。结果表明,退出车辆的变道行为是路线计划(强制性激励)与改善驾驶条件的期望(酌情性激励)之间取得平衡的结果。在较高的流量密度中,后者似乎起着重要作用。此外,我们发现从慢车道到快车道的换道将导致更高的速度变化值,这表明更高的碰撞风险。这些发现有助于人们更好地了解高速公路非匝道区域的驾驶员自然驾驶行为,并且可以提供对道路网络设计和安全管理策略的重要见解。

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