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首页> 外文期刊>Intelligent Transport Systems, IET >Longitudinal driving behaviour on different roadway categories: an instrumented-vehicle experiment, data collection and case study in China
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Longitudinal driving behaviour on different roadway categories: an instrumented-vehicle experiment, data collection and case study in China

机译：不同道路类别上的纵向驾驶行为：中国的车辆实验，数据收集和案例研究

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摘要

A significant portion of the observed variability in roadway performance can be due to the difference and innate heterogeneity in drivers' behaviour. Analytical models, stated preference data collection and studies and laboratory-based simulator experiments are developed to understand the driver behaviour for years. However, little has been done to fill the important gap between the survey/laboratory observed behaviour and the field observed behaviour. This study investigates drivers' actual behaviour by conducting real-world field experiments in Beijing's roadway system. In the experiment platform developed, instrumented vehicles are employed for the advanced data collection and analysis in order to understand the impact of roadway category on drivers' longitudinal behaviour, that is, car-following and car-approaching. These behaviour dimensions are identified in this study and quantified by parameters including relative speed, leading vehicle speed, accelerator release, braking activation, distance headway, time headway and time-to-collision. The analysis suggests that the drivers' behaviour variation heavily depends on roadway characteristics, which supplements further theoretical and survey-based behavioural research. The research findings provide insight for theoretical advances, evaluating driving assistance systems and roadway-specific incentive designs for traffic harmonisation, speed reduction, collision warning/avoidance, safety enhancement and energy consumption savings.
机译：观察到的道路性能差异的很大一部分可能是由于驾驶员行为的差异和先天异质性造成的。分析模型，陈述的偏好数据收集和研究以及基于实验室的模拟器实验被开发出来，以了解驾驶员的行为。但是，在填补调查/实验室观察到的行为与现场观察到的行为之间的重要空白方面，几乎没有做过任何事情。本研究通过在北京道路系统中进行现实世界的现场调查来调查驾驶员的实际行为。在开发的实验平台中，仪表车被用于高级数据收集和分析，以了解道路类别对驾驶员纵向行为（即跟车和驾车）的影响。在本研究中确定了这些行为维度，并通过参数进行了量化，这些参数包括相对速度，领先车辆速度，加速器释放，制动激活，距离时距，时间时距和碰撞时间。分析表明，驾驶员的行为变化在很大程度上取决于道路特征，这补充了进一步的理论和基于调查的行为研究。研究结果为理论发展提供了见识，评估了驾驶辅助系统和特定于道路的激励设计，以实现交通协调，减速，碰撞预警/避免，安全性增强和节能。

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