Afghari Amir Pooyan, Haque Md Mazharul, Washington Simon
a School of Civil Engineering , The University of Queensland , St. Lucia , Queensland , Australia.
b School of Civil Engineering and Built Environment, Science and Engineering Faculty , Queensland University of Technology , Brisbane , Queensland , Australia.
Traffic Inj Prev. 2018;19(8):860-866. doi: 10.1080/15389588.2018.1509208. Epub 2019 Jan 15.
The speed selection behavior of drivers has been reported to vary across driver demographics, psychological attributes, and vehicle-specific factors. In contrast, the effects of roadway geometric, traffic characteristics, and site-specific factors on speed selection are less well known. In addition, the relative degree of speeding has received little attention and thus remains relatively unexplored. This study aims to investigate the effects of roadway geometrics, traffic characteristics, and site-specific factors on speeding behavior of drivers.
A panel mixed logit fractional split model is estimated to analyze the proportion of speed limit violations across highway segments. To account for possible unobserved heterogeneity, the suitability of latent class model specification is also tested. Speeding data were collected from speed cameras along major arterials and highways in Queensland, Australia, and were merged with several other data sources including roadway geometric characteristics, spatial features of the surrounding environment, and driver behavioral factors.
The results of the panel mixed logit fractional split model suggest a tendency among drivers to commit minor speed limit violations irrespective of causal factors. Among potential road geometric and traffic factors, radius of horizontal curves, percentage of heavy vehicle traffic on segments with divided median, posted speed limit, and road functional classification are factors that influence speeding behavior. Additionally, the deployment of covert speed cameras is found to decrease the likelihood of major speed limit violations along arterials or highways.
An understanding of the influence of roadway geometrics and traffic characteristics on speeding behavior of drivers will inform the design of targeted countermeasures in order to reduce speed limit violations along highways.
据报道，驾驶员的速度选择行为会因驾驶员人口统计学特征、心理属性和车辆特定因素而有所不同。相比之下，道路几何形状、交通特征和特定地点因素对速度选择的影响则鲜为人知。此外，超速的相对程度很少受到关注，因此仍有待进一步探索。本研究旨在调查道路几何形状、交通特征和特定地点因素对驾驶员超速行为的影响。
估计一个面板混合逻辑分数拆分模型，以分析高速公路路段超速违规的比例。为了考虑可能存在的未观察到的异质性，还测试了潜在类别模型规范的适用性。超速数据是从澳大利亚昆士兰州主要干道和高速公路上的测速摄像头收集的，并与其他几个数据源合并，包括道路几何特征、周边环境的空间特征和驾驶员行为因素。
面板混合逻辑分数拆分模型的结果表明，无论因果因素如何，驾驶员都有轻微超速违规的倾向。在潜在的道路几何和交通因素中，水平曲线半径、设有中央分隔带的路段上重型车辆交通的百分比、公布的速度限制和道路功能分类是影响超速行为的因素。此外，发现隐蔽测速摄像头的部署会降低干道或高速公路上严重超速违规的可能性。
了解道路几何形状和交通特征对驾驶员超速行为的影响，将为制定有针对性的对策提供依据，以减少高速公路上的超速违规行为。
