Understanding speeding behavior on interstate horizontal curves and ramps using networkwide probe data

IF 3.9 2区 工程技术 Q1 ERGONOMICS
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Abstract

Introduction: Lane departure collisions account for many roadway fatalities across the United States. Many of these crashes occur on horizontal curves or ramps and are due to speeding. This research investigates factors that impact the odds of speeding on Interstate horizontal curves and ramps. Method: We collected and combined two unique sources of data. The first database involves comprehensive curve and ramp characteristics collected by an automatic road analyzer (ARAN) vehicle; the second database includes volume, average speed, and speed distribution gathered from probe data provided by StreetLight Insight®. We evaluated the impacts of level of service (LOS), which reflects traffic density or level of congestion, time of the day (morning, evening, and off-peak hours), time of the week (weekdays and weekends), and month of the year (Jan-Dec), and various information about geometric characteristics, such as curve radius, arc angle, and superelevation, on odds of speeding. Results: The results show that the odds of speeding increases at horizontal curves with improved levels of service, as well as those with larger radii and superelevation. The odds of speeding decreases on curves with larger arc angles and during the winter months of the year. The findings indicate a reduction in odds of speeding at diagonal/loop ramps with larger arc angles and narrower lane widths. Conclusion: The results show the importance of using speed enforcement and other countermeasures to reduce speeding on curves with low traffic volumes, high speed limits, and large radius and superelevation, especially for those in rural areas. Practical application: The results could be used to prioritize locations for the installation of speed countermeasures or dispatch enforcement resources to high-priority locations and times.

利用全网探测数据了解州际水平弯道和坡道上的超速行为
导言:在美国,车道偏离碰撞是造成许多公路死亡事故的原因。其中许多碰撞事故都发生在水平弯道或坡道上,而且都是由于超速造成的。本研究调查了影响州际公路水平弯道和坡道超速几率的因素。研究方法:我们收集并整合了两个独特的数据来源。第一个数据库包括由自动道路分析仪(ARAN)车辆收集的曲线和坡道综合特征;第二个数据库包括由 StreetLight Insight® 提供的探测数据收集的车流量、平均车速和车速分布。我们评估了反映交通密度或拥堵程度的服务水平 (LOS)、一天中的时间(早晨、傍晚和非高峰时段)、一周中的时间(工作日和周末)和一年中的月份(1 月至 12 月)以及有关几何特征的各种信息(如曲线半径、弧角和超高)对超速几率的影响。结果显示结果表明,在服务水平提高的水平弯道以及半径和高程较大的弯道上,超速几率会增加。而在弧角较大的弯道和每年的冬季,超速几率会降低。研究结果表明,在弧角较大、车道宽度较窄的对角线/环形坡道上,超速几率有所降低。结论结果表明,在交通流量小、限速高、半径大和超高的弯道上,尤其是农村地区的弯道上,采用测速执法和其他应对措施来减少超速的重要性。实际应用:这些结果可用于确定安装超速对策的优先地点,或将执法资源调度到优先地点和时间。
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来源期刊
CiteScore
6.40
自引率
4.90%
发文量
174
审稿时长
61 days
期刊介绍: Journal of Safety Research is an interdisciplinary publication that provides for the exchange of ideas and scientific evidence capturing studies through research in all areas of safety and health, including traffic, workplace, home, and community. This forum invites research using rigorous methodologies, encourages translational research, and engages the global scientific community through various partnerships (e.g., this outreach includes highlighting some of the latest findings from the U.S. Centers for Disease Control and Prevention).
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