Development of Strategies for Improving Traffic Safety and Operations in Winter

制定改善冬季交通安全和运营的策略

• 批准号: RGPIN-2016-05984
• 负责人: Mehran, Babak
• 金额: $ 3.5万
• 依托单位: University of Manitoba
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=753117
• 关键词: Development; Strategies; Improving; Traffic; Safety

Winter driving can be very challenging due to slippery roads and reduced visibility caused by falling and/or blowing snow. Due to reduced road surface friction and limited visibility, drivers are generally reluctant to use the desired acceleration and/or breaking power to react to traffic events. It is also common that pavement markings are completely covered by packed snow, and the effective lane width or the number of available lanes for moving traffic is reduced due to accumulation of snow caused by snow plow operations. These particular conditions suggest significant variations in physical characteristics of road network and driver behavior in winter. A clear understanding of such variations and their influence on traffic flow characteristics and safety are very important for highway agencies to plan for safe, efficient, and effective traffic management policies.The main purpose of this research is to investigate the effect of winter weather conditions on microscopic and macroscopic traffic flow characteristics on highways and intersections and evaluate the operational issues and safety risks caused by winter weather and winter road maintenance operations in order to develop traffic management strategies to minimize these impacts. Study sites will include several highway locations in Alberta and Saskatchewan and signalized intersections in Regina, Saskatchewan. Video surveys will be used to collect traffic data. Weather data will be collected using portable temperature and precipitation sensors installed at study sites. Road surface conditions will be monitored through video cameras and visual inspections. This research will also utilize traffic and weather data available from highway agencies and Environment Canada. A majority of parameters to be analyzed in this study have stochastic properties (e.g. following headway, capacity, etc.). The distribution of the parameter of interest will be obtained through empirical data, and statistical methods will be used to compare the distributions across different weather and road surface conditions. Regression and cross-classification analyses will be conducted to develop predictive models for describing these parameters considering various weather and road surface conditions.The research findings will allow calibration of driver behavior and car-following parameters in traffic micro-simulation models to account for winter weather conditions and provide better insights into seasonal fluctuations of highway capacity and intersection saturation flow rate. Furthermore, the investigations conducted in this study will provide clear guidelines for adjusting signal timing parameters to improve the operations and safety of signalized intersections in winter and assist highway agencies in maximizing the safety benefits of their winter road maintenance operations.

冬季驾驶是非常具有挑战性的，因为路面湿滑，能见度下降和/或吹雪。由于路面摩擦减少和能见度有限，驾驶员通常不愿意使用所需的加速和/或刹车功率来应对交通事件。路面标志完全被积雪覆盖的情况也很常见，由于扫雪机作业造成的积雪堆积，有效车道宽度或可供移动交通使用的车道数量减少。这些特殊情况表明，冬季道路网络的物理特征和驾驶员行为发生了显著变化。清楚地了解这些变化及其对交通流特征和安全的影响，对于公路管理机构制定安全、高效和有效的交通管理政策非常重要。本研究的主要目的是调查冬季天气条件对高速公路和交叉口微观和宏观交通流特征的影响，并评估冬季天气和冬季道路养护作业造成的运营问题和安全风险，以便制定交通管理策略以尽量减少这些影响。研究地点将包括阿尔伯塔省和萨斯喀彻温省的几条高速公路，以及萨斯喀彻温省里贾纳的信号十字路口。视频调查将用于收集交通数据。天气数据将通过安装在研究地点的便携式温度和降水传感器收集。路面状况将通过摄像机和目视检查进行监控。这项研究还将利用公路机构和加拿大环境部提供的交通和天气数据。本研究中分析的大部分参数都具有随机特性（如车头距、容量等）。将通过经验数据获得感兴趣参数的分布，并使用统计方法比较不同天气和路面条件下的分布。将进行回归和交叉分类分析，以开发预测模型，以描述考虑到各种天气和路面条件的这些参数。研究结果将允许在交通微观模拟模型中校准驾驶员行为和车辆跟随参数，以考虑冬季天气条件，并更好地了解公路容量和交叉口饱和流量的季节性波动。此外，本研究的调查将为调整信号配时参数提供明确的指导方针，以改善冬季信号交叉口的运营和安全，并协助公路机构最大限度地提高冬季道路养护作业的安全效益。