Li Lu, Persaud Bhagwant, Shalaby Amer
University of Toronto, Department of Civil Engineering, 35 St. George Street, Toronto, Ontario, M5S 1A4, Canada.
Ryerson University, Department of Civil Engineering, 350 Victoria Street, Toronto, Ontario M5B 2K3, Canada.
Accid Anal Prev. 2017 Mar;100:123-132. doi: 10.1016/j.aap.2016.12.019. Epub 2017 Jan 26.
This study investigates the use of crash prediction models and micro-simulation to develop an effective surrogate safety assessment measure at the intersection level. With the use of these tools, hypothetical scenarios can be developed and explored to evaluate the safety impacts of design alternatives in a controlled environment, in which factors not directly associated with the design alternatives can be fixed. Micro-simulation models are developed, calibrated, and validated. Traffic conflicts in the micro-simulation models are estimated and linked with observed crash frequency, which greatly alleviates the lengthy time needed to collect sufficient crash data for evaluating alternatives, due to the rare and infrequent nature of crash events. A set of generalized linear models with negative binomial error structure is developed to correlate the simulated conflicts with the observed crash frequency in Toronto, Ontario, Canada. Crash prediction models are also developed for crashes of different impact types and for transit-involved crashes. The resulting statistical significance and the goodness-of-fit of the models suggest adequate predictive ability. Based on the established correlation between simulated conflicts and observed crashes, scenarios are developed in the micro-simulation models to investigate the safety effects of individual transit line elements by making hypothetical modifications to such elements and estimating changes in crash frequency from the resulting changes in conflicts. The findings imply that the existing transit signal priority schemes can have a negative effect on safety performance, and that the existing near-side stop positioning and streetcar transit type can be safer at their current state than if they were to be replaced by their respective counterparts.
本研究调查了碰撞预测模型和微观模拟的使用情况，以在交叉口层面开发一种有效的替代安全评估措施。通过使用这些工具，可以开发和探索假设情景，以在可控环境中评估设计方案的安全影响，其中与设计方案不直接相关的因素可以固定。开发、校准并验证了微观模拟模型。估计微观模拟模型中的交通冲突，并将其与观察到的碰撞频率联系起来，由于碰撞事件的罕见性和不频繁性，这大大减少了为评估方案收集足够碰撞数据所需的漫长时间。开发了一组具有负二项式误差结构的广义线性模型，以关联加拿大安大略省多伦多市模拟冲突与观察到的碰撞频率。还针对不同碰撞类型的碰撞和涉及公交的碰撞开发了碰撞预测模型。模型的统计显著性和拟合优度表明其具有足够的预测能力。基于模拟冲突与观察到的碰撞之间已建立的相关性，在微观模拟模型中开发情景，通过对单个公交线要素进行假设性修改并根据冲突的相应变化估计碰撞频率的变化，来研究这些要素的安全效果。研究结果表明，现有的公交信号优先方案可能会对安全性能产生负面影响，并且现有的近端停车位置和有轨电车公交类型在当前状态下可能比被各自的对应类型取代时更安全。
