Introduction: With prevalent and increased attention to driver inattention (DI) behavior, this research provides a comprehensive investigation of the influence of built environment and roadway characteristics on the DI-related vehicle crash frequency per year. Specifically, a comparative analysis between DI-related crash frequency in rural road segments and urban road segments is conducted. Method: Utilizing DI-related crash data collected from North Carolina for the period 2013–2017, three types of models: (1) Poisson/negative binomial (NB) model, (2) Poisson hurdle (HP) model/negative binomial hurdle (HNB) model, and (3) random intercepts Poisson hurdle (RIHP) model/random intercepts negative binomial hurdle (RIHNB) model, are applied to handle excessive zeros and unobserved heterogeneity in the dataset. Results: The results show that RIHP and RIHNB models distinctly outperform other models in terms of goodness-of-fit. The presence of commercial areas is found to increase the probability and frequency of DI-related crashes in both rural and urban regions. Roadway characteristics (such as non-freeways, segments with multiple lanes, and traffic signals) are positively associated with increased DI-related crash counts, whereas state-secondary routes and speed limits (higher than 35 mph) are associated with decreased DI-related crash counts in rural and urban regions. Besides, horizontal curved and longitudinal bottomed segments and segments with double yellow lines/no passing zones are likely to have fewer DI-related crashes in urban areas. Medians in rural road segments are found to be effective to reduce DI-related crashes. Practical Applications: These findings provide a valuable understanding of the DI-related crash frequency for transportation agencies to propose effective countermeasures and safety treatments (e.g., dispatching more police enforcement or surveillance cameras in commercial areas, and setting more medians in rural roads) to mitigate the negative consequences of DI behavior.

简介：随着对驾驶员注意力不集中 (DI) 行为的普遍和日益关注，本研究对建筑环境和道路特征对每年与 DI 相关的车辆碰撞频率的影响进行了全面调查。具体而言，对农村路段和城市路段中与 DI 相关的碰撞频率进行了比较分析。方法：利用从北卡罗来纳州收集的 2013-2017 年期间与 DI 相关的碰撞数据，三种类型的模型：(1) 泊松/负二项式 (NB) 模型，(2) 泊松障碍 (HP) 模型/负二项式障碍 (HNB)模型和 (3) 随机截距泊松障碍 (RIHP) 模型/随机截距负二项式障碍 (RIHNB) 模型，用于处理数据集中过多的零和未观察到的异质性。结果：结果表明，RIHP 和 RIHNB 模型在拟合优度方面明显优于其他模型。发现商业区的存在增加了农村和城市地区与 DI 相关的事故的概率和频率。道路特征（例如非高速公路、多车道路段和交通信号灯）与 DI 相关事故数量增加呈正相关，而州二级路线和速度限制（高于 35 mph）与 DI 相关事故数量减少相关农村和城市地区的事故数量。此外，水平弯曲和纵向底部路段以及带有双黄线/禁止通行区的路段可能在城市地区发生与 DI 相关的事故较少。发现农村路段的中位数可有效减少与 DI 相关的事故。实际应用：这些发现为交通机构提供了对 DI 相关碰撞频率的宝贵理解，以提出有效的对策和安全处理（例如，在商业区派遣更多的警察执法或监控摄像头，并在农村道路设置更多的隔离带）以减轻DI行为的负面后果。