Diabetes is a major public health challenge worldwide. Abnormal physiology in diabetes, particularly hypoglycemia, can cause driver impairments that affect safe driving. While diabetes driver safety has been previously researched, few studies link real-time physiologic changes in drivers with diabetes to objective real-world driver safety, particularly at high-risk areas like intersections. To address this, we investigated the role of acute physiologic changes in drivers with type 1 diabetes mellitus (T1DM) on safe stopping at stop intersections. 18 T1DM drivers (21-52 years, mean = 31.2 years) and 14 controls (21-55 years, mean = 33.4 years) participated in a 4-week naturalistic driving study. At induction, each participant's vehicle was fitted with a camera and sensor system to collect driving data. Video was processed with computer vision algorithms detecting traffic elements. Stop intersections were geolocated with clustering methods, state intersection databases, and manual review. Videos showing driver stop intersection approaches were extracted and manually reviewed to classify stopping behavior (full, rolling, and no stop) and intersection traffic characteristics. Mixed-effects logistic regression models determined how diabetes driver stopping safety (safe vs. unsafe stop) was affected by 1) disease and 2) at-risk, acute physiology (hypo- and hyperglycemia). Diabetes drivers who were acutely hyperglycemic had 2.37 increased odds of unsafe stopping (95% CI: 1.26-4.47, p = 0.008) compared to those with normal physiology. Acute hypoglycemia did not associate with unsafe stopping (p = 0.537), however the lower frequency of hypoglycemia (vs. hyperglycemia) warrants a larger sample of drivers to investigate this effect. Critically, presence of diabetes alone did not associate with unsafe stopping, underscoring the need to evaluate driver physiology in licensing guidelines.
翻译:糖尿病,特别是低血糖病的异常生理学,可以造成影响安全驾驶的病变。虽然糖尿病驾驶员安全以前已经研究过,但很少有研究将糖尿病驾驶员的实时生理变化与糖尿病和现实世界驾驶员安全客观联系起来,特别是在诸如十字路口等高风险地区。为此,我们调查了1型糖尿病(T1DM)司机的急性生理变化在安全停留十字路口方面的作用。 18个T1DM司机(21-52年,平均=31.2年)和14个控制(21-55年,平均=33.4年)参加了为期4周的自然驾驶研究。在上岗时,每个参加者的车辆都安装了摄像和感系统来收集驾驶员数据。视频的处理过程是计算机视觉算法检测交通要素。停止路交路口是采用集方法、州间交叉数据库和手动审查。显示司机停止交接的视频方法没有被提取和手动地审查,以分类行为(完整、滚动和不停止)和交叉交通特征(21-47年的司机的比值)比值比值比值比值(停止性机机机机机机机变机变机变机变机的机机的机的机能机变变)。