###### Abstract  
Driving under the influence of alcohol (DUI) remains a leading cause of accidents globally, with accident risk rising exponentially with blood alcohol concentration (BAC). This study aims to distinguish between sober and intoxated drivers using driving behavior analysis and driver monitoring system (DMS), technologies that align with emerging EU regulations. In a driving simulator, twenty-three participants (average age: 32) completed five drives (one practice and two each while sober and intoxated) on separate days across city, rural, and highway settings. Each 30-minute drive was analyzed using eye-tracking and driving behavior data. We applied significance testing and classification models to assess the data. Our study goes beyond the state of the art by a) combining data from various sensors and b) not only examining the effects of alcohol on driving behavior but also using these data to classify driver impairment. Fusing gaze and driving behavior data improved classification accuracy, with models achieving over 70% accuracy in city and rural conditions and a Long Short-Term Memory (LSTM) network reaching up to 80% on rural roads. Although the detection rate is, of course, still far too low for a productive system, the results nevertheless provide valuable insights for improving DUI detection technologies and enhancing road safety.  
driving under the influence; intoxication detection; study; fusion; classification; driving behavior; gaze behavior; in-cabin monitoring systems 2020 IEEE/  
(NHTSA), about 10,000 people die each year in the U.S. [6]. This makes driving under the influence of alcohol (DUI) the number one cause of fatal accidents in the U.S., and 31% of fatal car accidents are correlated with alcohol [6]. The relative probability of causing an accident increases exponentially with blood alcohol concentration (BAC) [7,8]. This is visualized in Figure 1. Figure 1 shows the relative crash risk in relation to the BAC, where the relative risk is set in relation to the accident risk of driving sober (BAC = 0).  
This is why countries around the world have set limits above which it is illegal to drive a car. In Germany, the legal limit is 0.05% BAC. The relative crash risk at the legal limit is only 38% higher than driving sober [7]. This is why this study examined a blood alcohol concentration just above the legal limit of 0.06%. Various approaches exist in the literature to distinguish between sober and impaired drivers. These include methods based on thermal (Far-Infrared (FIR)) cameras [9], near-infrared (NIR) cameras [10,11], gas sensors [1,2,12], electrocardiography (ECG) [13], driving behavior analysis [14,15], and multi-sensor systems [2,15,16,17]. Most of today's production vehicles do not integrate these sensors, but the available driving data can still be utilized. In addition, camera-based driver monitoring systems (DMSs) are being developed (e.g., DMSs from the Frauenhofer Institute [18]). According to a study by ABI Research, DMSs with driver monitoring cameras are considered a key technology for systems for driver condition recognition required by EU regulations (General Safety Regulations (GSRs) [19]) from 2024 and for semi-autonomous driving [18,20]. Therefore, the combination of driving behavior analysis and DMSs should increase the accuracy of detecting DUI.