Search Results (15)

Global road safety reports identify human factors as the leading causes of traffic accidents, particularly behaviors such as speeding, drunk driving, and driver distraction, emphasizing the need for autonomous driving technologies to enhance transport safety. This research aims to provide a practical model for the development of autonomous driving systems as part of an autonomous transportation system for inter-building passenger mobility, intended to enable safe and efficient short-distance transport between buildings in semi-open environments such as university campuses. This work presents a fully integrated autonomous platform combining LiDAR, cameras, and IMU sensors for mapping, perception, localization, and control within a drive-by-wire framework, achieving superior coordination in driving, braking, and obstacle avoidance and validated under real campus conditions. The electric golf cart prototype achieved centimeter-level mapping accuracy (0.32 m), precise localization (0.08 m), and 2D object detection with an mAP value exceeding 70%, demonstrating accurate perception and positioning under real-world conditions. These results confirm its reliable performance and suitability for practical autonomous operation. Field tests showed that the vehicle maintained appropriate speeds and path curvature while performing effective obstacle avoidance. The findings highlight the system’s potential to improve safety and reliability in short-distance autonomous mobility while supporting scalable smart mobility development. Full article

This study aims to decrease the number of drunk drivers, a significant social problem. Traditional methods to measure alcohol intake include blood alcohol concentration (BAC) and breath alcohol concentration (BrAC) tests. While BAC testing requires blood samples and is impractical, BrAC testing is commonly used in drunk driving enforcement. In this study, the multiple biological signals of electrocardiogram (ECG), photoplethysmogram (PPG), and electrodermal activity (EDA) were collected non-invasively and with minimal driver restraint in a driving simulator. Data were collected from 10 participants for approximately 10 min at BrAC levels of 0.00%, 0.03%, and 0.08%, which align with the latest Korean drunk driving standards. The collected data underwent frequency filtering and were segmented into 30 s intervals with a 10 s overlap to extract heart rate variability (HRV) and pulse arrival time (PAT). Using more than 10 machine learning algorithms, the classification accuracy reached 88%. The results indicate that it is possible to classify a driver’s level of intoxication using only non-invasive biological signals within a short period of about 30 s, potentially aiding in the prevention of drunk driving. Full article

Background: Drugged driving is associated with an increased risk of road accidents worldwide. In Italy, driving under the influence (DUI) of alcohol and drugs is a reason for driving disqualification or revocation of the driving license. Drivers charged with driving under the influence of alcohol and drugs must attend a Local Medical Commission (LMC) to undergo mandatory examinations to regain the suspended license. Our study mainly aims to report on the analysis performed on hair samples collected from 7560 drivers who had their licenses suspended for drugged or drunk driving between January 2019 and June 2024. Methods: A rapid, sensitive, and selective method for the determination of ethyl glucuronide in hair by UPLC/MS-MS was developed and fully validated. Results: The most frequently detected substances were cocaine (ecgonine methyl ester, norcocaine, and benzoylecgonine) and cannabinoids (Δ9-tetrahydrocannabinol, cannabidiol, and cannabinol), followed by opiates (codeine, morphine, and 6-MAM), methadone (EDDP), and amphetamines (amphetamine, methamphetamine, MDA, MDMA, and MDEA). To perform a more in-depth analysis, we also compared hair color with the drug classes that tested positive. The results showed a significant prevalence of dark hair that tested positive for one or more substances, followed by gray/white hair and light hair. Conclusions: Our study provides an interesting and alarming insight into drug exposure in the general population with serious public health threats, discussing the main aspects of hair matrix analysis and focusing on its advantages and reliability in the interpretation of results. Full article

In this research, 3356 alcohol-related traffic crashes were obtained from blood-alcohol test reports in Tianjin, China. Population density, intersection density, road density, and alcohol outlet densities, including retail density, entertainment density, restaurant density, company density, hotel density, and residential density, were extracted from 2114 traffic analysis zones (TAZs). After a spatial autocorrelation test, the multiple linear regression model (MLR), geographically weighted Poisson regression model (GWPR), and semi-parametric geographically weighted Poisson regression model (SGWPR) were utilized to explore the spatial effects of the aforementioned variables on drunk-driving crash density. The result shows that the SGWPR model based on the adaptive Gaussian function had the smallest AICc value and the best-fitting accuracy. The residential density and the intersection density are global variables, and the others are local variables that have different influences in different regions. Furthermore, we found that the influence of local variables in the economic–technological development area shows significantly different characteristics compared with other districts. Thus, a comprehensive consideration of spatial heterogeneity would be able to improve the effectiveness of the programs formulated to decrease drunk driving crashes. Full article

Since drunk driving poses a significant threat to road traffic safety, there is an increasing demand for the performance and dependability of online drunk driving detection devices for automobiles. However, the majority of current detection devices only contain a single sensor, resulting in a low degree of detection accuracy, erroneous judgments, and car locking. In order to solve the problem, this study firstly designed a sensor array based on the gas diffusion model and the characteristics of a car steering wheel. Secondly, the data fusion algorithm is proposed according to the data characteristics of the sensor array on the steering wheel. The support matrix is used to improve the data consistency of the single sensor data, and then the adaptive weighted fusion algorithm is used for multiple sensors. Finally, in order to verify the reliability of the system, an online intelligent detection device for drunk driving based on multi-sensor fusion was developed, and three people using different combinations of drunk driving simulation experiments were conducted. According to the test results, a drunk person in the passenger seat will not cause the system to make a drunk driving determination. When more than 50 mL of alcohol is consumed and the driver is seated in the driver’s seat, the online intelligent detection of drunk driving can accurately identify drunk driving, and the car will lock itself as soon as a real-time online voice prompt is heard. This study enhances and complements theories relating to data fusion for online automobile drunk driving detection, allowing for the online identification of drivers who have been drinking and the locking of their vehicles to prevent drunk driving. It provides technical support for enhancing the accuracy of online systems that detect drunk driving in automobiles. Full article

Driving safety issues, such as drunk driving, have drawn a lot of attention since the advent of shared automobiles. We used an electronic nose (EN) detection device as an onboard system for shared automobiles to identify drunk driving. The sensors in the EN, however, can stray in cold winter temperatures. We suggested an independent component analysis (ICA) correction model to handle the data collected from the EN in order to lessen the impact of low temperature on the device. Additionally, it was contrasted with both the mixed temperature correction model and the single temperature model. As samples, alcohol mixed with concentrations of 0.1 mg/L and 0.5 mg/L were tested at (20 ± 2) °C, (−10 ± 2) °C, and (−20 ± 2) °C. The results showed that the ICA correction model outperformed the other models with an accuracy of 1, precision of 1, recall of 1, and specificity of 1. As a result, this model can be utilized to lessen the impact of low temperature on the EN’s ability to detect the presence of alcohol in the driver’s inhaled gas, strongly supporting its use in car-sharing drink driving. Other ENs that need to function in frigid conditions can also use this technique. Full article

Breathalyzer is a common approach to measuring blood alcohol concentration (BAC) levels of individuals suspected of drunk driving. Nevertheless, this device is relatively high-cost, inconvenient for people with limited breathing capacity, and risky for COVID-19 exposure. Here, we designed and developed a smart wristband integrating a real-time noninvasive sweat alcohol metal oxide (MOX) gas sensor with a Drunk Mate, an Internet of Thing (IoT)-based alarming system. A MOX sensor acquired transdermal alcohol concentration (TAC) which was converted to BAC and sent via the IoT network to the Blynk application platform on a smartphone, triggering alarming messages on LINE Notify. A user would receive an immediate alarming message when his BAC level reached an illegal alcohol concentration limit (BAC 50 mg%; TAC 0.70 mg/mL). The sensor readings showed a high linear correlation with TAC (R² = 0.9815; limit of detection = 0.045 mg/mL) in the range of 0.10–1.05 mg/mL alcohol concentration in artificial sweat, achieving an accuracy of 94.66%. The sensor readings of ethanol in water were not statistically significantly different (p > 0.05) from the measurements in artificial sweat and other sweat-related solutions, suggesting that the device responded specifically to ethanol and was not affected by other electrolytes in the artificial sweat. Moreover, the device could continuously monitor TAC levels simulated in real-time in an artificial sweat testing system. With the integration of an IoT-based alarming system, the smart wristband developed from a commercial gas sensor presented here offers a promising low-cost MOX gas sensor monitoring technology for noninvasive and real-time sweat alcohol measurement and monitoring. Full article

This article evaluates the driver’s reaction times in a driving simulator environment. The research focused mainly on young drivers under the age of 26, who cause many accidents. Each participating driver provided basic information later used for mathematical-statistical analysis. The main advantage of driving simulators is limitless usage. It is possible to simulate situations that would be unacceptable in real road traffic. Therefore, this study is also able to examine drunk driving. The main goal of the article is to evaluate if gender, practice, or alcohol significantly affected the reaction time of 30 drivers. We also focused on drinking before driving for a smaller number of the drivers; ten of them performed driving under the influence of alcohol. For these mathematical-statistical purposes, we used a one-sample t-test, a paired-samples t-test, an independent-sample t-test, and a correlation analysis together with the assessment of its statistical significance. Full article

This study explored the important factors affecting drunk car/motorbike drivers’ willingness to use and pay for alcohol interlocks. Data were obtained through a survey upon choice-based sampling conducted in central Taiwan. Questionnaires were distributed to the participants of drunk driving and road safety education courses from 17 August to 26 October 2020. All drunk drivers whose driver’s licenses are revoked for drunk driving are mandated to participate in this course. Prior to the survey, the researchers explained the questionnaires, instructed the participants to complete the questionnaires, and then collected all the questionnaires. The socioeconomic characteristics of drunk drivers, awareness of alcohol interlocks and drunk driving, drinking patterns and health self-assessment before and after drunk driving ban enforcement, and changes in the number of trips were investigated. This study applied the double-hurdle model for data analysis to estimate the variables affecting drunk car/motorbike drivers. Results indicate that the respondents who were classified by the Alcohol Use Disorders Identification Test as high-risk drinkers before and after drunk driving ban enforcement were more willing to use alcohol interlocks and to pay higher prices. Additionally, the respondents with declined health self-assessments were also more willing to use alcohol interlocks and pay higher prices. This study suggests offering subsidies for alcohol interlocks to families with financial difficulties, in order to increase the alcohol interlock installation rate. Moreover, since the current duration of license suspension and withdrawal is considerably long, drunk drivers avoid using and installing alcohol interlocks by reducing the number of trips. In other words, the willingness to install alcohol interlocks may be increased by reducing the duration of license suspension and withdrawal. Full article

Despite the existence of many different “Don’t drink and drive” programs and campaigns over the past 30 years, alcohol intoxication has continued to account for approximately one quarter to one third of all traffic crashes and crash-related deaths in the United States. The present study describes a new ‘hands on’ evidence-based approach involving real alcohol-intoxicated subjects using a virtual reality (VR) driving ‘game’ to educate the public more effectively about the dangers of drunk driving. A single demonstration subject ‘drove’ a VR-based portable driving simulator on multiple occasions before (Pre) and at 30 min intervals for up to six hours after either vehicle (no alcohol), two, four or six ‘drinks’ (3, 6, or 9 ounces of 80 proof vodka). The defensive driving task was a choice reaction crash avoidance steering maneuver in which the driver’s task was to determine which way to turn to avoid a crash and then aggressively steer away to avoid a crash. The primary dependent variable was the latency to initiate an avoidance steering response. Blood alcohol concentration (BAC) determinations (estimations) were conducted immediately prior to driving tests using BAC Track portable breathalyzers. Control drives (Pre-Treatment and Vehicle treatment) were characterized by an approximately 300–320 ms reaction time to initiate a crash avoidance. Alcohol increased crash-avoidance reaction time. Peak BAC values were 35, 78 and 120 mg/dL for two, four and six drinks, respectively; the decline in BAC was comparable and linear for all three treatments. There was a strong correlation (r = 0.85) between pre-drive BAC level and reaction time across all of the alcohol-related drives. There was a significant increase in crash avoidance reaction time when the BAC was 50–79 mg/dL, which is below the legally defined BAC limit (80 mg/dL) currently used in most states in the US. These results demonstrate that (1) this VR-based driving simulator task could be a useful ‘hands on’ tool for providing public service demonstrations regarding the hazards of drinking and driving and (2) a BAC concentration of 50 mg/dL represents a reasonable evidence-based cut-off for alcohol-impaired driving. Full article

The purpose of this review is to present an overview of roadside drug testing, driving enforcement, and drunk/drug driving detection around the world. Drunk and drug driving is a severe problem, not only in the UAE, but also around the world. This has important implications for road safety as drunk or drug driving may increase the chances of a driver’s involvement in a road crash when compared to a drug-free driver. Recently, due to increases in drug-impaired drivers’ crash involvement, many mobile roadside drug testing devices have been introduced to the market. These devices use oral fluid, urine or blood matrices. These are on-the-spot tests, which are easy to use and are applied by law enforcement agencies and the public. Law enforcement agencies most commonly use oral fluid to detect the presence of illicit drugs in drivers. This review discusses all the available devices in the market used by the authorities. It also describes the type of drugs widely abused by drivers along with behavioral testing methods. The different types of matrices used for roadside drug testing are also evaluated. Sample collection, storage, and pre-treatment methods are discussed, followed by the confirmatory analysis of positive samples. This article will significantly help law enforcement agencies compare and evaluate all the reliable roadside testing devices and new emerging confirmatory devices available to them in the market. This will help them make an informed decision on which device to adapt to their individual needs. Full article

While drunk driving accidents, which are a serious problem in Taiwan, have decreased in recent years, cases of drunk driving continue to emerge endlessly, and are a source of traffic risks even when the accidents cause no injuries. In order to prevent drunk driving and reduce car accidents, the government has made laws stricter, and has vigorously promoted “designated drivers”. As the concept of designated drivers is not common in Taiwan, this study mainly explores drunk drivers’ understanding of designated drivers in Nantou County and Taichung City, and investigates the willingness of drunk drivers to use and to pay for designated driving services. This study conducted a questionnaire survey on the drunk drivers of the drunk driving and traffic safety training course held at the Motor Vehicles Office. Double-hurdle and tobit models were applied to investigate the issues mentioned above. According to the test results, the tobit model was superior to the double-hurdle model. The estimation results indicated that distance, age, income, family conditions, and drinking habits influence the willingness to use and to pay for designated drivers. Gender, age, family background, and experience in designated driving cause differences in the willingness to use designated drivers in the two regions. It is expected that the conclusion of this study could provide a direction and reference for the future improvement of designated driving services. Full article

This paper analyzes Chile’s drunk driving laws and their effects on car crashes, injuries, and deaths. There were two policy changes. While the 2012 law increased license suspension penalties and decreased the legal blood alcohol limits for drivers, the 2014 law only increased sanctions, including at least one year of actual imprisonment for drunk driving implicated in car crashes with severe injury or death. We use a rich data set of countrywide administrative records that permit us to identify direct measures of alcohol-related accidents, including fatalities and injuries. We also have access to blood alcohol tests to assess whether the laws affected drivers’ alcohol consumption. Using count data models and a rich set of covariates, including police stops and gasoline sales, we find a short-run decrease in accidents and injuries for the 2012 law and a sustained decline in these outcomes for the 2014 law. Neither intervention has an effect on deaths. There is a marginal decline in alcohol consumption after the enactment of both legal changes. However, while the 2012 law only affects male drivers, the 2014 law affects both males and females. No reductions in alcohol intake are found for heavy drinkers. Full article

It is a commonly known fact that both alcohol and fatigue impair driving performance. Therefore, the identification of fatigue and drinking status is very important. In this study, each of the 22 participants finished five driving tests in total. The control condition, serving as the benchmark in the five driving tests, refers to alert driving. The other four test conditions include driving with three blood alcohol content (BAC) levels (0.02%, 0.05%, and 0.08%) and driving in a fatigued state. The driving scenario included straight and curved roads. The straight roads connected the curved ones with radii of 200 m, 500 m, and 800 m with two turning directions (left and right). Driving performance indicators such as the average and standard deviation of longitudinal speed and lane position were selected to identify drunk driving and fatigued driving. In the process of identification, road geometry (straight segments, radius, and direction of curves) was also taken into account. Alert vs. abnormal and fatigued vs. drunk driving with various BAC levels were analyzed separately using the Classification and Regression Tree (CART) model, and the significance of the variables on the binary response variable was determined. The results showed that the decision tree could be used to distinguish normal driving from abnormal driving, fatigued driving, and drunk driving based on the indexes of vehicle speed and lane position at curves with different radii. The overall accuracy of classification of “alert” and “abnormal” driving was 90.9%, and that of “fatigued” and “drunk” driving was 94.4%. The accuracy was relatively low in identifying different BAC degrees. This experiment is designed to provide a reference for detecting dangerous driving states. Full article

Background: The quantitative, measurable detection of drinking is important for the successful treatment of alcohol misuse in transplantation of patients with alcohol disorders, people living with human immunodeficiency virus that need to adhere to medication, and special occupational hazard offenders, many of whom continually deny drinking. Their initial misconduct usually leads to medical problems associated with drinking, impulsive social behavior, and drunk driving. The accurate identification of alcohol consumption via biochemical tests contributes significantly to the monitoring of drinking behavior. Methods: A systematic review of the current methods used to measure biomarkers of alcohol consumption was conducted using PubMed and Google Scholar databases (2010–2015). The names of the tests have been identified. The methods and publications that correlate between the social instruments and the biochemical tests were further investigated. There is a clear need for assays standardization to ensure the use of these biochemical tests as routine biomarkers. Findings: Alcohol ingestion can be measured using a breath test. Because alcohol is rapidly eliminated from the circulation, the time for detection by this analysis is in the range of hours. Alcohol consumption can alternatively be detected by direct measurement of ethanol concentration in blood or urine. Several markers have been proposed to extend the interval and sensitivities of detection, including ethyl glucuronide and ethyl sulfate in urine, phosphatidylethanol in blood, and ethyl glucuronide and fatty acid ethyl esters in hair, among others. Moreover, there is a need to correlate the indirect biomarker carbohydrate deficient transferrin, which reflects longer lasting consumption of higher amounts of alcohol, with serum γ-glutamyl transpeptidase, another long term indirect biomarker that is routinely used and standardized in laboratory medicine. Full article