Lecca, Luigi I.;Fadda, Paolo;Fancello, Gianfranco;Medda, Andrea;Meloni, Michele
Safety and Health at Work
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v.13
no.2
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pp.148-154
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2022
Background: Bus driving is a mentally demanding activity that requires prolonged attention to ensure safety. The aim of the study was to assess mental fatigue caused by driving a public bus and to find a profile of workers at higher risk. Methods: We evaluated changes of critical flicker fusion (CFF) (index of central arousal) and heart rate variability (HRV) (index of autonomic balance) in a 6-hour driving shift on a real route, in 31 professional bus drivers, and we tested the influence of personal factors such as sleep quality, BMI, and age. Paired t-test was used to test differences of CFF and HRV between both initial and final phase of driving, while multiple linear regression tested the influence of personal variables on the indexes of mental fatigue. Results: Results showed that CFF significantly decreased after 6 hours of bus driving (41.91 Hz, sd 3.31 vs. 41.15 Hz, sd 3.15; p = 0.041), and heart rate significantly decreased in the final phase of driving, with respect to the initial phase (85 vs. 78 bpm, p = 0.027). Increasing age (beta = -0.729, p = 0.022), risk of obstructive sleep apnea syndrome (beta = -0.530, p = 0.04), and diurnal sleepiness (beta = -0.406, p = 0.017) showed a significant effect on influencing mental fatigue. Conclusion: Elderly drivers at higher risk of sleep disorders are more prone to mental fatigue, when exposed to driving activity. Monitoring indexes of central arousal and autonomic balance, coupled with the use of structured questionnaires can represent a useful strategy to detect profile of workers at higher risk of mental fatigue in such duty.
In roadside workplaces, more attention should be paid to the safety of workers. The roadside workers underestimate the effect of the brightness of their clothes and judge that drivers will recognize them easily, and the drivers misjudge that the roadside workers are far away and that the vehicle can be stopped in sufficient time. Therefore, customized safety education reflecting this and wearing work clothes with certified visibility functions are required. In Korea, it is not compulsory for roadside workers and vehicle guide attendants to wear work clothes with a visibility function. In this study, the distance ahead perceived by drivers was measured using manikins wearing certified and non-certified reflective safety vests. The perception distance of the non-certified reflective safety vest was 1.4 times longer than that of the certified reflective safety vest, thus confirming the importance of wearing a certified reflective safety vest. To prevent roadside workers from suffering traffic accidents, we propose the enactment of a law that makes it mandatory for them to wear high-visibility safety clothing. Specifically, Article 32 of the Enforcement Regulation of the Road Traffic Act should include high-visibility safety clothing in life protection equipment, and additionally, to prevent secondary accidents, we propose the enactment of a law requiring the installation and wearing of certified reflective safety vests in vehicles.
The development of autonomous driving and Advanced Driver Assistance System (ADAS) technology has grown rapidly in recent years. As most traffic accidents occur due to human error, self-driving vehicles can drastically reduce the number of accidents and crashes that occur on the roads today. Obviously, technical advancements in autonomous driving can lead to improved public driving safety. However, due to the current limitations in technology and lack of public trust in self-driving cars (and drones), the actual use of Autonomous Vehicles (AVs) is still significantly low. According to prior studies, people's acceptance of an AV is mainly determined by trust. It is proven that people still feel much more comfortable in personalized ADAS, designed with the way people drive. Based on such needs, a new attempt for a customized ADAS considering each driver's driving style is proposed in this paper. Each driver's behavior is divided into two categories: assertive and defensive. In this paper, a novel customized ADAS algorithm with high classification accuracy is designed, which divides each driver based on their driving style. Each driver's driving data is collected and simulated using CARLA, which is an open-source autonomous driving simulator. In addition, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) machine learning algorithms are used to optimize the ADAS parameters. The proposed scheme results in a high classification accuracy of time series driving data. Furthermore, among the vast amount of CARLA-based feature data extracted from the drivers, distinguishable driving features are collected selectively using Support Vector Machine (SVM) technology by comparing the amount of influence on the classification of the two categories. Therefore, by extracting distinguishable features and eliminating outliers using SVM, the classification accuracy is significantly improved. Based on this classification, the ADAS sensors can be made more sensitive for the case of assertive drivers, enabling more advanced driving safety support. The proposed technology of this paper is especially important because currently, the state-of-the-art level of autonomous driving is at level 3 (based on the SAE International driving automation standards), which requires advanced functions that can assist drivers using ADAS technology.
KSCE Journal of Civil and Environmental Engineering Research
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v.42
no.2
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pp.219-227
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2022
In Korea, as the aging phenomenon accelerates, the problem of traffic accidents related to the elderly is continuously emerging. Efforts to improve this are being implemented, but unfortunately the results of these effects are not clear. Therefore, in this study, the effect of traffic characteristics and incentive policies on the return of driver's licenses of elderly drivers was reviewed. As a result of the analysis, it was confirmed that the intention to return the driver's license was low in the case of men, older people, those with low dependence on public transportation, those who undertook long driving hours, and those who took frequent trips. On the other hand, financial incentives were found to play a positive role with regard to the intention to return the driver's license. However, the effect is expected to be insignificant for those with a low intention to return the driver's license. As a result, under the current policy, it is predicted that there is a limit to improving the social problems caused by elderly drivers, meaning that it is necessary to review approaches that induce the return of their driver's licenses.
KSCE Journal of Civil and Environmental Engineering Research
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v.30
no.3D
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pp.231-240
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2010
As majority of the traffic accidents in intersections is caused by human factor, a close examination is required on its contributing factors through measuring the psychological and physiological response according to the driving characteristics of the drivers and the road conditions. In this study, for the safety evaluation of individual intersection considering human factors of the drivers, electroencephalography reaction was measured utilizing cutting-edge measuring equipment and survey on drivers' cognitive characteristics in ordinary times and while driving test was conducted. The relationship between the electroencephalography response when approaching the intersection and cognitive evaluation survey data in driving test was clarified, and individual intersection safety evaluation model was built considering cognitive evaluation factor and the reaction of a bio-response electroencephalography data. As a result, I could find out that cognitive evaluation was made through the reaction of a bio-response (Electroencephalography) process because electroencephalography reaction of a bio-response showed differently by the physical characteristics of the intersection and cognitive evaluation had a difference.
Journal of Korean Society of Industrial and Systems Engineering
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v.46
no.4
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pp.39-52
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2023
In this study, project information of government-funded research institute in the food field was collected and analyzed to systematically identify the factors affecting the process of transferring technological achievements of public research institute to the private sector. This study hypothesized that human resources, financial resources, and technological characteristics as input factors of R&D projects affect output factors, such as research papers or patents produced by R&D projects. Moreover, these outputs would serve as drivers of the technology transfer as one of the R&D outcomes. Linear Regression Analysis and Poisson Regression Analysis were conducted to empirically and sequentially investigate the relationship between input factors and output and outcome of R&D projects and the results are as follows: First, the principle investigator's career and participating researcher's size as human resource factors have an influence on both the number of SCI (science citation index) papers and patent registration. Second, the research duration and research expenses for the current year have an influence on the number of SCI papers and patent registrations, which are the main outputs of R&D projects. Third, the technology life cycle affects the number of SCI papers and patent registrations. Lastly, the higher the number of SCI papers and patent registrations, the more it affected the number of technology transfers and the amount of technology transfer contract.
Smart cars, which incorporate information and communication technologies (ICT) to improve driving safety and convenience for drivers, have recently emerged. However, the increasing risk of automotive cybersecurity due to the vulnerability of electronic control units (ECUs) and automotive networks, which are essential for realizing the autonomous driving functions of smart cars, is a major obstacle to the widespread adoption of smart cars. Although there have been only a few real-world cases of smart car hacking, drivers' concerns about the security of smart cars can have a negative impact on their proliferation. Therefore, it is important to understand the risk factors perceived by drivers and the trust in smart cars formed through them in order to promote the future diffusion of smart cars. This study examines the risk factors that affect the formation of trust in smart cars, focusing on security and privacy, and analyzes how these factors affect safety perceptions and trust in smart cars.
Mallikarjun, Sajjanshetty;Rao, Ashwini;Rajesh, Gururaghavendran;Shenoy, Ramya;Mithun, Pai B.H.
Asian Pacific Journal of Cancer Prevention
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v.15
no.19
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pp.8265-8270
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2014
Background: Smoking tobacco is considered as a leading cause of preventable death, mostly in developing countries like India. One of the primary goals of international tobacco control is to educate smokers about the risks associated with tobacco consumption. Tobacco warning labels (TWLs) on cigarette packages are one of the most common statutory means to communicate health risks of smoking to smokers, with the hope that once educated, they will be more likely to quit the habit. Materials and Methods: The present survey was conducted to assess the effectiveness of TWLs in communicating health risks of tobacco usage among 263 adult smokers working as bus drivers in Karnataka State Road Transport Corporation (KSRTC), Mangalore, India. Information was collected on demographic details, exposure and response to health warnings on tobacco products, intention to quit and nicotine dependency. Results: The majority (79.5%) of the respondents revealed negative intentions towards quitting smoking. Nearly half of the participants had a 'low' nicotine dependency (47.5%) and 98.1% of the respondents had often noticed warning labels on tobacco packages. These health warnings made 71.5% of the respondents think about quitting smoking. Respondents who noticed advertisement or pictures about dangers of smoking had better knowledge, with respect to lung cancer and impotence as a consequence of tobacco. A higher exposure to warning labels was significantly associated with lower nicotine dependency levels of smokers among the present study population. A significantly higher number of respondents who noticed advertisement or pictures about the dangers of smoking thought about the risks of smoking and were more inclined to think about quitting smoking. As exposure increased, an increase in the knowledge and response of participants was also observed. Conclusions: Exposure to tobacco warning labels helps to educate smokers about health risks of tobacco smoking. It may be possible to promote oral health among bus drivers by developing strategies to educate them about these risk factors.
When it comes to the process of information storage, people are likely to organize individual information into the forms of groups rather than independent attributes, and put them together in their brains. Likewise, in case of finding the shortest path, this study suggests that a Hierarchical Road Network(HRN) model should be selected to browse the most desirable route, since the HRN model takes the process mentioned above into account. Moreover, most of drivers make a decision to select a route from origin to destination by road hierarchy. It says that the drivers feel difference between the link travel tine which was measured by driving and the theoretical link travel time. There is a different solution which has predicted the link travel time to solve this problem. By using this solution, the link travel time is predicted based on link conditions from time to time. The predicated link travel time is used to search the shortest path. Stochastic Process model uses the historical patterns of travel time conditions on links. The HRN model has compared favorably with the conventional shortest path finding model in tern of calculated speeds. Even more, the result of the shortest path using the HRN model has more similar to the survey results which was conducted to the taxi drivers. Taxi drivers have a strong knowledge of road conditions on the road networks and they are more likely to select a shortest path according to the real common sense.
The Korean government introduced an automated speed enforcement system (ASES), which uses traffic enforcement cameras, to counteract safety issues that are caused by speeding. As the information of the traffic enforcement camera locations is provided to the drivers via navigation systems and mobile applications in a timely manner, drivers can avoid enforcement by momentarily diminishing their speeds only near the camera locations. To prevent drivers' evasional behavior and improve the effectiveness of ASES, section control, which enforces speeding vehicles by measuring their average travel speeds over a stretch of road and checking against the speed limit, has been recently implemented. In this study, Section Speed Enforcement Zone and Comparison Zone are compared in terms of traffic stream characteristics under free flow conditions. To this end, loop detector data were obtained from the three study sites and analyzed. The study results demonstrated that drivers maintain their speeds below the speed limit over the enforcement section with a lower variance of speeds.
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