Fees for shipment of hardware may apply. 2, pp. Communication: The Key to Understanding Behaviors For instance, occupational injuries and traffic accidents stem from overlooking long-term fatigue. Drowsy driving is another risky driving behavior and can lead to impaired cognition and performance and motor vehicle crashes. Risky driving behavior No. The equation for calculating the variation coefficient of the indicator is as follows: Indicator conflict analysis. Learn how companies use our solutions to drive impressive results. And in 2021, 13 state legislatures are considering medical or adult-use marijuana legalization bills. Cell phone call operations during driving can lead to distraction and cause potential safety hazards. The correlation degrees of different driving states were consistent with the variation rule of mean VSC, which further verified the validity of the assessment results of VSC. Millennials Are the Riskiest Drivers, Just Ask AAA In 2019, 10,142 people died in drunken-driving crashes. Driving They also engage in various other dangerous driving behaviors far more than drivers who consume either just alcohol or abstain from either drinking alcohol or using marijuana. Finally, the grey correlation analysis method was introduced to verify the assessment effect of VSC. (4)Indicator conflict analysis. The percentage of fixation point offset distance in each interval is shown in Figure 3. Drivers must maintain the same attention to speed, control and alertness as driving on any urban roadway or highway. Du, Improvement of analytic hierarchy process based on grey correlation model and its engineering application, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A-Civil Engineering, vol. 3855, 2021. The IEFA was introduced to represent the drivers visual search span, the PARSV was established to reflect the dynamic balance degree of saccade behavior, and combined with saccade amplitude and RCPA, the influence of the combined effect of traffic conditions and driving states on the drivers visual behavior was comprehensively analyzed. The urban expressway scenario was developed for the simulated driving test to collect eye movement data when the drivers were in different driving states during driving to provide data support for the subsequent analysis of the drivers' visual characteristics. T. A. Dingus, J. M. Owens, F. Guo et al., The prevalence of and crash risk associated with primarily cognitive secondary tasks, Safety Science, vol. The saccade amplitude was mainly distributed from 6.67 to 24.76 in the free flow scenario and from 3.47 to 21.27 in the congested flow scenario. Advertised example rates are returned based on the driver's self-reported data and the driver meeting certain criteria. In order to address the influence of individual differences in the pupil area of drivers, Ding et al. 3, pp. 2672, no. A. Ali Sharifi, Discrete hartley matrix transform precoding-based OFDM system to reduce the high PAPR, ICT Express, vol. As alcohol is ingested, it passes into the bloodstream and accumulates before the liver metabolizes it. Risky Driving Behaviors According to the calculation results of VSC, the K-means clustering method was used to classify drivers VSC into four categories and determine the interval range of four visual stability types [57]. 2: Drug-impaired driving, Risky driving behavior No. Table 2. Archived - Safer Roads campaign highlights too many fatalities 2, pp. The concept of PAPR was introduced into the study of human visual characteristics, and the peak-to-average ratio of saccade velocity (PARSV) was established to reflect the dynamic balance degree of saccade behavior and to represent the stability of individual visual search ability, as defined in the following equation:where PARSV (dB) denotes the peak-to-average ratio of saccade velocity, denotes saccade peak velocity, is the saccade average velocity. The smartphones used in the driving missions were equipped with the WeChat chat application. The VSC calculation equation is as follows:where denotes the VSC, is the weight coefficient of the th visual characteristics indicator, and is the data of the th visual characteristics indicator of the th driver after standardized processing. Each operation lasted about the 50s, with an interval of 5min for the subjects to adjust their state. Manufacturing fear-based trigger-happyresponses to innocent behavior can be deadly. Table 1. By calculating the variation coefficient of each evaluation indicator, the internal variability of the indicator is characterized by the degree of data dispersion. K. L. Young, P. M. Salmon, and M. Cornelissen, Missing links? The equation for calculating the variation coefficient of the indicator is as follows:where denotes the variation coefficient of the th evaluation indicator, is standard deviation, and is the mean value. Furthermore, it estimates that in 2017, 91,000 police-reported crashes involved drowsy drivers, leading to an estimated 50,000 injured and nearly 800 deaths. Y. Yao, X. Zhao, H. Du, Y. Zhang, and J. Rong, Classification of distracted driving based on visual features and behavior data using a random forest method, Transportation Research Record, vol. 2672, no. X. Yang, F. Wang, Y. Wang, T. Zhao, C. Gao, and X. Hu, Are pupils the window of our mind? Due to the differences in density and importance of the information contained in different areas of the driving visual field, drivers often adopt the visual search pattern of selective attention [43]. "Ultimately, knowing what drives us puts us in the driver's seat. The subjects were ensured to have a normal diet and rest without alcohol or drugs for 24h before the test while avoiding strenuous exercise. ( 2012 ) and modified by the author consistent with Indonesian context. A recent study found this to be the case, The distribution of PARSV was similar in the two traffic conditions, and the mean PARSV of drivers in the cell phone operation state was generally increased compared with the normal driving state, and the growth rates of the hands-free call state were relatively low, 2.64% and 0.77% in free flow and congested flow, respectively, while the mean PARSV in video call state increased more, with growth rates of 8.52% and 5.64%, respectively, indicating that the saccade velocity fluctuated greatly and the visual stability decreased during distracted driving. 253262, 2018. However, the distribution of fixation data collected by the eye tracker is discrete, and the pattern is not obvious. The study shows that drivers According to equation (1), the minimum sample size was obtained as 14. In the two traffic conditions, compared with normal driving, the percentage of fixation point offset distance in the medium and long interval above 300px increased significantly, and the percentage in the short interval of 0100px decreased significantly in the video call state, indicating that most drivers were in a state of visual distraction during this process, and needed to shift their eyes frequently between the cell phone screen and the road ahead, expanding the visual search range of the road area to ensure driving safety. In order to explore the individual differences in pupil area, the significance test was performed on the pupil area of the drivers, and the results of one-way ANOVA are shown in Table 9, with significant individual differences in the pupil area of the drivers. At this time, the mutual interference between vehicles was obvious, showing the speed adaptation characteristics, and the road was continuously congested. In the free flow, different types of cell phone call operations had the opposite influence on the IEFA, while the saccade amplitude, PARSV, and RCPA all showed an increasing trend compared to the normal driving state, and the above four types of indicators in congested flow all showed an increasing trend compared to normal driving. There were significant differences in RCPA among drivers in different driving states under different traffic conditions. Risk 56, pp. R. Saha, M. T. Tariq, M. Hadi, and Y. Xiao, Pattern recognition using clustering analysis to support transportation system management, operations, and modeling, Journal of Advanced Transportation, vol. In two traffic conditions, compared to the normal driving state, the VSC generally decreased when drivers were distracted, and the decrease in VSC during video calls was significantly higher than that of hands-free calls, indicating that the video call had a greater negative impact on drivers driving safety. Overall design framework of simulated driving test. There were 697 drowsy-driving-related crashes in 2019, according to the NHTSA. By calculating the correlation coefficient between evaluation indicators and taking the absolute value, the conflict between indicators is measured. The NHTSA says buckling up is the most effective way to protect yourself in a crash. Nowadays, many countries regulate the use of cell phones while driving and most explicitly prohibit hand-held calls, but there are no clear requirements for other cell phone call methods [27, 28]. Webrisky driving episode. K. Lipovac, M. Deric, M. Tesic, Z. Andric, and B. Maric, Mobile phone use while driving-literary review, Transportation Research Part F: Traffic Psychology and Behaviour, vol. Y. Sha, J. Hu, Q. Zhang, and C. Wang, Systematic analysis of the contributory factors related to major coach and bus accidents in China, Sustainability, vol. The authors declare that they have no conflicts of interest. Percentage of fixation point offset distance in each interval for different traffic conditions and driving states.
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