A. I. Dumitru, T. Girbacia, R. G. Boboc, C. C. Postelnicu, and G. L. Mogan, Effects of smartphone based advanced driver assistance system on distracted driving behavior: a simulator study, Computers in Human Behavior, vol. Since 1902, the not-for-profit, fully tax-paying AAA has been a leader and advocate for safe mobility. The VSC of all drivers was counted, as shown in Figure 11, and the VSC was mainly distributed from 0.309 to 0.728 in free flow and from 0.288 to 0.686 in congested flow. It can be considered that the more orderly the system is, the smaller the information entropy is, and vice versa [46, 47]. In order to quantitatively characterize the influence of cell phone With more than 160,000 new driving events captured every 24 hours, Lytx clients benefit from the industrys most reliable and expansive data set to help them detect and reduce high-risk driving behaviors. The subjects drove the SV from the starting point through different traffic flow scenarios and drove to specific locations to trigger secondary driving tasks, including hands-free calls and video calls, with content designed to be mathematical calculations of equal difficulty. In order to avoid the learning effect, the speed of the LV was set to fluctuate in a small range to simulate the acceleration and deceleration. We harness the power of video to help clients see what happened in the past, manage their operations more efficiently in the present, and improve driver behavior to change the future. The mean value of the correlation coefficient of the corresponding elements of the comparison sequence and the reference sequence is calculated to reflect its association with the reference sequence, which is called the correlation degree, as shown in the following equation. Driving Based on the improved CRITIC method, the weights of visual characteristics indicators in the two traffic conditions were calculated, respectively, and the calculation results are shown in Table 12. The equation for calculating the variation coefficient of the indicator is as follows: Indicator conflict analysis. Driving is a seemingly innocuous part of modern life and, for many, has become second nature. and (mm2) are the pupil area at time and time when the driver is in the free driving state which is not affected by the road speed limit and other vehicles in the pretest, and is the sample size taken in the 30s data window of the pretest. We as humans behave the way we do for one reason: to get what we need and want. Furthermore, the mean RCPA of the video call increased sharply, with growth rates of 47.69% and 72.75%, respectively. The American Automobile Association (AAA) also found that those who drove more during the early pandemic were more likely than average to report recent risky driving behaviors, such as driving without a seat belt or speeding. Compared to alcohol-only users, drivers who admitted to using both were more likely to report such behaviors as: Speeding on residential streets (55%) vs. alcohol-only (35%) Aggressive driving (52%) vs. alcohol-only (28%) Intentional red-light running (48%) vs alcohol-only (32%) Texting while driving (40%) vs. alcohol-only (21%) According to the evaluation criteria of visual stability based on the cluster analysis, the percentage of drivers VSC in each interval for different traffic conditions and driving states is shown in Figure 9.
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