10 A/m
The driving task should not be too long in order to avoid fatigue and boredom, but not too short in order to be able to extract relevant results. Participants need to be monitored in case they experience simulator sickness during the practice session and in the study itself. A subjective evaluation of the experiment, for example, using questionnaires to better understand how the experiment influenced the driver’s psychological state (e.g., discomfort, fatigue, workload, frustration, mind wandering, and so on), can be beneficial and generate other valuable insights.
Therefore, punctual research studies that focus on a particular subject or concern are frequently carried out over a shorter period and might utilize a smaller sample size and a limited number of techniques to gather data. These studies might also look at the efficacy of measures taken to reduce the harmful effects caused by particular driving distractions. On the other hand, in order to gain a thorough understanding of a specific topic, it is crucial to gather a large amount of data over time and under different driving conditions, which, in turn, can reveal significant trends and patterns.
Certain limitations need to be mentioned for this review. First, since the use of the mobile phone while driving is a widely studied field of research, it is possible that some relevant articles may have been missed even after a rigorous search of the literature. The review was limited to excluding studies published in conference proceedings or book chapters, as well as those published in languages other than English. Some shortcomings are related to the data, which were not fully reported in several papers. There are also methodological limitations, including the lack of valid and reliable measures to assess the effects of TWD, the use of small samples, the duration of experiments, and so on.
The proposed recommendations aim to offer guidelines for experiments using a driving simulator. However, they cannot consider all the possible scenarios that could be investigated. The suggested minimum requirements are based on the knowledge gained from the literature review analysis and on our partially subjective vision of driving simulators. It can be argued that a consensus regarding this topic will, perhaps, never be reached, as researchers will just use the infrastructure available.
This study presents the results of a review of the literature using a structured search to examine drivers’ use of mobile phones and wearable devices concerning simulated driving. Through a rigorous selection process, fifty-nine studies published in the past 20 years were extracted, analyzed, and classified into four categories. Advanced driving simulators with a motion system were used in less than 20% of the studies due to the high costs and complexity of operation and maintenance. According to [ 132 ], studies that include low-cost simulators to identify and analyze the driver’s performance can offer meaningful and even similar findings as those obtained from experiments with advanced driving simulators. Nonetheless, the lack of a motion platform significantly affects the realism of the simulated scenario, as the participant cannot experience the vehicle’s inertia when accelerating or when negotiating a curve.
Mobile phone use in the vehicle is a major component of distracted driving that requires drivers to take their eyes off the road and one or both hands off the steering wheel, thus impairing their driving performance and increasing the likelihood of crashes [ 133 ]. Most studies reached the conclusion that activities such as texting a message on the phone, manipulating the phone, or the use of different types of phone-connected devices can introduce cognitive, manual, visual, or even auditory distractions [ 134 ] that can have serious negative effects on drivers’ attention and concentration, and this can lead to serious traffic incidents [ 135 ].
Many studies based on driving simulators show that performing secondary tasks (such as manual input) while driving leads to a compromised driving performance [ 17 , 18 , 19 , 32 , 70 , 101 , 136 ]. Distraction can be achieved by removing the driver’s gaze from the road. However, cognitive distractions can be just as dangerous by taking his/her mind away from the driving process [ 137 ].
The ubiquity of mobile phones; the increasing number of traffic participants; and their need/desire to engage in secondary tasks, such as games, texting, or social media, could have a negative effect on road safety, despite the integrated or mobile driver assistance systems. This review can serve as a basis for regulators and interested parties to propose restrictions related to using mobile phones in a vehicle and improve road safety. It also points out the significance of informing drivers about the dangers of using mobile phones while driving and the importance of enforcing strict rules and sanctions for those who have a habit of doing this. Moreover, the study provides researchers with an overview of the types of distractions that can affect the driver at a cognitive, visual, manual, or auditory level, as well as the measures that can be used to predict and analyze those distractions. The review recommends that future research should concentrate on creating more sophisticated driver assistance systems and technologies that can better detect and prevent distractions caused by TWD.
Future research should focus on finding a consensus regarding driving-simulator studies that will enable scholars to directly compare their work with similar studies, thus ensuring high validity of results, especially in the context of automated driving.
An overview of driving simulators characteristics and classification ( n = 67).
ID | Ref. | NP | Sample Characteristics | Driving Simulator Class | LSR (km) | TD | MT | Type of Device—Distraction Task | Findings |
---|---|---|---|---|---|---|---|---|---|
1 | [ ] | 35 | NR; 22.5; NR; 21–14 | B | 2,65 | V, C, M | TrVs, DM | HH—texting | Based on vehicle dynamics, it is possible to identify specific distraction tasks with a level of accuracy that is adequate. |
2 | [ ] | 25 | 22–33; 25; 2.6; NR | A | NR | V, M, C | OMs | HF—destination entry | In comparison to the primary visual-manual interaction with the Samsung Touch interface, voice entry (from Google Glass and Samsung) resulted in lower subjective workload ratings, lower standard deviation of lateral lane position, shorter task durations, faster remote Detection Response Task (DRT) reaction times, lower DRT miss rates, and less time looking off-road. |
3 | [ ] | 134 | 20–30, 65–75; 23.2, 70.0; 2.8, 3.0; 23–40, 39–22 | A | 25.7 | V, Au + A | DM | HF—typing a number into a keypad, conversation with a car passenger, memorizing | Braking responses are affected by distractions, and this effect can last for up to 11.5 s. |
4 | [ ] | 31 | 18–47; 25.61; 6.24; 16–15 | A | NR | V, C, M | TrVs | HH—received and answered text messages | Any mobile gadget, like a smartwatch, smartphone, or voice assistant, could affect how well you drive, especially if you have to pay attention to it when your eyes are off the road. |
5 | [ ] | 24 | NR; 33, 26.3; NR; 8–4, 8–4 | B | NR | V, C, Au | DM | HF—receives traffic information | The two other systems required the participants to glance away from the road (too) long, endangering their safety, and reading an SMS took longer than scanning a PDA. The auditory information provision system, however, provided for the best driving performance. |
6 | [ ] | 39 | 19–32; 21.5; 2.6; 27–12 | A | NR | V, C, M | TrVs | HF—respond to a call, replay several WhatsApp messages, use Instagram | Young drivers who use mobile phones while operating a vehicle experience impairments that limit their ability to control the vehicle. |
7 | [ ] | 53 | 22–34; 25.25; 3.08; 37–16 | B | 3 | V, C, M | RT | HH—speech-based texting and handheld texting (two difficulty levels in each task) | Drivers undertake risk-compensation behavior by extending time headway in order to offset the higher accident risk associated with using a mobile phone while driving. Drivers perceive a rise in accident risk during distracted driving. |
8 | [ ] | 41 | <25, 26–40, >41; NR; NR; 30–11 | B | 20 | V, M + A | DM, OMs | HF—enter the application interface of 3, 4, or 6 icons | In the HMI design of in-vehicle information, there is a statistically significant difference in driver perception reaction time for varying numbers of icons (IVI). |
9 | [ ] | 100 | <30, 30–50, >50; 24.14, 36.05; 54.67; 2.79, 5.43, 5.04; 87–13 | B | 3.5 | V, C | DM | HH—simple conversation, complex conversation, and simple-texting and complex-texting tasks | Both talking on the phone and texting while driving impair a driver’s ability to pay enough attention to the road ahead, to react appropriately to unexpected traffic situations, and to control the car within a lane and in relation to other vehicles. |
10 | [ ] | 100 | <30, 30–50, >51; 24.14, 36.05, 54.68; 2.79, 5.43, 5.05; 87–13 | B | 3.5 | V, C + RC, T | RT | HH—simple conversation, complex conversation, and simple-texting and complex-texting tasks | Simple conversations, complicated conversations, basic texts, and complex texts all increased reaction times for pedestrian crossing events by 40%, 95%, 137%, and 204%, respectively. For parked car crossing events, the tasks increased reaction times by 48%, 65%, 121%, and 171%, respectively. |
11 | [ ] | 100 | <30, 30–50, >52; 24.14, 36.05, 54.69; 2.79, 5.43, 5.06; 87–13 | B | 3.5 | V, C + A, G | DM, AP | HH—simple conversation, complex conversation, simple texting and complex texting tasks | When engaged in conversation or texting duties, the drivers significantly decreased their mean speed by 2.62 m/s and 5.29 m/s, respectively, to offset the increased strain. |
12 | [ ] | 49 | 22.12, 37.62; 22.12, 37.62; 2.45, 7.22; 22–3, 25–0 | B | 3.5 | V, C + A, E | DM | HH—simple conversation, complex conversation, simple texting and complex texting tasks | Younger drivers are less able to compensate for distractions while driving and have poorer longitudinal control. |
13 | [ ] | 90 | <30, 30–55; 25.31, 37.00; 2.74, 6.29; 83–7 | B | NR | V, M + A | DM, RT | HH—conversation, texting, eating, music player | Most of the drivers (72.06%) reported texting as an extremely risky task |
14 | [ ] | 14 | 18–22; NR; NR; | B | NR | C, M | DM | HH—cell phone conversation, back seat conversation, text message, Ipod manipulation | The iPod task and all wireless communication tasks caused a noticeable increase in speed variability throughout the driving scenario. |
15 | [ ] | 49 | 19–65; 35.63; 14.26; 32–17 | B | 50 | V, C + A, G | OMs | HH—reading and comprehension task (three types of display) | Warnings took longer to read and comprehend (4 s on average), compared to recommendations. |
16 | [ ] | 40 | 19–23; 21; NR; 20–20 | B | 51.5 | V, M | DM, RT | HH—text messaging | Simulated driving performance suffers when texting while operating a vehicle. This detrimental effect seems to be more severe than the consequences of using a cell phone for conversations while driving. |
17 | [ ] | 17 | NR; 25.88; 5.82; 14,3 | B | NR | V, M | TrVs, DM | HH—accessing social network on the smartphone | Even when the driver is distracted, using an in-vehicle smartphone ADAS application has enhanced driving performance in a simulator.. |
18 | [ ] | 101 | 18–57; 27.8; 8.3; 68,33 | A | NR | C, V, M | DM | HH—using a handheld cell phone; texting; eating | Regardless of their prior experience, multitasking while driving and distracting activities have a negative influence on driving performance for both genders and all age groups. The main factor that negatively affected driving performance was texting. |
19 | [ ] | 56 | 21–30; 25.13; 2.57; 41–15 | B | 3 | V, C, M | RT | HF, HH—speech-based and handheld texting | Compared to the baseline, handheld texting tasks caused a delayed reaction to the unexpected braking occurrences. |
20 | [ ] | 26 | 22–31, 22–29; 25.5, 23.9; 3.33, 2.27; 3–3, 20–0 | B | NR | V, M + A | RT, DM | HH—receive notification | The use of smartwatches could affect traffic safety. There may be a discrepancy between drivers’ actual performance and their views regarding using a wristwatch while driving, given that participants generally believed that smartwatch use resulted in similar or fewer traffic fines than smartphone use. |
21 | [ ] | 48 | 20–79, 19–66; 34.8, 35.3; 16.0, 13.9; 17–7, 16–8 | C | NR | V | OMs | HH—email reading, view-switching, song searching, email replying | Compared to using standard smartphone apps, an automotive-specific application reduced the visual demand and visual distraction potential of in-car duties. |
22 | [ ] | 63 | 25–66, 8–18; NR; NR; 32–31 | D | NR | V, M + A | DM | HH, HF—answer incoming calls, dialing, retrieve a voicemail message from a specific person using either the handheld or hands-free phone | Teenagers were shown to adopt risky following distances, to drive poorly, and to be more easily distracted by handheld phone tasks than adults. |
23 | [ ] | 36 | NR; 20.95; 2.36; 16,10 | C | 6.8 | V, C, M | RT, DM | HH—social media browsing | Performance is impacted by both texting and using social media, but texting while driving is more harmful. |
24 | [ ] | 20 | 18–21; NR; NR; 12,8 | C | 8 | V, M | DM, HA | HH—retrieve and send text messages | Text messaging has negative consequences on driving ability, which could explain the higher crash risks. |
25 | [ ] | 24 | 18–64; 32.1; 12.5; 10,14 | A | 3.55 | V, M | DM | HH—manual dialing, voice-dialing | When participants utilized voice-activated dialing as opposed to manual dialing, there were 22% fewer lane-keeping mistakes and 56% fewer looks away from the road scene. |
26 | [ ] | 40 | 20–52; 32.5; NR; 11,29 | B | NR | V, C | OMs | HH—touching the touch-screen telephone menu to a certain song, talking with laboratory assistant, answering a telephone via Bluetooth headset, and finding the navigation system from Ipad4 compute | The attention of the driver is substantially diverted from the road when engaging in secondary tasks while driving, and the evaluation model used in this study could accurately predict driving safety under various driving circumstances. |
27 | [ ] | 24 | 20–45; 33.43; 6.32; 22–2 | A | NR | V | DM, RT | HF—ordering, route check, destination search | Usability and driving safety were higher when the phone was placed on the left side of the steering wheel as opposed to the right. |
28 | [ ] | 29 | NR; 56.6, 55.9; 4.1, 3.0; 16, 13 | A | NR | V, M, N | RT, OMs | HH—sending a text message, searching navigation | When driving while sending a text message or using navigation, the jerk-cost function, medial-lateral coefficient of variation, and braking time were all higher than when driving alone. |
29 | [ ] | 20 | 27–59; 37.65; 9.75; 14,6 | B | 10 + 9 | V, M, C | DM, OMs | HH—conversation, texting, destination entry, following route guidance | Only when individuals engaged in visual-manual tasks, such as texting and entering a location, when they frequently glanced away from the forward road, did lateral performance decline. |
30 | [ ] | 30 | 18–30; 22.7; 3.51; 15,15 | A | 13 | C, M | DM, TrVs | HH—“temptation to text” | The “Temptation to Text” condition revealed noticeably more workload. Similarly, it was discovered that texting while driving drastically reduced vehicle performance. |
31 | [ ] | 20 | 23–30; 26.20; 2.58; 10,10 | A | NR | C, M | TrVs, DM, ALs, RT | HF—conversation, HF cognitive demanding conversation, texting | Comparatively to legal BAC limits, very basic mobile phone conversations may not pose a substantial risk to driving, but cognitively taxing hands-free talks and, most notably, texting, do pose significant dangers. |
32 | [ ] | 41 | 18-61; 31; 9.7; 23,18 | B | 5 | C + G | ALs | HF, HH—conversation | Drivers’ decisions regarding accepting gaps were unaffected by the distraction task, although the crossing’s completion time increased by over 10% in comparison to the baseline. Also, when using a phone at an intersection, drivers exhibited conservative behavior, slowing down more quickly, waiting longer, and keeping a greater distance from the vehicle in front of them. |
33 | [ ] | 29 | 22–49; 30; 6; 15,14 | A | 1 | V, M | DM | HH—help, browse, filter task | The filtering task’s slider widget was overly demanding and hindered performance, whereas kinetic scrolling produced an equal amount of visual distraction although requiring less precise finger pointing. |
34 | [ ] | 15 | NR; 28; 4.08; 12,3 | A | NR | C, V, M | OMs | HH—button, slider, Insert data, dropdown, radio buttons | When evaluating the mental workload related to wide differences in task complexity in terms of the amount of information to be processed, a commercial BCI device may be helpful. |
35 | [ ] | 60 | 16–17; 16.8; 0.4; 20, 40 | B | NR | V, M + G | OMs | HH—looking at the phone, picking up the phone, taking a picture, sending the picture, hand manipulation of phone (mimicking writing a text), answering a call, and looking at a picture on the phone | Self-reported distracted driving habits grew with time, with a significant effect of visit on self-report outcomes. |
36 | [ ] | 28 | 18–28; 21.0, 2.4; _; 16,12 | B | 1.1–1.5 | V, M | DM | HH—type and send a text message vs,. tunning car radio | Even in the simplest of driving situations, multitasking while operating a motor vehicle can have a negative impact on performance and increase risk. Comparing text messaging to other in-car activities like changing the radio, text messaging may present a “perfect storm” of risks. |
37 | [ ] | 18 | 18–22; 20.4; NR; NR | C | NR | V, M | RT | HH—text messaging, reading Facebook posts (text/self-paced), exchanging photos via Snapchat, and viewing updates on Instagram | When compared to the image-based scenario (mean = 0.92 s) and the baseline, the brake reaction times (BRTs) in the text-based scenarios were substantially longer (mean = 1.16 s) (0.88 s). Both the task-pacing impact and the difference between BRTs in the image-based and baseline conditions were not statistically significant. |
38 | [ ] | 64 | 22–60; 33; 10; 34, 30 | D | NR | V, C | RT | HH—reading, texting, video, social media, gaming, phoning, music | Reaction times did decrease when performing non-driving related tasks (NDRTs), suggesting that the NDRT assisted the drivers in keeping their focus during the partially automated drive. Drowsiness and the NDRT’s motivational appeal thus raised situation criticality, whereas the NDRT’s cognitive load decreased it. |
39 | [ ] | 35 | 18–29; 22.9; 4.0; 22, 13 | D | 10 | V, M, C + RC | DM | HF, HH—calling, texting vs. road environment | Compared to distraction from a cell phone or other road elements like pedestrians and approaching vehicles, road geometry has a greater impact on driver behavior. |
40 | [ ] | 35 | 18–29; 22.9; 4.0; 22, 13 | D | NR | V, M, C | OMs | HH—ring a doctor and cancel an appointment, text a friend and tell him/her that the participant will be arriving 10 min late, share the doctor’s phone number with a friend, and take a ‘selfie | The three types of self-regulation that distracted drivers use most frequently are tactical, operational, and strategic. |
41 | [ ] | 50 | 27–55; 36.8; 5.8; 50,0 | D | NR | V, M, C | DM | HH—driving while having a conversation on the mobile phone, driving while reading out loud text messages and driving while texting | The “reading of text messages” and “texting” had a big impact on the “change of the steering position per second. For all three cell phone assignments, a substantial main effect was seen in terms of “following distance per second” and “change of the lateral lane position per second”. |
42 | [ ] | 90 | NR; NR; NR; 73,17 | A | 3.6 | C, V | DM, RT, TrVs | HH—using the mobile phone, drinking and text messaging | The disruptive variables have a negative impact on road safety due to cognitive distraction and mobility limitation (e.g., longer response times and more errors), on the one hand, and have a bad impact on the environment and the economy (e.g., increased fuel consumption), on the other. |
43 | [ ] | 36 | 21–54; 33.3; 8.6; 21–15 | B | 4.8 | V, Au | DM, RT | HF—features presented via a mobile phone mounted near the line of sight | The findings indicated that new features with the greatest levels of urgency and criticality, such as Emergency Vehicle Warning (EVW) and Emergency Electronic Brake Lights (EEBL), would improve safety and make it easier for emergency vehicles to reach their intervention site. |
44 | [ ] | 36 | NR; NR; NR; 18,18 | A | NR | V, C, M, Au | RT, DM, OMs | HH—smartwatch vs. smartphone calling | By using a phone instead of just driving, participants shown increased off-road visual attention. |
45 | [ ] | 32 | 17–21; 19.0, 19.3; NR; 7,9 | B | NR | V, M | DM, TrVs, RT | HH—manipulating controls of a radio/tape deck and dialing a handheld cellular phone | The time spent on tasks was marginally longer for participants who anticipated dangers compared to those who did not, but the difference was stable across tasks. |
46 | [ ] | 45 | NR; 62.8, 24.3; 7.2, 4.8; 30–0, 11–4 | B | NR | V, P | DM, OMs | HH—texting on a smartphone and while sitting on a stable or unstable surface | When drivers were texting, the perceived workload increased, but balancing training decreased it. While seated on the unsteady surface, perceived workload was higher; however, it decreased after balance training. |
47 | [ ] | 40 | NR; 20.47; 4.76; 24, 16 | B | 8.04 | V, M | DM, RT | HH—use Google Glass or a smartphone-based messaging interface | Glass-delivered messages served to reduce distracting cognitive demands, but they did not completely remove them. Comparatively speaking to driving when not multitasking, messaging while using either gadget impairs driving. |
48 | [ ] | 37 | 18–33; 24.7; 3.6; 20–17 | B | NR | V | DM, RT, AP | HF—navigating on the Facebook newsfeed, reading and sending text messages in Facebook Messenger, searching for a location in Google Maps | Web browsing and texting-related distraction raise the likelihood of an accident, the headway, and the lateral distance deviation by 32%, 27%, and 6%, respectively. |
49 | [ ] | 123 | 18–64; 34.46; 13.04; 62,61 | B | 26.4 | V, Au | DM, OMs | HH—audio warning, flashing display | There was no difference in the number of vehicles overtaken between the groups, and the existence of the speed warnings had no effect on overtaking. |
50 | [ ] | 34 | 16–18; 17.25, 17.09; 0.99, 0.89; 12–4, 14–4 | B | 8.04 | C, M | DM, RT, TrVs | HH—conversing on a cell phone, text messaging | Compared to the no task and the cell-phone task, the lane position varied significantly more while texting. Teens with ADHD spent noticeably less time to finish the scenario while texting in particular. There were no discernible group-wide major effects detected. |
51 | [ ] | 50 | 24–54; 39.8; 8.4; 49, 1 | B | 36.2 | C, M, V | TrVs, DM, OMs | HH—cell phone conversation, text message interaction, emailing interaction | Poorer driving performance was associated with more visually demanding jobs. Yet, using a cell phone caused fewer off-road eye looks. Drivers who described themselves as “extremely skilled” drove less well than those who described themselves as “talented.” |
52 | [ ] | 75 | 16–18, 19–25; 17.67, 23.39; 1.18, 1.81; 11–19, 23–22 | B | 38,6 | C, M + T | TrVs, DM | HH—cell phone, texting | Texting generally resulted in more lane deviations and collisions. Text messaging was the most common form of distraction, which had a major negative influence on traffic flow. As a result, participants’ speeds fluctuated more, changed lanes less frequently, and took longer to finish the scenario. |
53 | [ ] | 32 | 18–25; 20.6; 2.1; 32–0 | D | 13 | V | DM, TrVs | HH—gamified boredom intervention | The gamified boredom intervention promoted anticipatory driving while reducing risky coping strategies like speeding. |
54 | [ ] | 36 | NR; 28.44; 9.26; 30,6 | A | NR | C, V, M | DM | HH—conversation, texting | Driver performance in the longitudinal and lateral control of the vehicle for the texting event significantly declined during the texting task. |
55 | [ ] | 37 | NR; 21; 3.63; 11,26 | B | NR | C, Au | DM, OMs | HH—text-message distractions | For at least 10 s but no more than 30 s following the text message alert, situation awareness is negatively impacted. Participants’ mean speed increased during periods of distraction in the 10 s after receiving a mobile phone notification, which also resulted in a decrease in context awareness. |
56 | [ ] | 27 | 24–59; 42.4; 9.1; 11, 16 | B | 4.4 | V, M + A, E | DM, OMs | HH vs. dashboard—texting with the smartphone in one hand (handheld drive) and texting while the phone is placed in a dashboard mount | Texting while driving when using a dashboard-mounted device impairs driving safety at least as much as texting while using a handheld device. |
57 | [ ] | 40 | NR; 28; 12.6; 10,30 | A | NR | V, M + E | DM | HH—texting | Mobile phone texting dramatically reduced the ability to drive. Driving experience had no bearing on the results, however highly skilled phone users’ texting use had a noticeably reduced negative impact. |
58 | [ ] | 40 | NR; 18.6; 1.8; 11–29 | B | NR | V, M, C | DM, OMs | HF, HH—conversation, texting, selecting a song | Although the amount of interference varied depending on the task, hands-free smartphone call created substantially less interference than texting and listening to music on an MP3 player. |
59 | [ ] | 60 | NR; 19.74; 2.4; 30,3 | A | 8.04 | C, M | OMs | HF—conversation, texting | Driving while texting was similar to driving while not doing anything. The results of this study highlight the need for further investigation into the long-term effects of secondary task use while driving on cardiovascular reactivity as well as the dangers of secondary task use while driving on the risk of cardiovascular disease or stroke. |
60 | [ ] | 36 | 18–56; 26.95; 5.076; 23,13 | A | 2.5 | M | DM, RT | HH—cell-phone texting | Driver groups with phone-texting distractions exhibited larger speed variability, longer average following HWDs, considerably slower reaction times, and longer distances needed for quick recovery in response to front-car braking events than driver groups without such distractions. |
61 | [ ] | 34 | 18–28; NR; NR; 19,15 | A | NR | V, M + RC, W | DM, RT, AP | HH—texting | In both urban and rural road contexts, texting results in a statistically significant decrease in mean speed and an increase in mean reaction time. Due to driver distraction and delayed response at the time of the incident, it also increases the likelihood of an accident. |
62 | [ ] | 34 | 18–24; NR; NR; 19,15 | B | 3 | V, M + W | DM, AP | HH—navigation, tuning the radio, replying to a text message, replying to a voice message, and making a phone call | On highways, texting appears to cause drivers to exhibit compensatory behavior, which statistically significantly reduces the mean speed and increases headway in both normal and particular traffic and weather conditions. |
63 | [ ] | 34 | NR; 47.6, 23.05; NR; 23, 11 | A | NR | V, M + A | OMs | HF—normal conversation (non-emotional cellular conversation), and seven-level mathematical calculations | Making a call, returning a voicemail, and responding to texts are high-visual-load secondary chores that drivers shouldn’t engage in while operating a vehicle. |
64 | [ ] | 43 | NR; 24.09; 3.27; 25–18 | B | 4.1 | V, C | DM, OMs | HF—texting, talking | For basic road portions, texting considerably raised the SDLP, although conversational tasks showed less lateral variance than when there was no distraction. |
65 | [ ] | 28 | 18–55; 29.4; 11.3; 16, 12 | B | 9 | V, M, Au | RT, DM, OMs | HH—text messaging | Although Glass enables drivers to better maintain their visual attention on the front scene, they are still unable to efficiently divide their cognitive attention between the Glass display and the road environment, which impairs their ability to drive. |
66 | [ ] | 20 | 22–47; 32.2; 6.3; 16, 4 | A | 3 | V, C | DM, OMs | HH—reading text on Glass and on a smartphone | When approaching active urban rail level crossings (RLXs), texting had a negative effect on how well the driver performed. |
67 | [ ] | 101 | 18–57; 27.8; 8.3; 68, 33 | A | 6 | V, C, M | DM | HH—texting, talking on the phone, or eating | According to the simulation results, texting and, to a lesser extent, talking on the phone cause traffic to move more slowly on average and with higher coefficients of variation. |
Note: TD—type of distraction: C—cognitive, V—visual, M—manual, Au—auditory; MT—measure type: AL—attention lapses, AP—accident probability, DM—driving maintenance, HA- hazard anticipation, RT—response time, TrV—traffic violations, OM—other measures; HH—hand-held, HF—hands-free, NP—number of participants; LSR—length of simulated route; NR—not reported. a Values include age, mean, standard deviation, and gender (M, F). b Driving Simulator Classification: A—fixed-based, basic visual capability, FOV minimum H:40 and V:30; B—fixed-based, FOV minimum H:40, and V:30; C—motion platform, FOV minimum H:120 and V:30; D—minimum 6 DOF motion platform, FOV minimum H:180 and V:40 [ 40 ].
This work was supported by a grant from the Romanian Ministry of Education and Research, CCCDI–UEFISCDI, project number PN-III-P2-2.1-PED-2019-4366 (431PED), within PNCDI III.
Conceptualization, R.G.B. and I.-D.B.; methodology, R.G.B.; software, G.-D.V.; validation, I.-D.B., C.A. and G.Y.; formal analysis, R.G.B.; investigation, G.-D.V.; resources, G.-D.V.; data curation, I.-D.B.; writing—original draft preparation, R.G.B. and G.-D.V.; writing—review and editing, C.A. and G.Y.; visualization, I.-D.B.; supervision, C.A. and G.Y.; project administration, R.G.B.; funding acquisition, C.A. All authors have read and agreed to the published version of the manuscript.
Informed consent statement, data availability statement, conflicts of interest.
The authors declare no conflict of interest.
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COMMENTS
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Evidence from a variety of cross-sectional, longitudinal and empirical studies implicate smartphone and social media use in the increase in mental distress, self-injurious behaviour and suicidality among youth; there is a dose-response relationship, and the effects appear to be greatest among girls. Social media can affect adolescents' self ...
Further evidence suggests that even the mere awareness of the physical presence of a cell phone may impact cognitive performance. Thornton et al. (2014) conducted a study in which participants were asked to complete two neuropsychological tasks designed to measure executive function and attention, a digit cancelation task and a trail-making ...
In 2015, well-known technology researcher and social commentator Sherry Turkle wrote "Stop Googling. Let's Talk." In this piece for the New York Times, Turkle laments the mobile phone's negative impact on face-to-face social interactions. She writes that phones inhibit the ability to read and understand others' emotions, beget more superficial conversations, and lead to a decrease in ...
1. Introduction. Cellphone texting has become one of the primary communication activities for relationship maintenance in recent years. As of May 2013, 81% of cellphone owners reported sending or receiving text messages, and this proportion reached up to 94-97% for younger adults aged between 18 and 49 (Duggan, 2013).Teens who texted often were more likely to own a smartphone as opposed to a ...
The current research considers the impact of mobile phone technology and social media use on ... suggesting that " one's awareness of a cell phone being present can impact cognitive ...
Emerging research provides examples of factors that might impact perceptions of responsiveness when communicating via text, such as response time (Atchley & Warden, 2012) and similarity in the use of emojis (Coyle & Carmichael, 2019), but research remains in its infancy. The impact of video and voice messages, GIFs, memes, and photos on ...
Abstract. Objective: A fully immersive, high-fidelity street-crossing simulator was used to examine the effects of texting on pedestrian street-crossing performance. Background: Research suggests that street-crossing performance is impaired when pedestrians engage in cell phone conversations. Less is known about the impact of texting on street ...
This paper will address the first sub-question: What is the effects of cell phone use on adolescents? The advances in smartphones are increasing rapidly due to cooperate competition, increased ...
analyz e its impact on literacy development. This analysis considers the two lines of inquiries. posited by Drouin (2011), namely "the use of textese and literacy" and "text messaging ...
1. Introduction. In 2018, approximately 77 percent of America's inhabitants owned a smartphone (Pew Research Center, 2018), defined here as a mobile phone that performs many of the functions of a computer (Alosaimi, Alyahya, Alshahwan, Al Mahyijari, & Shaik, 2016).In addition, a survey conducted in 2015 showed that 46 percent of Americans reported that they could not live without their ...
Some studies also showed a positive relation of cell phone addiction and physiological health. The other school of thought reveals an indirect relation between cell phone usage and psychological health. They say adolescents use cell phones at night, which leads to insomnia. And insomnia ultimately results in depression, anxiety, and depression.
The mobile phone is stimulating one of the most important technological revolutions in human history. This article first presents impacts, challenges, and predictions of mobile phone use. It first indicates that the impact of the mobile phone on society has been predominantly positive while the mobile phone has certain negative attributes.
In support of the "cell phone as disrupter" hypothesis, a recent study by our group (Lepp et al., 2013) found that cell phone use was negatively associated with an objective measure of cardiorespiratory fitness in a sample of typical U.S. college students.Interview data collected for the study explained the negative relationship by suggesting that cell phone use disrupts physical activity ...
The current study uses true experimental design to measure the impact that cell phones have on our face-to-face interactions. 37 students from a Central Florida university participated in the ...
Semantic Scholar extracted view of "The Impact of Cell Phone Texting on the Amount of Time Spent Exercising at Different Intensities: 465 Board #302 June 1, 11: 00 AM - 12: 30 PM." ... Search 219,045,839 papers from all fields of science. Search. Sign In ... The present research is based on a qualitative exploration of 58 on campus intercept ...
1. Introduction. Texting and other cell phone use while driving is a major risk factor for motor vehicle collisions and associated injury and death (Wilson & Stimpson, 2010).In 2012, distracted driving was associated with 3300 deaths and 421,000 injuries in collisions in the US; there is evidence that smartphone use is increasingly contributing to these numbers (US Department of Transportation ...
Some 17% of these high-income earners say that their phone makes it "a lot" harder to do this (compared with 7% for those earning less than $30,000 per year, 6% for those earning $30,000-$49,999, and 8% for those earning $50,000-$74,999). Overall, nearly one third (29%) of high-income cell owners say that their phone makes it at least ...
Majorities of users in nine countries say their phone has had a positive impact on their livelihood - ranging from 55% in Tunisia to 81% in Kenya - while Jordanians and Lebanese most commonly say that mobile phones have not had much impact either way on their ability to make a living. Still, few people see mobile phones having a negative ...
mobile phones in the classroom and 45% of the respondents were supportive. The researchers. explained that the more American adults are used to their devices in their everyday life, the. more ...
Most people think of talking on a cell phone or texting, but distracted driving can go beyond these behaviors. The Centers for Disease Control and Prevention has identified three kinds of ...
This study investigated the effects of smartphone use on the perceived academic performance of elementary school students. Following the derivation of four hypotheses from the literature, descriptive analysis, t testing, one-way analysis of variance (ANOVA), Pearson correlation analysis, and one-way multivariate ANOVA (MANOVA) were performed to characterize the relationship between smartphone ...
1. Introduction. Road safety is increasingly threatened by distracted driving. One of the highest-risk forms of distracted driving is texting while driving (TWD) [1,2] alongside talking on the phone while driving (TPWD) [3,4].After decades of research, the statistics show that the risks associated with TWD are very high [].According to the United Nations Road Safety statistical data [], car ...