Effects of Mobile Phone Distraction at the Onset of Amber Light: Analysis of Driving Simulator Data

Distraction whilst driving on an approach to a signalized intersection is particularly dangerous, as potential vehicular conflicts and resulting angle collisions tend to be severe. This study examines the decisions of distracted drivers during the onset of amber lights. Driving simulator data were obtained from a sample of 58 drivers under baseline and handheld mobile phone conditions at the University of IOWA - National Advanced Driving Simulator. Explanatory variables include age, gender, cell phone use, distance to stop-line, and speed. An iterative combination of decision tree and logistic regression analyses are employed to identify main effects, non-linearities, and interactions effects. Results show that novice (16-17 years) and younger (18-25 years) drivers’ had heightened amber light running risk while distracted by cell phone, and speed and distance thresholds yielded significant interaction effects. Driver experience captured by age has a multiplicative effect with distraction, making the combined effect of being inexperienced and distracted particularly risky. Solutions are needed to combat the use of mobile phones whilst driving.

Effects of mobile phone distraction on drivers’ reaction times

Distraction resulting from mobile phone use whilst driving has been shown to increase the reaction times of drivers, thereby increasing the likelihood of a crash. This study compares the effects of mobile phone conversations on reaction times of drivers responding to traffic events that occur at different points in a driver’s field of view. The CARRS-Q Advanced Driving Simulator was used to test a group of young drivers on various simulated driving tasks including a traffic event that occurred within the driver’s central vision—a lead vehicle braking suddenly—and an event that occurred within the driver’s peripheral—a pedestrian entering a zebra crossing from a footpath. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), and while engaged in hands-free and handheld phone conversations. The drivers were aged between 21 to 26 years and split evenly by gender. Differences in reaction times for an event in a driver’s central vision were not statistically significant across phone conditions, probably due to a lower speed selection by the distracted drivers. In contrast, the reaction times to detect an event that originated in a distracted driver’s peripheral vision were more than 50% longer compared to the baseline condition. A further statistical analysis revealed that deterioration of reaction times to an event in the peripheral vision was greatest for distracted drivers holding a provisional licence. Many critical events originate in a driver’s periphery, including vehicles, bicyclists, and pedestrians emerging from side streets. A reduction in the ability to detect these events while distracted presents a significant safety concern that must be addressed.

The impact of mobile phone distraction on the braking behaviour of young drivers : a hazard-based duration model

Braking is a crucial driving task with a direct relationship with crash risk, as both excess and inadequate braking can lead to collisions. The objective of this study was to compare the braking profile of young drivers distracted by mobile phone conversations to non-distracted braking. In particular, the braking behaviour of drivers in response to a pedestrian entering a zebra crossing was examined using the CARRS-Q Advanced Driving Simulator. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free, and handheld. In addition to driving the simulator, each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The drivers were 18–26 years old and split evenly by gender. A linear mixed model analysis of braking profiles along the roadway before the pedestrian crossing revealed comparatively increased decelerations among distracted drivers, particularly during the initial 20 kph of deceleration. Drivers’ initial 20 kph deceleration time was modelled using a parametric accelerated failure time (AFT) hazard-based duration model with a Weibull distribution with clustered heterogeneity to account for the repeated measures experiment design. Factors found to significantly influence the braking task included vehicle dynamics variables like initial speed and maximum deceleration, phone condition, and driver-specific variables such as licence type, crash involvement history, and self-reported experience of using a mobile phone whilst driving. Distracted drivers on average appear to reduce the speed of their vehicle faster and more abruptly than non-distracted drivers, exhibiting excess braking comparatively and revealing perhaps risk compensation. The braking appears to be more aggressive for distracted drivers with provisional licenses compared to drivers with open licenses. Abrupt or excessive braking by distracted drivers might pose significant safety concerns to following vehicles in a traffic stream.

Effect of mobile phone distraction on car-following behaviour

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18 to 26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 seconds in time headway when a driver is engaged in hands-free phone conversation and a 0.75 seconds increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.

Influence of road traffic environment and mobile phone distraction on the speed selection behaviour of young drivers

Travel speed is one of the most critical parameters for road safety; the evidence suggests that increased vehicle speed is associated with higher crash risk and injury severity. Both naturalistic and simulator studies have reported that drivers distracted by a mobile phone select a lower driving speed. Speed decrements have been argued to be a risk compensatory behaviour of distracted drivers. Nonetheless, the extent and circumstances of the speed change among distracted drivers are still not known very well. As such, the primary objective of this study was to investigate patterns of speed variation in relation to contextual factors and distraction. Using the CARRS-Q high-fidelity Advanced Driving Simulator, the speed selection behaviour of 32 drivers aged 18-26 years was examined in two phone conditions: baseline (no phone conversation) and handheld phone operation. The simulator driving route contained five different types of road traffic complexities, including one road section with a horizontal S curve, one horizontal S curve with adjacent traffic, one straight segment of suburban road without traffic, one straight segment of suburban road with traffic interactions, and one road segment in a city environment. Speed deviations from the posted speed limit were analysed using Ward’s Hierarchical Clustering method to identify the effects of road traffic environment and cognitive distraction. The speed deviations along curved road sections formed two different clusters for the two phone conditions, implying that distracted drivers adopt a different strategy for selecting driving speed in a complex driving situation. In particular, distracted drivers selected a lower speed while driving along a horizontal curve. The speed deviation along the city road segment and other straight road segments grouped into a different cluster, and the deviations were not significantly different across phone conditions, suggesting a negligible effect of distraction on speed selection along these road sections. Future research should focus on developing a risk compensation model to explain the relationship between road traffic complexity and distraction.

A parametric duration model of the reaction times of drivers distracted by mobile phone conversations

The use of mobile phones while driving is more prevalent among young drivers—a less experienced cohort with elevated crash risk. The objective of this study was to examine and better understand the reaction times of young drivers to a traffic event originating in their peripheral vision whilst engaged in a mobile phone conversation. The CARRS-Q Advanced Driving Simulator was used to test a sample of young drivers on various simulated driving tasks, including an event that originated within the driver’s peripheral vision, whereby a pedestrian enters a zebra crossing from a sidewalk. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free and handheld. In addition to driving the simulator each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The participants were 21 to 26 years old and split evenly by gender. Drivers’ reaction times to a pedestrian in the zebra crossing were modelled using a parametric accelerated failure time (AFT) duration model with a Weibull distribution. Also tested where two different model specifications to account for the structured heterogeneity arising from the repeated measures experimental design. The Weibull AFT model with gamma heterogeneity was found to be the best fitting model and identified four significant variables influencing the reaction times, including phone condition, driver’s age, license type (Provisional license holder or not), and self-reported frequency of usage of handheld phones while driving. The reaction times of drivers were more than 40% longer in the distracted condition compared to baseline (not distracted). Moreover, the impairment of reaction times due to mobile phone conversations was almost double for provisional compared to open license holders. A reduction in the ability to detect traffic events in the periphery whilst distracted presents a significant and measurable safety concern that will undoubtedly persist unless mitigated.

Impact of mobile phone use on car-following behaviour of young drivers

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18–26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 s in time headway when a driver is engaged in hands-free phone conversation and a 0.75 s increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.

Gap acceptance behavior of mobile phone distracted drivers at roundabouts

While mobile phones have become ubiquitous in modern society, the use of mobile phones while driving is increasing at an alarming rate despite the associated crash risks. A significant safety concern is that driving while distracted by a mobile phone is more prevalent among young drivers, a less experienced driving cohort with elevated crash risk. The objective of this study was to examine the gap acceptance behavior of distracted young drivers at roundabouts. The CARRS-Q Advanced Driving Simulator was used to test participants on a simulated gap acceptance scenario at roundabouts. Conflicting traffic from the right approach of a four-legged roundabout were programmed to have a series of vehicles having the gaps between them proportionately increased from two to six seconds. Thirty-two licensed young drivers drove the simulator under three phone conditions: baseline (no phone conversation), hands-free and handheld phone conversations. Results show that distracted drivers started responding to the gap acceptance scenario at a distance closer to the roundabout and approached the roundabout at slower speeds. They also decelerated at faster rates to reduce their speeds prior to gap acceptance compared to non-distracted drivers. Although accepted gap sizes were not significantly different across phone conditions, differences in the safety margins at various gap sizes—measured by Post Encroachment Time (PET) between the driven vehicle and the conflicting vehicle—were statistically significant across phone conditions. PETs for distracted drivers were smaller across different gap sizes, suggesting a lower safety margin taken by distracted drivers compared to non-distracted drivers. The results aid in understanding how cognitive distraction resulting from mobile phone conversations while driving influences driving behavior during gap acceptance at roundabouts.

Mobile phone use and driving : the message is just not getting through

Previous research has shown that mobile phone use while driving can increase crash risk fourfold while texting results in 23 times greater crash risk for heavy vehicle drivers. However, mobile phone use has changed in recent years with the functional capabilities of smart phones to now also include a range of other common behaviours while driving such as using Facebook, emailing, the use of ‘apps’, and GPS. Research continues to show performance decrements for many such behaviours while driving, however many Australians still openly admit to illegal mobile phone use while driving despite ongoing enforcement efforts and public awareness campaigns. Of most concern are young drivers. ‘Apps’ available to restrict mobile phone use while in motion do not prevent use while a driver is stopped at traffic lights, so are therefore not a wholly viable solution. Vehicle manufacturers continue to develop in-vehicle technology to minimise distraction, however communication with the ‘outside world’ while driving is also perhaps a strong selling point for vehicles. Hence, the safety message that drivers should focus on the driving task solely and not use communication devices is unlikely to ever be internalised by many drivers. This paper reviews the available literature on the topic and argues that a better understanding of perceptions of mobile phone use while driving and motives for use are required to inform public awareness campaign development for specific road user groups. Additionally, illegal phone use while driving may be reinforced by not being apprehended (punishment avoidance), therefore stronger deterrence-focussed messages may also be beneficial.

Exploring boredom proneness as a predictor of mobile phone use in the car

Driver distraction through mobile phone use in the car is a growing road safety concern. This paper presents findings of a survey (N = 528), which seeks to better understand the predictors of mobile phone use while driving in young (18-25) adult drivers. The survey investigated factors and motivations such as young adults' boredom proneness and their social connectedness, as well as their general mobile phone use and phone use in the car. We found, e.g., that boredom proneness plays a larger role (compared to social connectedness) in determining how much a young male uses their phone in the car (compared to young females). Despite the study’s limitations, this initial understanding allows us to better design and develop innovative HCI interventions that prevent young adults, particularly males, from phone use while driving in a way that appeals to their needs.

Influence of personal mobile phone ringing and usual intention to answer on driver error

Given evidence of effects of mobile phone use on driving, and also legislation, many careful drivers refrain from answering their phones when driving. However, the distracting influence of a call on driving, even in the context of not answering, has not been examined. Furthermore, given that not answering may be contrary to an individual’s normal habits, this study examined whether distraction caused by the ignored call varies according to normal intention to answer whilst driving. That is, determining whether the effect is more than a simple matter of noise distraction. Participants were 27 young drivers (18-29 years), all regular mobile users. A Theory of Planned Behaviour questionnaire examined predictors of intention to refrain from answering calls whilst driving. Participants provided their mobile phone number and were instructed not to answer their phone if it were to ring during a driving simulation. The simulation scenario had seven hazards (e.g. car pulling out, pedestrian crossing) with three being immediately preceded by a call. Infractions (e.g. pedestrian collisions, vehicle collisions, speed exceedances) were significantly greater when distracted by call tones than with no distraction. Lower intention to ignore calls whilst driving correlated with a larger effect of distraction, as was feeling unable to control whether one answered whilst driving (Perceived Behavioural Control). The study suggests that even an ignored call can cause significantly increased infractions in simulator driving, with pedestrian collisions and speed exceedances being striking examples. Results are discussed in relation to cognitive demands of inhibiting normal behaviour and to drivers being advised to switch phones off whilst driving.

Mobile phone consumption and implications for SMS marketing

This paper reports on a Q-methodology study on the consumption of mobile phones and opinions on SMS-marketing, extracted from interpretive interviews and focus groups. The Metaphors Q-sort, developed within a framework of Holt's (1995) four metaphors of consumption, identifies three experiential value clusters in the consumption of mobile phones: the Mobile Pragmatists, the Mobile Connectors and the Mobile Revelers. The SMS-marketing Q-sort identifies two key clusters of subjective opinions on various aspects of SMS-based mobile-marketing. By integrating the findings from these two Q-sorts, we demonstrate that while all three value clusters express positive opinions towards ‘location specific’ and ‘customer initiated contact’ SMS-marketing, there are noticeable differences in how marketers should develop their strategies to maximize the consumers’ perceived experiential value derived from the consumption of their mobile phones. Keywords: mobile phones; experiential consumption: SMS-marketing; Q-methodology

Mobile phone use while driving : an investigation of the beliefs influencing drivers’ hands-free and hand-held mobile phone use.

This study explored the psychological influences of hands-free and hand-held mobile phone use while driving. Participants were 796 Australian drivers aged 17 to 76 years who owned mobile phones. A cross-sectional survey assessed frequency of calling and text messaging while driving (overall, hands-free, hand-held) as well as drivers’ behavioural, normative, and control beliefs relating to mobile phone use while driving. Irrespective of handset type, 43% of drivers reported answering calls while driving on a daily basis, followed by making calls (36%), reading text messages (27%), and sending text messages (18%). In total, 63.9% of drivers did not own hands-free kits and, of the drivers that owned hand-free kits, 32% did not use it most or all of the time. Significant differences were found in the behavioural, normative, and control beliefs of frequent and infrequent users of both types of handset while driving. As expected, frequent users reported more advantages of, more approval from others for, and fewer barriers that would prevent them from, using either a hands-free or a hand-held mobile phone while driving than infrequent users. Campaigns to reduce mobile phone use while driving should attempt to minimise the perceived benefits of the behaviour and highlight the risks of this unsafe driving practice.