Driver distractions

Last updated: 09-17-2020

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Driver distractions

Driving always requires the driver’s full attention. However, many people still let themselves become distracted and inattentive behind the wheel.

Distraction happens when drivers stop focusing on safely making their journey and divert their attention towards something else. Any distraction reduces drivers’ awareness and their ability to spot and respond to hazards in time, making it much more likely that they will be involved in a road crash. The effects of distractions on drivers can vary, depending on timing, intensity, duration, frequency, resumability (the extent to which the driving task can be halted and resumed efficiently) and the ‘hang-over effect’ (the mental distraction that remains once a task is completed) [4]. However, even a moment’s distraction can have fatal consequences.

Out of the 1,456 fatal collisions recorded by police in Britain in 2018, 383 involved drivers failing to properly look at the road (26%). Another 110 fatal crashes (8%) involved other distractions, including in-vehicle distraction, distractions outside of the vehicle, and using a mobile phone [5].

The scale of driver distraction is concerning. A recent survey by Brake and Direct Line revealed many drivers admit to performing distracting secondary tasks [6]. In another study by Cranfield University, one in six of 11,000 drivers observed on roads in St Albans, England, were found to be engaged in a distracting activity, such as talking on a phone, or to a passenger, or smoking. The study also found younger drivers are more likely to be engaged in distracting activities [7].

However, any road user can become distracted, including vulnerable road users (for example, people on foot or bicycle) [8] [9]. This fact emphasises the importance of drivers watching out for people on foot and bicycles doing unpredictable and dangerous things.

Drivers may risk distraction because they mistakenly believe they are in full control and have time to react if danger arises – but evidence suggests this is not always the case. Research has found that drivers cannot divide their attention between driving and a secondary task without significantly reducing their driving performance. They also cannot estimate their own levels of distraction effectively [10].

Academics have also found drivers may fall into ‘consequence traps’ and ‘conditioning traps’. A consequence trap is when a driver knows the risk, but succumbs to an overriding temptation of an immediate reward (for example reaching for a flask of coffee, or changing the music from a track they don’t like). A conditioning trap is when a driver knows the risk, but has ‘got away with it’ on numerous occasions before, so takes the risk again on the presumption that nothing bad will happen this time either [11].

One of the most dangerous distractions is covered in more detail in our phones and screens fact page. However, there are many other things that can distract drivers, both inside and outside their vehicles [12]. These distractions can be categorised into four main types: visual; auditory; manual; and cognitive.

A selection of other causes of distraction are listed below.

Read more: Read our fact-page on on driver distraction caused by mobile phones and screens. 

When using roads, drivers’ thoughts can easily wander to things other than the safety of the task at hand. Driving, particularly on a familiar route, can be perceived as something we can do semi-automatically, or a car can become a place where people consciously decide to think about other things, such as work or relationships, or reflect on a memory. In one study, more than half of drivers’ thoughts (“what are you thinking about?”) were on subjects unrelated to driving [15].

Many vehicles are now being fitted with automated technology designed to assist drivers. However, certain technologies may in fact tempt drivers to engage in distracting activities [16]. Research has found some advanced driver assistance systems (ADAS) may encourage ‘disengagement’ with the driving task, leading to inattention (such as the driver’s mind wandering or purposely choosing to do something else) [17] and difficulty then reengaging in time should a hazard arise.

For example, automated “cruise control” systems aim to enable the vehicle to maintain speed and distance from a vehicle in front. Manufacturers warn drivers these systems require driver attention at all times. In 2016, a driver died in the USA when their Tesla collided with a truck during a trial of the vehicle’s ‘autopilot’ feature. Tesla said: "Neither Autopilot nor the driver noticed the white side of the tractor trailer against a brightly lit sky, so the brake was not applied." [18]

As an auditory distraction, music reduces driver attention on the road. There is evidence that the more complex/loud the music is, the greater the distraction [19]. Recent studies have also suggested that upbeat music increases both driver error and aggressive driving [20].

Research by Brake has found that just 16% of drivers do not think it is distracting at all to adjust the radio while driving. Almost a quarter (24%) think it is very distracting and 60% think it is slightly distracting [21].

Eating and drinking can be both cognitive and physical distractions, as they require drivers to remove at least one hand from the wheel [22]. A Brake study has shown eating or drinking at the wheel can increase driver reaction times by 44%, [23] and one in 10 drivers polled had suffered a near-miss because they were distracted by food while driving. A third of drivers admit to eating at the wheel and the worst offenders are drivers aged 25-34, with more than half of drivers (55%) in this age bracket admitting to unwrapping and eating food at the wheel [24].

Past research has suggested drivers who eat and drink at the wheel can be twice as likely to crash [25]. Brake’s own findings show two in five people (39%) think eating or drinking while driving is very distracting, and 45% think it is slightly distracting [26]. However, 60% of drivers admit eating or drinking at the wheel in the last 12 months, and 4% do so on every journey.

Smoking while driving makes it more likely that you will be involved in a crash [27]. Accessing and lighting a cigarette within the car causes physical and mental distraction. The smoke from the lit cigarette, from the driver or passenger, could also impair the driver’s vision, and a cigarette falling into the driver’s lap or onto a seat could cause distraction.

Almost four-fifths of drivers (79%) believe smoking or vaping at the wheel is at least slightly distracting, and 73% say they never smoke or vape while driving [28]. However, 6% smoke or vape on every journey, 6% on most journeys, and 10% on less than half of journeys or on rare occasions.

Drivers may develop a habit of failing to look properly, particularly on routes they are familiar with or are often quiet or empty of traffic. However, they often lack ‘metacognitive awareness’ about their behaviour, meaning they think they look properly even though their attention may be restricted, diverted, misprioritised, neglected or cursory [29].

It is common to hear that experienced drivers ‘looked but didn’t see’ another vehicle immediately before a crash. Studies have found that experienced drivers give less than half the length of attention to motorcycles than they give to other cars. Novice drivers, by contrast, were found to give cars and motorcycles equal “gaze lengths”, showing that they pay more attention to other road users [30].

This may explain why motorcyclists involved in crashes are often hit by drivers pulling out from side junctions. Academics describe the motorcycle, in such an incident, as a “low spatial frequency” object (a narrow object that is blurred into the background unless carefully sought). It is harder to see, and requires a longer fixation by the driver to see it [31].

Familiarity with a route may also lead to drivers looking at things unrelated to driving to keep themselves entertained, causing them to miss emerging hazards. Research into the brain patterns of police drivers undertaking the same simulated drive twice, found a “significant reduction in attentional areas of the brain” and concluded route familiarity reduces activation in the brain [32]. A similar study tested the attention of a driving instructor undertaking a real road journey 28 times, and found a “decrease in attention to safety-relevant aspects” [33].

As well as ‘inattentional blindness’ (the tendency not to see unattended things), drivers may experience ‘change blindness’. This is when someone is familiar with a particular situation, and doesn’t notice when that situation changes (for example, when a road sign is changed). People are much more likely to notice change if they focus for longer, and more familiarity with a road leads to a shorter glance duration and heightened risk [34].

Recent studies have shown younger drivers (17-29) and older drivers (over 65) have a significantly and consistently higher risk of causing a road crash due to distracted driving, and certain types of driver distraction have a greater influence on these age groups than any other [35].

While visual distractions affect drivers of all ages, younger drivers are more likely to have their driving performance negatively affected by auditory distractions, e.g. listening to music [36].

Younger drivers are also more likely to succumb to other distractions within the vehicle including checking social media, messaging, or paying attention to other passengers. Recent studies have suggested the presence of a peer passenger can be associated with a reduction in visual scanning, by male drivers in particular, due to cognitive distraction triggered by either the physical presence of the passenger or the perceived expectations of the passenger [37].

Driver distraction and drowsiness recognition (DDDR) systems aim to detect distraction (or fatigue) and send a warning to the driver to stop and rest. Eye movements can be monitored by a camera pointed at the driver, and the technology can also monitor a driver’s heart rate and brain function. This information can be combined with detection of wider head movements. Systems monitoring people in such ways (particularly eye movements) and then issuing a warning are commonly available as an aftermarket product, marketed to fleet operators.

Steering and braking patterns can also give some indication of inattention, and some new vehicles come fitted with DDDR systems that monitor these patterns and warn the driver.

Increasingly, companies with at-work drivers are fitting their vehicles with cameras that watch the driver. In October 2016, lorry driver Thomasz Kroker was jailed for killing four people after ploughing into their car while changing music on his phone; his actions were recorded on camera, providing evidence of his distraction to the police and courts.

[4] Kinnear, N. et al (2013), Understanding how drivers learn to anticipate risk on the road: A laboratory experiment of affective anticipation of road hazards

[8] Fitzpatrick, C. et al (2016), The prevalence of distracted walking and its effect on driver behaviour

[9] Boufous, S. et al (2015), Circumstances of on-road single-vehicle cyclist crashes in the Australian Capital Territory

[10] Kinnear, N. and Stevens, A. (2015), The battle for attention: Driver distraction – a review of recent research and knowledge, TRL for IAM

[11] Lee, J. (2014), Dynamics of driver distraction: the process of engaging and disengaging

[12] Beanland, V. et al (2013), Driver inattention and driver distraction in serious casualty crashes: data from the Australian national crash in-depth study

[13] Young, K, et al (2003), Driver Distraction: a review of the Literature

[15] Starkey, N (2016), University of Waikato, International Conference on Traffic and Transport Psychology, Brisbane

[16] Dunn, N. et al (2019), Understanding the impact of technology: Do advanced driver assistance and semi-automated vehicle systems lead to improper driving behaviour? AAA Foundation for Traffic Safety

[17] Lee, J. (2014), Dynamics of driver distraction: the process of engaging and disengaging

[19] Brodsky, W. (2001), The effects of music tempo on simulating driving performance on simulated driving performance and vehicular behaviour

[20] Brodsky, W. & Slor, Z. (2012), Background music as a risk factor for distraction among young novice drivers

[22] Irwin, G. et al (2014), The influence of drinking, texting, and eating on simulated driving performance

[23] Brake and Direct Line (2016), Eating at the Wheel

[25] Young, M. et al (2008), Crash dieting: the effects of eating and drinking on driving performance

[27] Ayaka I. et al (2019), Does cigarette smoking increase traffic accident death during 20 years follow-up in Japan? The Ibaraki prefectural health study, Journal of Epidemiology 29(5), 192-196

[29] Beanland, V. & Chan, EHC. (2016), The relationship between sustained inattentional blindness and working memory capacity

[32] Mader et al (2016), International Conference on Traffic and Transport Psychology, Brisbane

[34] Marieke Martens (2016), University of Twente, International Conference on Traffic and Transport Psychology, Brisbane

[35] Guo, F. et al (2017), The effects of age on crash risk associated with driver distraction, International Journal of Epidemiology 46(1), 258–265

[36] Brodsky, W. & Slor, Z. (2012), Background music as a risk factor for distraction among young novice drivers

[37] Beanland, V. et al (2013), Driver inattention and driver distraction in serious casualty crashes: data from the Australian National Crash In-depth Study

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