Human error is a frequent contributor to road traffic collisions, understanding the human factors provides a deeper insight into road-user behaviour.

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Driving when tired – how and why does fatigue influence driving behaviours?

Driving when feeling very tired is obviously highly risky behaviour and estimates have suggested that up to 20% of collisions could, at least to some extent, be attributed to fatigue. So how does being tired influence our driving behaviours and what can we do to reduce or avoid our chances of being involved in an incident?

One of the ways in which fatigue impairs driving behaviour is by making reaction times slower. In one study[i] 240 male drivers were stopped between 1am and 6am. They were asked to rate how tired they were and to complete a simple reaction time task. Those who felt rested had reaction times of around 189 milliseconds (ms), but those who were very tired had significantly slower reaction times of 309 ms.

However, some research[ii] has suggested that this increase in reaction times might not be seen in actual driving behaviours. Instead, it is argued that, when fatigued and driving, we allocate our resources in such a way that we prioritise collision avoidance, but that other tasks, such as steering accuracy, may suffer. There is also some evidence to show that driving performance when fatigued is more affected when driving an easier route than when driving on a more complex one[iii]. It seems that the added cognitive load enables the driver to allocate their processing resources in a way that leads to safer driving behaviour.

Regardless of why fatigue influences driving behaviour, it is clear that the chances of having a crash increases greatly when the driver is tired. The important issue is how this risk can be avoided or minimised. Two psychologists, Reyner and Horne[iv], have conducted a series of experiments examining how effective various methods of reducing fatigue are.  Methods such as listening to loud music or opening the window are only effective for a very short period of time, around 15 minutes. Similarly, consuming a highly caffeinated drink only relieved sleepiness for about 30 minutes in people who had no sleep at all the night before, although it was more effective if people had at least some sleep. The researchers concluded that by far the most effective method of avoiding fatigue was to take a short nap, of just 10 to15 minutes, and then have a caffeinated drink.

Some people are more at risk of driving when fatigued than others, and those who drive as part of their occupation are particularly vulnerable. There is evidence that the attitudes of employers can influence how well drivers deal with fatigue. One piece of research[v] examined how the organisational safety climate and occupational stress might influence driving behaviours whilst fatigued. They found that fewer “near misses” occurred when drivers exhibited lower levels of work-related stress and worked for organisations with a high awareness of driver safety-related issues. However, while both factors were found to be significant and important, the occupational safety climate had a far greater effect. This study really emphasises the importance of the attitudes, policy and training provided by employers in reducing potential on-road incidents.

For instance, research has proved conclusively that there are two times of the day during which collisions due to fatigue are most likely to occur: at night time between midnight and 6 a.m. and at mid-afternoon in the post-lunch dip. A sensible risk management action would therefore be to arrange work patterns so that no business driving was required in the early hours and that drivers were mandated to take a break during the afternoon period.

Ideally, people would not drive when they feel sleepy, but in the real world this is hard to police and prevent. One thing that is clear from the research is that the risk of having a crash can be reduced if driver safety is taken seriously by both employer and employee. This involves having policies in place, procedures to identify likely risk scenarios and interventions that are tailored to specific need.


[i] Corfitsen (1999)

[ii] Van der Hulst et al. (2001)

[iii] Matthews and Desmond (2002)

[iv] Reyner and Horne (1998, 2000), Horne and Reyner (1996, 1997)

[v] Strahan et al. (2008)

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