Traditional methods and sources

The most common sources of data on driver behaviour and exposure are self-reported information collected from surveys, police enforcement records, driver and vehicle license records and hospital records. Data derived from insurance claims has also been used but is less common due to commercial sensitivity. Together these are sometimes referred to as traditional methods and sources. They continue to be used extensively and have many benefits.

Self-reported speeding behaviour is the most common method of collecting information about the extent of risky driving behaviour. Its primary advantage is that it is

relatively inexpensive, especially as part of a larger study where participants already complete a questionnaire or interview, and includes incidences of risky driving

behaviour that may not be recorded using other traditional methods. The recruitment process for self-reported surveys also allows researchers to ensure that the sample is

representative of the driving population which may not be possible with other

methods. However, although there is evidence that self-reported driving behaviour is a valid predictor of actual behaviour (Hatakka et al., 1997) it suffers from extensive under (and in some cases over) reporting of risky driving behaviour (Corbett, 2001; Hatfield et al., 2008). Given that risk perception17 _{– defined in this thesis as a}

person‘s subjective estimate of the likelihood of an event occurring (Ulleberg and Rundmo, 2003)18 _{– appears linked to experience (Rosenbloom et al., 2008) the validity}

of self-reported driving behaviour is open to question. Furthermore, evidence suggests that there is a limit to the quantity and complexity of the information that can be collected using this method (Goldenbeld and Van Schagen, 2007). Nonetheless, self- reported survey data forms the basis of much of the road safety literature. Provided that results are interpreted with its constraints in mind, they continue to be a source of important contributions to road safety. The number of surveys employing this method makes it impossible to discuss all of them. A selection of studies using a self- report methodology is shown in Table 2-2. This list is not exhaustive but is meant to illustrate the large number of uses of this methodology. These studies were selected on the basis of similarity to the methods employed for the research described in this thesis.

Alternatives (or in some cases complements) to self-reported driving behaviour are police enforcement and licensing records. These records are collected by the police and licensing authorities in the course of enforcing road rules and attending to road

crashes. This method allows for analyses using large samples or cross-validating self- reported measures of behaviour. Speeding and red light running benefit from the use of speed and red light cameras (Wundersitz et al., 2009) which can provide more detailed information about behaviour in the locations where they are installed. Drink driving is revealed in these records from on-road enforcement and from crash records. Other forms of risky driving behaviour, for example illegal u-turns, are recorded only when a citation is issued. The disadvantage of these records is they only include incidences where the road rules have been broken and enforced or where a serious

17 _{Risk perception is explored in Section 3.1.5.}

18 _{Although risk (and risk perception) has been widely studied (Naiitiinen and Summala, 1976; Fuller,}

crash19 _{has occurred meaning that as with self-reported driving behaviour this method}

suffers from under-reporting (Schafer and Mastrofski, 2005; Wilson et al., 2006). It is also likely that police enforcement records tend to overstate more extreme behaviours whilst understating the extent of less extreme (but more common) behaviours or magnitudes of behaviours. This can be particularly problematic when attempting to calculate crash risk because an accurate crash risk calculation requires an accurate record of frequency or exposure. Since not all forms of risky driving behaviour are illegal, this method is not useable for research on risky but legal driving behaviour.

Table 2-2: Selection of studies employing a self-report methodology

Citation Self-Reported Behaviours and Factors _Studied Country Sample _Size Report Self- Only? (Delhomme et al.,

2009b) Speeding; Risk judgements; Personality France 3,002 Y (Iversen and

Rundmo, 2002) Speeding; Risky driving (general); Crash involvement; Personality Norway 2,605 Y (Wood et al., 2009) Driver-Cyclist conflicts, Cyclist visibility; _{Cyclist safety} Australia 1460 Y

(Horwood and

Fergusson, 2000) Drink driving; Distance travelled Zealand New 1011 N (Donovan et al.,

1999) Road safety advertising; Fatigue; Speeding; Inattention; Drink driving Australia 1000 Y (Porter and Berry,

2001) Red light running; Risk perceptions United States 880 Y (Soole et al., 2009) Police enforcement; Speeding Australia 852 Y (Beck et al., 2012) Risky behaviour; Enforcement perceptions; _{seat-belt usage; Hurried drivers} United _States 796 Y (Fleiter et al., 2006) Speeding; Influence of passengers; Social _influence Australia 320 Y

(Young and Lenné,

2010) Distractions; Risk assessment; Crash involvement Australia 287 Y (Hatfield et al.,

2006) Fatigue; Road safety campaigns Australia 230 to 259 Y (Warner and Aberg,

2006) Speeding Sweden 250 N

(Warn et al., 2004) Street racing; Motor sport; Risky driving _Zealand New 180 Y (Bagdadi and

Várhelyi, 2011) Crash involvement Sweden 166 N

Police-reported crashes (Wang et al., 2002; McEvoy et al., 2007a) – as distinct from enforcement records – and hospital records (McEvoy et al., 2005, 2007b) are two other

sources of risky driving behaviour. Police crash records are likely accurate for crashes resulting in fatalities but as many as 30 percent of injury crashes are not reported to police (Shinar et al., 1983). In addition, since these databases only capture behaviour when it has resulted in a crash they ignore the (likely) many instances where the same behaviour has not resulted in an injury. Since every time a driver engages in risky behaviour with no consequences (either injury or penalty) reinforces perceptions of safety (Falk and Montgomery, 2007; Mannering, 2009) this is a potential issue. Hospital records face a similar problem but can be used in conjunction with police records to reduce under reporting of crashes (Shinar et al., 1983). However the process of matching hospital records to their related police crash records (if there is one) is not simple. When possible, researchers face the complication of conflicting records since medical practitioners will likely make a different assessment of sustained injuries than police (Tarko and Azam, 2011). In addition, police and hospital/medical records provide an indication as to the frequency of serious crashes but they do not adequately represent the frequency of behaviour since most driving behaviour goes unrecorded. Therefore it is not possible to determine, for example, the frequency of speeding behaviour by examining licensing/enforcement records which shows that 30 percent of drivers were fined for speeding in the preceding three years (Fleiter et al., 2009). Similarly, looking at crash records will reveal the proportion of crashes where a certain behaviour (speeding, fatigue, etc.) was a factor but not the frequency (or magnitude) to which a behaviour occurs on the road.

Keeping in mind the previously stated caveats about the comparability of different data sources, police enforcement, driver licensing, police crash and medical records can all be used in conjunction with self-reported behaviour. By combining more than one of these methods it is possible to gain a more detailed picture of a driver‘s history including fines or medical issues that have been the result of a crash or which may increase the risk of a crash occurring. In one study, police crash records from fatal crashes were combined with police enforcement records and driving licence records to examine the effect of fines and demerit points on crash risk (Redelmeier et al., 2003). Table 2-3 contains a selection of studies which employed more than one data source including self-reports, police enforcement, crash records and medical records.

The primary disadvantage of all of these methods is the limited ability to monitor the same drivers across time and location. Although some time series data can be

collected by administering multiple surveys to the same drivers or using licensing records to retrieve a history of driving convictions, the majority of driving activity is not accounted for in these datasets. This makes it impossible to determine the frequency and magnitudes of some key measures of driver behaviour including speeding, acceleration and braking.

Table 2-3: Selection of studies employing multiple traditional data sources

Citation Behaviours and Factors Studied Enforce-Police ment

Police

Crash Medical _Report Self- (Cooper, 1997) Speeding and crash involvement Y Y ― ― (Redelmeier et

al., 2003) Traffic law enforcement and its effect on fatal vehicle crashes Y Y ― ― (McEvoy et al.,

2005) Drivers‘ use of mobile telephones ― b ― Y Y (Patil et al.,

2006) Driver behaviour and personality Y Y ― Y (Williams et al.,

2006) Speeding Y ― ― ― c

(McEvoy et al.,

2007a) Driver distractions ― ― Y Y

(Vassallo et al.,

2007) Risky driving behaviour among young drivers Ya ― ― Y (Chen et al.,

2009) Road crashes in rural areas by young drivers Y Y ― Y (Ivers et al.,

2009) Novice drivers‘ risky behaviour, perceptions and crash risk Y Y ― Y (Tarko and

Azam, 2011) Pedestrian injuries ― Y Y ―

(Wundersitz and

Baldock, 2011) behaviour, extreme driving behaviour Road system failures, illegal driving Y Y Y Y ― Indicates data source was not used.

a _{Police enforcement data was not used but telephone records were obtained from the}

telecommunications providers.

b _{Vehicle speeds were measured from the road side and matched to licence data using the licence plate}

number.

c _{Only used to assess validity of self-reported data.}