Road Safety Performance Indicators

According to Hermans et al. (2008) the concept of Road Safety Performance Indicators has gained popularity in recent years. This may be as a result of the work of projects such as SafetyNet (Hakkert, Gitelman, 2007) and SUNflower (Wegman et al. 2008)

According to Nardo et al (2005) an indicator can be defined as

“a quantitative or qualitative measure that is deduced from a series of observed facts to reveal the relative positions“

The European Transport Safety Council (2001) identified a number of reasons for using Performance Indicators rather than outcomes measures as a means to monitor road safety.

These included:

 Crash outcomes can be highly dependent on chance, with even small variations in the elements of the crash (speed, weather conditions, angle of impact, age of casualties for example) altering the severity of the outcome.

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 Reporting of accidents and injuries is often incomplete

 Crash counts do not always provide adequate information about the underlying processes that lead to accidents and injuries

 Falling fatalities may mean that low numbers of cases present a problem when attempting to analyse a very specific issue, for example, fatalities involving pedestrians over 65 years old.

Hakkert and Gitelman (2007) represented the theoretical basis for Performance Indicators as shown in figure 7, below

Fig 7; Safety Performance Indicator theory

Figure 7 shows how the social cost is the final outcome of the operation of the traffic system. In the ETSC model, this represents the cost of accidents and injuries (for example, lost output, the cost of treating casualties, the attendance at the scene of the emergency services, and the knock-on effect of resultant traffic disruption.) In this model it can also be considered to include the costs of treating the consequences of lack of independent mobility for older people. Accidents and

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fatalities are the “Intermediate outcomes” in the ETSC model, which here would also include increases in depression, and in other physical conditions which were shown in Chapter 2 to be linked to lack of independent mobility for older people. The operational conditions of the next level of the triangle are the element that performance indicators attempt to measure. These result from the outputs of policy – in the case of infrastructure, this could mean the decision to separate motorised and non-motorised traffic in order to maximise traffic throughput or minimise pedestrian accidents.

Indicators can be used for several objectives, such as monitoring performance, identifying trends, predicting problems, assessing policy impact, prioritizing remedial measures, benchmarking and so on. In the work presented here, the objective of using indicators is to incorporate a wider range of information into monitoring the effect of road safety policies than could be achieved only by using outcomes measures such as accidents or fatalities. In this way, the impact of road safety policies on people’s mobility can also be assessed, and the trade-offs between safety and mobility for different groups of road user can be made more explicit.

The European Transport Safety Council highlighted seven areas for which it was felt Performance Indicators for road safety should be calculated. These areas were;

 Alcohol and drugs

 Speeds

 Protective systems

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 Vehicles (passive safety)

 Roads

 Trauma management

These are the topic areas selected for discussion and calculation of SPIs for the SafetyNet project (Hakkert et al 2007) and were also used by Hermans et al. (2008).

However, as has been pointed out by Hakkert and Gitelman (2007), these different areas operate at different levels of the traffic system; Protective systems, daytime running lights, passive safety and trauma management describe the incidence of counter-measures to either reduce accidents (in the case of daytime running lights) or to lower the severity of consequences (in the case of protective systems, passive safety and trauma management). Alcohol and drugs is concerned with human behaviour as a causal factor in accidents. Speed can also be thought of as a human factor. However, as has been explained in Chapter 2, the design of infrastructure can also be a factor in determining vehicle speeds. Selection of the appropriate level of the road safety system for which to calculate performance indicators may be dictated by data availability (or the ease with which it could be acquired). For example, whilst data on the use of daytime running lights may be relatively easy to collect using roadside surveys, data on the proportion of drivers who are driving whilst impaired cannot be collected this way and must therefore be inferred from other data. Where data for Performance Indicator calculation must be inferred from accident data, it will be subject to all of the previously-discussed limitations of this data.

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This work focuses on Performance Indicators related to infrastructure, which include speed limits as one input. The reasons for considering speed as an infrastructure features (as opposed to a human factor) are set out in chapter 2.

Further to selecting the appropriate features of the road safety system on which to focus for Performance Indicator calculation, there are a number of other important considerations to bear in mind. The European Transport Safety Council suggested the following additional requirements of performance indicators:

 Firstly, a causal relationship between crashes and the indicator under consideration must be established.

 Performance Indicators should relate directly to policy; if a region is performing badly with respect to a particular indicator, there must be easily identifiable measures that can be taken to reduce the hazard in the system and improve performance. So, for example, whilst weather conditions may have a causal relationship with crashes, a Performance Indicator for weather conditions for which easily identifiable counter-measures could not be designed would not meet the requirements.

One difficulty with establishing a link between the indicator under consideration and crashes is the role of Exposure to Risk. As was explained in section 2.15 cases where the infrastructure is particularly problematic for older users, some users will choose to avoid it, either by not making the journey at all, or by changing some journey characteristic such as mode choice, route choice, or time of trip. The effect of this will be to reduce the exposure to risk of certain groups of user at certain

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locations: Pedestrian casualties may be very low in some areas, but this may reflect the fact that pedestrians do not use the infrastructure unless they have no alternative. Thus low accident rates may be an indication of barriers to mobility as much as facilitators of safety. This will be discussed further in Chapter 9, where proxy measures of exposure will be explored, but is worth bearing in mind when considering what the nature of the relationship between performance indicators and outcomes-based measures such as number of accidents or number of casualties should be.

For the purposes of calculating the Performance Indicators, the links established by existing work between features of urban infrastructure such as junction complexity, number of lanes of traffic pedestrians have to cross, traffic speeds and the safety of older road users will be assumed to be correct. In chapter 9 accident statistics will be examined in conjunction with proxy measures of road safety, in order to draw conclusions about the nature of the relationship between crash counts, exposure data and Performance Indicators.