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CR 223: A pilot study of the relationship between macrotexture and crash occurrence



Macrotexture refers to variations in the road surface in the range 0.5 mm to 50 mm. It is generally believed to affect braking performance by assisting drainage, thereby preventing the formation of a water film over the road surface, and through hysteresis, the deformation of the tyre which converts mechanical energy into heat. Macrotexture is relatively stable, and can be measured by laser profilometers travelling at highway speed in the course of multi-variable highway condition surveys.

Literature review

To date, few studies examining the relationship between macrotexture and crashes have been undertaken. These studies, conducted in the UK, France and Australia, are in agreement that crash risk is greater at sites with low macrotexture, and that crash risk is relatively unaffected over the rest of the usual range of macrotexture. However, it is difficult to determine how close the agreement is about the point at which risk begins to rise, due to different measurement equipment and units of measurement. The UK and Australian studies show that the proportions of crashes on wet road surfaces were approximately the same for low macrotexture and other sites, suggesting that the drainage function may be less important than commonly believed. The UK study also showed that the relationship between macrotexture and crashes could not be explained by both occurring at sites with higher traffic flows in the vicinity of junctions.

There do not appear to be any studies which have investigated the relationship between macrotexture and stopping distance.


Macrotexture and crash data were obtained from the Great Eastern Highway, Western Australia, the Princes Highway West, Victoria, and the Duke?s Highway, South Australia. Analysis proceeded by locating each crash on the running record of macrotexture. The macrotexture of the section where each crash was located was taken as the macrotexture at the crash site. Sites were identified as rural sites (speed limit greater than 80 km/h) or urban sites (speed limit 80 km/h or less). Distributions of macrotexture were prepared across all sites, and across crash sites.

Analysis was carried out separately for rural and urban sites. For each macrotexture category, the percentage of crash sites was compared with the percentage of all sites. The ratio of crash sites to all sites for each macrotexture category was taken as an indication of the crash risk associated with that level of macrotexture. On the basis of the risk data, sites were classified as low macrotexture or high macrotexture for the next stage of the analysis.

The possible relationship of a number of crash variables to macrotexture was investigated by crosstabulating the number of crashes in each category of interest with macrotexture to create a 2x2 contingency table, except in the case of severity where the contingency table differed for the States according to the number of crash severity categories. The chi square test was used to test for association between the crash variables and macrotexture.


For the Great Eastern Highway, a significant association between crashes and macrotexture was found for both rural and urban sites.

For the Princes Highway West, there was a significant association between macrotexture and crashes for urban sections, and a marginally significant association for rural sections.

For the Dukes Highway, there was a significant association between macrotexture and crashes for rural sections, but no association for urban sections. Note that there were very few urban sections on this road.

There was significant over-representation of low macrotexture at intersection crash sites on rural sections of all three routes (marginally significant in the case of the Duke?s Highway), and at intersection crash sites on urban sections of the Great Eastern Highway. There was also significant over?representation of low macrotexture at the sites of crashes on straight sections on the Great Eastern Highway, but no other significant associations with road alignment.

There was no association between low macrotexture and wet road crashes. The data were also examined for associations between low macrotexture and young driver and heavy vehicle involvement. There was no significant association with young driver involvement. There was insufficient data to do formal testing for heavy vehicle involvement, but the pattern of the data suggests that low macrotexture was underrepresented at the sites of crashes involving heavy vehicles.

Implications for surfacing management based on macrotexture monitoring

The results agree with previous studies regarding the increase in risk with low macrotexture, although there is not close agreement about the precise value of macrotexture at which crash risk begins to rise. The prospects for a surface management process based on macrotexture are therefore good.

On the Great Eastern Highway and the Princes Highway West, 30% and 36.5% of crashes occurred at low macrotexture sites, and the crashes which could be saved by treating all low macrotexture sites was estimated to be 13% and 17% respectively. Twenty-one percent and twenty-nine percent of each route would have to be resurfaced to achieve this. However, it may be possible to target improvements more narrowly at high risk sites. Two possible examples are intersections and curves.

Before a surfacing management process based on macrotexture can be developed, a further study is required to examine the relationship between crash risk and macrotexture in more detail, taking into account intersections, road geometry and road surfacing materials and techniques. A study of vehicle braking distance on surfaces with different macrotexture would also be useful in demonstrating the effects and providing practical guidance in situations where increased macrotexture might be required.

Download Complete Document: CR223_Text_Crash [PDFPDF: 686 KB]

Type: Research and Analysis Report
Sub Type: Consultant Report
Author(s): Cairney P and Styles E
ISSN: 1445 4467
Topics: Crash data, Risk, Road
Publication Date: 10/02/05


Last Updated: 6 May, 2013