1) relationship between crash frequency and pavement surface


Improving road safety through proper pavement
engineering and maintenance should be one of the major objectives of engineer.
When pavements are evaluated in terms of safety, a number of factors related to
pavement performance are raised, such as roughness, rutting, cracking, mobility
& speed (Cenek et. al. 2014). Each year there are huge annual reports on
traffic accident in Pakistan. According
to Pakistan Bureau of Statistics, in the last 10 years data on traffic
accidents present a terrible picture, as average 15 people died every day in
traffic accidents across the country (Traffic accident report, 2016 P.P 16). Therefore discussion of
such road safety issues as road safety modeling and pavement safety
measurements and criteria is necessary. The main pavement engineering
relationships associated with road safety should be identified, and the various
aspects of road safety related to pavement performance indicators should be

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With the passage of time, vehicles movement, and environmental
conditions road pavement deteriorate.  If
this deterioration is not properly addressed, the amount of surface distress
will increase and be harmful to traffic. 
In this sense, pavement surface characteristics are a significant issue
because of its influence in preserving roadway safety. Maintaining these
characteristics during pavement construction or rehabilitation may lessen or
even prevent crashes and incidents related to loss of vehicle control, slipping,
and excessive skidding.

Many road crash investigations and statistical analysis have
suggested that there is a relationship between crash frequency and pavement
surface characteristics (Noyce et. al.
2007). Additionally, a recent paper has suggested that little has been
done to incorporate pavement management and maintenance into roadway safety
evaluations (Tighe et. al. 2000).  Thus,
research is needed to confirm the relationship between crash frequency and
pavement surface characteristics, and to develop strategies to incorporate
these findings in roadway safety evaluations.





Following are the main objectives of this


To evaluate the correlation between traffic oriented parameters,
roadway safety and pavement performance indicators. 

To identify / estimate threshold values of pavement performance
indicators, after which there is a need of improvement.




Various studies have been done using pavement
performance indicators i.e roughness, rutting, cracking, macro texture and skid
resistance to find its relationship with traffic safety. All of the studies show
that there is a strong relationship between pavement performance indicators and
traffic safety.


Salimi et. al. (2015) evaluated
the effect of friction behavior of tire with road surface in different road
conditions in winter i.e bare dry, dry with ice path and three levels of snow
surface which can be directly related to road safety. This study was done by
driving trucks at target speed of 30, 50 & 60 km/h on different road
conditions. No considerable correlation between vehicle speed and
the friction measurements for bare dry, ice- and snow-covered conditions was
found. But bare dry asphalt surface had the highest Halliday Friction Number
(HFN), presence of ice reduced the dry surface friction by 55%. For light,
moderate and heavy snow on the dry surface reduced the HFN further than ice, by
69, 75, and 81%. Analysis of the effect of number of truck passes over ice at  -3.5 and -5 °C showed that ice can become more
slippery after each pass of traf?c but for light snow, even at low temperatures
(<-10 °C), passes of traf?c will melt the snow through frictional heat and result in higher friction values.   A similar study was done by Najafi et. al. (2015). He investigated the effect of friction on roadway safety on urban roads. Friction was measured using ribbed tire, locked-wheel skid trailer and their regression analysis was done by using ANOVA. Friction was measured for both wet and dry road condition. Friction is a significant factor that affects the ratio of both wet and dry road condition, vehicle accidents on urban roads. Seasonal variation and temperature changes can also affect the friction measurements. Relationship between friction and accidents is not linear, so some logarithmic transformation was used in developing the regression equations. Relationship developed in this research can be used by designers to define the acceptable level of friction for different roads.   Wang et. al (2006) examined the effect of speed on road safety. Study illustrate that high speed limits on signalized intersections could result in rear end crashes. As the speed limit increases, drivers attempt to travel into the dilemma zone, as they may not be able to implement the intersection crossing or implement the stopping action safely at the start of yellow. However, at lower speed limits the drivers can easily take braking action or change lanes to avoid the impact or striking of the leading vehicle.   Chan et. al. (2009) studied the effect of surface roughness using International Roughness Index (IRI), rut depth and Present Serviceability Index (PSI) on crash frequency for asphalt pavements. He used divided highway in urban environment with a speed limit of 88 km/h and the total length of highway used in analysis was about 117 km. It was found that rut depth has no significant effect on crash rate except for the accidents at night and in rainy weather conditions. On the other hand roughness has a direct relation with the crash rate as crash rate increases with increase in roughness. Different models were developed between roughness, rut depth and PSI with crash rate. This study suggests that rut depth model should not be used for predicting accidents, however roughness and PSI models perform well in predicting crash rate.   Chan et. al.'s finding are consistent with the finding of H.R. Al-Masaeid (2003). He estimated the effect of pavement condition including International Roughness Index (IRI), Present Serviceability Index (PSI) and rut depth and pavement geometry on rural road accidents. For this study 32 road segments were selected from 12 primary rural roads, which shows that by increasing IRI level or by decreasing PSI, single vehicle accident rate will decrease but it would increase multiple vehicle accident rate. This study also shows that by increasing roughness, no. of vertical curves and no of intersection, it would increase multiple vehicle accident rate. Saplioglu et. al. (2012) investigated the effect of skid resistance on road accidents at the intersection of the road. Four, four leg intersections were selected which have the same properties. In this study skid resistance was measured in terms of texture depth. This study shows that when texture depth decreases, skid resistance also decreases resulting in high chances of the accidents. When the average texture depth was 0.75mm probability of accident occurrence was 15%, when texture depth became 0.5mm then the probability of accident was 85%.   Furthermore Hussein et. al. (2016) evaluated the effect of surface condition including rutting, skid resistance and roughness on traffic safety at signalized intersections. They studied the crash rate at signalized intersection before and after improvements were made for road surface conditions. Analysis period of 3,4 & 5 years were selected based upon the data available before and after improving the surface condition. This study shows that before and after the treatment there was a difference in crash type and most of the accidents occurred at the speed of 60 – 80 km/h. It was seen in this study that after the treatment, accidents due to roughness were considerably low. However with increased rutting a reduction in accidents was observed.   Cairney et. al. (2008) investigated the relationship between road surface characteristic (including macro texture, rutting & roughness) and crashes for rural roads. Roads selected in this study was two-way undivided and the speed limits was 100 km/h. This study shows that with the decrease in macro texture (below 1.8mm) traffic accidents increases. They could not find a reliable relation between rutting and crash rate and they found that with the increase in roughness crash rate also increases but only when traffic volume is high.   A similar study, but including only rutting and crash rate was done by Cenek et. al. (2014). This study was done for New-Zeeland state highway network, which results in that crash rate slightly decreases as rut depth increases over the normal range of rut depth particularly for dry crashes because driver normally reduce speed in that area in order to keep vehicle in control. This study shows that even with the rut depth more than 10mm there was no indication of an increase in crash rate but there was increase in crash rate when there was water on the road surface.   Noyce et. al. (2007) studied the relationship between asphalt mix design, skid friction and roadway safety. Additionally this research studied relationship between macro texture and friction for high speed roads. This research show that for a wet pavement, with the decrease in skid friction, crash rate increases. Relationship between Mean Texture Depth (MTD) and friction comes inversely proportion which was against their prediction. According to this research dense graded asphalt mixes has lowest mean texture depth value resulting in high friction value. This research suggested that minimum of 35 FN value should be maintained for safe traffic operation.   5)      RESEARCH METHADOLOGY:-   Tasks are developed for determining the relationship and their analysis between different pavement performance indicators and road safety as shown in Fig 1. ·         Task 1 :- Literature review will be conducted to find out any information available regarding impacts of pavement performance indicators on traffic oriented parameters and roadway safety.   ·         Taks 2 :- Selection of the test sites for research. Test site should be selected on the basis of pavement performance indicators, where these indicators vary from each other and can affect road safety.   ·         Task 3 :- Field data collection should be done for selected sites based on the procedure mentioned below in data collection methods.   ·         Task 4:- Data regarding selected roadway safety & traffic oriented parameters will be collected using techniques and surveys, mentioned below.   ·         Task 5 :- Based on the data collected, relationships between pavement performance indicators under study with traffic oriented parameters and with the crash data will be developed, for roadway's safety measurement.