Safety ranking of the Lithuanian road network of national significance/Eismo saugumo lygiu nustatymas Lietuvos valstybines reiksmes automobiliu keliuose/Lietuvas nacionalas nozimes celu tikla drosibas ranzejums/Rahvusliku tahtsusega Leedu teedevorgu ohutushindamine.
Jasiuniene, Vilma ; Cygas, Donatas ; Ratkeviciute, Kornelija 等
1. Introduction
Improvement of road traffic safety in Lithuania as well as other EU
Member States still remains a priority field of transport development.
Road accidents cause not only large moral but also economic losses.
Analysis made by Elvik (2000) showed that losses due to road accidents
make 1-2% of GDP.
Traffic safety largely depends on human, vehicles and road
infrastructure (Elvik 2011; Grislis 2010; Orfila et al. 2010;
Prentkovskis et al. 2010; Naevestad, Bj0rnskau 2012; Schulze, Kossmann
2010; Valiunas et al. 2011). Road infrastructure has a great effect on
the accident risk but also to the severity of the accidents. Engineering
solutions of roads can protect people from injuries in accidents but
they even modify people's behaviour, which can have a great effect
in preventing accidents.
In 2008, the European Parliament and the Council adopted the
Directive 2008/96/EC on Road Infrastructure Safety Management which
defines four procedures for the road infrastructure safety management:
--road safety audit;
--road safety inspection;
--road safety impact assessment;
--road network safety ranking and ranking of high accident
concentration sections.
According to the European Commission the implementation of the
Directive 2008/96/EB has the potential of saving 600 lives and avoiding
7000 serious injuries every year across the EU on the TEN-T network
only.
In 2011, Lithuania prepared the National Traffic Safety Development
Program for 2011-2017. The program defines the targets reaching of which
would help to reduce the number of accidents and the number of traffic
participants injured and killed on roads. The strategic objective of
this program--improve traffic safety situation so that by the number of
killed traffic participants per 1 million population in Lithuania in no
more than the average of the 10 EU states showing the best results in
this field (or no more than 60 people killed/1 million population). This
objective will be implemented based on the following priorities:
--safe behaviour of traffic participants;
--safe roads;
--safe vehicles;
--speedy and high quality first-aid to traffic participants;
--modern information technologies.
Network safety ranking is a method for identifying, analysing and
classifying sections of the existing road network according to their
potential for safety development and reduction of the number and
severity of accidents on those sections. When selecting road sections
for the analysis of the network safety ranking a potential to reduce the
number of accidents is taken into consideration. Road sections are
classified into separate categories, i.e. the roads of national
significance are divided into homogenous sections (based on road
category, speed limit, traffic volume and composition, similar road
environment, etc.). Road sections of each category are studied and
classified by the factors related to road safety, such as the number of
accidents, traffic flow and traffic type. For the purpose of network
safety ranking a priority list is made of all-category road sections
where with the help of infrastructure improvements good results are
expected.
Ranking of high accident concentration sections--is a method to
identify, analyse and rank sections of the road network which have been
in operation for more than three to five years. Identification of road
sections with a high accident concentration takes into account the
existing traffic volume per unit of road length or intersection, traffic
composition and data on fatal and injury accidents.
Procedures defined by above definitions are interrelated and called
the Safety Ranking and Management of the Road Network in Operation.
According to the Directive 2008/96/EB "network safety
ranking" means a method for identifying, analysing and classifying
parts of the existing road network according to their potential for
safety development and accident cost savings. Two main objectives of
this procedure can be distinguised:
--to identify and analyse the most dangerous road sections in order
to more precisely target the traffic safety funds and to obtain the best
possible result reduction of accidents and their victims at the lowest
possible cost;
--to assess all sections of the road network and to compare them
according to their accident potential. This means to identify road
sections where a potential number of road accidents is higher than in
other similar sections.
Effective work with the black spots and high accident concentration
sections leads to their elimination in time and network safety
management becomes the main reactive activity of traffic safety. In
practice this can be seen as transition from remedial and retrospective
considerations to preventive and prospective way of working.
2. Methodology for road network safety ranking
A central question in relation to application of network safety
ranking is how the road system should be divided into a smaller road
sections and how long these sections should be. S0rensen and Elvik
(2008) propose to use the following principles.
Section based principles. In the first principle, the road system
is divided into sections that are homogeneous with regard to selected
traffic and road design parameters that have significant influence on
the number of accidents.
Point based principles. The second principle is a point based
principle, where intersections, towns or other "points" are
used as division points.
Accident based principles. The third principle is based on
registered accidents in the identification period. Either there has to
be a certain number of accidents on each road section or there has to be
a uniform accident concentration or pattern on each road section.
Combination. The last principle is to combine the previously
described principles.
An obvious opportunity is to combine the first two principles. The
two principles differ a lot from each other, but in practice, they will
result in more or less the same division and can therefore
advantageously be combined. The reason that the two principles
approximately give the same result is that major changes in road design
and traffic obviously coincide with larger intersections and towns. To
ensure reliable identifications and a potential for reducing the number
of accidents the first two principles can be combined with the third
principle that each road section has to have a certain number of
accidents (Lynam et al. 2003a; 2003b). It is recommended that the road
and traffic based division principles are used. The argument is that
these principles can be used together with the model based
identification method, where it is essential to have homogeneous road
sections for the estimation of the general expected number of accidents.
In addition, the advantage is that the principles more or less will
result in the same division of the road system for different time
periods, which make it possible to compare the accident level for
different time periods for each road section. Finally, the advantage of
the point based principle is that it gives a rational, easy and natural
division (S0rensen, Elvik 2008).
In spring 2011, the international BALTRIS project was started to be
implemented the specific objective of which is to develop tools and
build capacity/competence for a better safety management of road
infrastructure in the Baltic Sea Region. The project focuses on the
exchange of experiences, knowledge and joint development of road
infrastructure safety management procedures. BALTRIS is led by the
Lithuanian Road Administration under the Ministry of Transport and
Communications of the Republic of Lithuania and the project partners
are: Lithuanian Road Administration, Estonian Road Administration,
Swedish Transport Administration, Vilnius Gediminas Technical
University, Tallinn University of Technology, Lund University and Riga
Technical University (Laurinavicius et al. 2012).
During the BALTRIS project a comprehensive review of investigations
in different countries in the field of network safety ranking was
carried out, the exchange of the best practice was performed and
recommendations were given for the implementation of this procedure
defined in the Directive 2008/96/EC (Laurinavicius et al. 2012).
Procedures for the road network safety and high accident
concentration sections ranking can be divided into 5 stages (Table 1):
Stage 1. Data collection. Data collection is a very important part
of the implementation of network safety ranking. The collected data is
as follows:
--accidents--location of the accident, accident type, date and hour
of accident, accident severity, including number of fatalities and
injured persons, alcohol level, data on the vehicles involved (type,
age, country, safety equipment if any, data of last periodical technical
check according to applicable legislation), road surface and weather
conditions etc.;
--traffic volume--annual average daily traffic, proportion of light
and heavy vehicles;
--road parameters--road status or function, road significant
(type), road category, cross section including number of lanes, lane
width, shoulder and the presence of bicycle lanes and side strips,
possibility for oncoming traffic, speed limit, lightning, markings,
alignment, roadside obstacles, number and design of intersections and
access roads, junction type including signalling;
--the surrounding environment--rural or urban area).
Stage 2. Definition of road groups and junction groups. The groups
and subgroups of road sections are defined by 4 criteria. First
criterion--road type and category. Based on this criterion the whole
road network is divided into 4 groups: motorway, main roads, national
and regional roads; urban roads. Second criterion--cross-section. Based
on this criterion the roads are divided into subgroups: road with median
and roads of different width of the carriageway without median. Third
criterion - speed limit. Based on this criterion the subgroups are
divided into smaller subgroups according to the speed limit, i.e. 50
km/h; 70 km/h; 80 km/h; 90 km/h; 100 km/h; 110 km/h; 130 km/h. Fourth
criterion--traffic volume. Based on this criterion the subgroups are
divided into smaller subgroups according to the different traffic
volume.
The groups defined by the first criterion are divided into groups
by the second criterion and so on. Having made the division by all
criteria the final number of groups is obtained.
The groups and subgroups of junctions are defined by 3 criteria.
First criterion--junction type. Based on this criterion the junctions
are divided into groups: level crossing T, level crossing X and grade
separate crossing.
Second criterion--road type. Based on this criterion the junctions
are divided depending on which road according to its significance the
main road of the junction belongs to.
Third criterion: traffic volume. This criteria evaluates a
proportion of vehicles entering the junction from the minor road from
the total amount of vehicles entering the junction.
Road sections and junctions are divided into the groups based on
their road and traffic data. The general idea is to build up the groups
so that they describe as well as possible the variation of accident risk
and accident severity.
The authors of this article were able to use very simple accident
prediction models by assuming a constant injury accident rate and
constant severity of accidents in each group. Severity means the number
of killed persons per 100 injury accidents.
By combining the results from the accident prediction model with
the accident history it became possible to make reliable estimates of
expected numbers of accidents and fatalities.
This information could be used in identifying dangerous road
locations. Additionally, it could be used when evaluating the safety
effects of different measures in various locations. In this way, there
is a possibility to create a priority list for road sections where good
results are expected with the help of infrastructure improvements. And
it is also possible to evaluate the effect of road improvements on those
locations.
3. Road network safety management in Lithuania
Based on the given recommendations the specialists of Road
Department of Vilnius Gediminas Technical University in partnership with
the State Enterprise Transport and Road Research Institute and Finnish
Technical Research Centre VTT carried out the safety ranking of the road
network of national significance of Lithuania.
The roads of Lithuania according to their capacity, social and
economic significance are divided into roads of national and local
significance.
The Law on Roads of the Republic of Lithuania, adopted in 1995, the
roads of national significance divides into:
1) Main roads. These are the main Lithuanian roads or their
extensions--carriageways of streets with the highest traffic volumes.
They comprise all roads of national significance included into the
European international road network;
2) National roads. They comprise part of the main road network.
These are roads or their extensions--carriageways of streets with high
traffic volumes connecting the centres of territorial administrative
units of the Republic of Lithuania, as well as transit and tourist
traffic;
3) Regional roads. These are roads which are used to meet the
communication needs of legal or natural persons operating on the
territories of territorial administrative units of the Republic of
Lithuania, and connecting urban and rural residential locations with the
main road network.
Based on data of 1 January 2010, provided by the Lithuanian Road
Administration under the Ministry of Transport and Communications of the
Republic of Lithuania, the road network of national significance
totalled to 21 268.4 km of roads, of which:
--Main roads--1738.5 km;
--National roads--4939.3 km;
--Regional roads--14 590.6 km.
In order to divide road network into homogenous road sections the
2006-2010 data on road accidents, traffic volume, road parameters and
the surrounding environment was collected. Data of the Lithuanian Road
Information System LAKIS was collected into 16 data sets:
1--cross-sections of roads, 2--junctions, 3--railway crossings, 4--high
accident concentration road sections and black spots, 5--road signs,
6--fatal and injury accidents of 2006-2010 (accidents at junctions are
given separately), 7--illuminated road sections, 8--speed measuring
equipment, 9--pedestrian paths, 10--protective fences from people and
wild animals, 11--road sections with the installed guardrail systems,
12--technical categories of roads, 13--average annual daily traffic on
roads; 14--average annual daily traffic at junctions, 15--speed
restrictions on road sections, 16--accidents at junctions.
[FIGURE 1 OMITTED]
Based on the mentioned data the road network of Lithuania was
divided separately into groups of roads and junctions.
3.1. Dividing the road network into homogeneous road sections and
junctions
The groups of road sections were defined by the criteria described
in section 2: road significance; cross-section of road; speed
restrictions and traffic volume. Based on the above criteria 34
homogenous road groups were formed (Fig. 1).
Based on the scheme presented in Fig. 1 the Lithuanian network of
the roads of national significance was divided into 13 254 homogenous
road sections, the average length of one homogenous section being 2.31
km. The largest group of homogenous road sections is the group No. 3
which comprises national and regional roads, as well as gravel roads.
The total length of the group No. 3 is 16 266.99 km, the roads are
divided into 7770 separate homogenous road sections the average length
of which is 2.06 km. The average annual daily traffic of this group of
roads is the lowest compared to the other road groups--2951 vehicles/day
(vpd). Data on homogenous road sections is given in Table 1.
The groups and subgroups of junctions were determined based on
three criteria: type of junction, road significance and traffic
distribution at the junction (i.e. a proportion of vehicles entering the
junction from the minor road from the total amount of vehicles entering
the junction).
Based on the mentioned criteria 14 homogenous groups were
determined (Fig. 2). Table 2 gives the groups and subgroups of junctions
determined by the criteria described in section 2.
[FIGURE 2 OMITTED]
3.2. Lithuanian road network safety ranking
Having accomplished the division of Lithuanian road network into
homogenous road sections and junctions, based on the groups of road
sections and junctions given in subsection 3.1, the road network safety
ranking was carried out. Road sections and junctions get into the group
of road sections and the group of junctions with their own accident
history. To distinguish the road network safety levels it is necessary
to determine the total accident level in each road group or junction
group, i.e. to calculate the accident rate (AR) in each road or junction
group. After calculating the accident rate the accident severity shall
be taken into consideration. For road links the accident rate AR shows
the number of fatal or injury accidents per vehicle mileage (often
expressed as accidents/100 million vehicle kilometres). The accident
rate is calculated by Eq:
A[R.sub.i] = [A.sub.i][10.sup.8]/365[L.sub.i]AD[T.sub.i]m
where: [A.sub.i]--the number of accidents during 5 years on a
homogenous road section; [L.sub.i]--the length of a homogenous road
section, km; AAD[T.sub.i]--average annual daily traffic on a homogenous
road section, vpd; m--the number of years, 5 years.
For junctions the accident rate is calculated respectively,
however, the rate is calculated per millions of vehicles entering the
junction. Thus, instead of NL (Eq (1)), the number of vehicles entering
the junction is used (calculated by AADT on the legs of the studied
junction, vpd).
After implementation of this stage the current network safety level
was obtained in each road group or junction group. The average accident
rate of the groups of roads or junctions allows us to determine the
safety level of the group within the road network, i.e. from the total
road network to distinguish the groups of roads and junctions having the
highest numbers of accidents in relation to driven kilometres (or
arriving vehicles in the case of crossings).
When defining road group safety levels the highest average accident
rate was determined in the subgroup "Gravel roads" of the
group No. 3 (Fig. 3). This subgroup contains 2208 homogenous road
sections the length of which is 6303.14 km, i.e. this subgroup makes 30%
of the total length of the roads of national significance. The average
accident rate of this subgroup amounts to even 39.23, whereas, the
average accident rate of all the roads of national significance is
15.56. This could be explained by the fact that the road sections of
this subgroup represent a prevailingly low traffic volume, low road
standards and low amount of enforcement.
When defining junction group safety levels, the largest average
accident rate was determined at four-leg at grade junctions--16.64,
whereas, the average accident rate of the whole junctions is 12.80. The
four-leg at grade junctions make 32% of the total number of junctions on
the roads of national significance. The lowest accident rate was
determined in the group of grade-separated junctions--4.65. A histogram
on the average accident rate of the groups of junctions is given in
(Fig. 4).
After this phase, hazardous road sections are identified in terms
of the high expected numbers of accidents. For this purpose the average
accident risks were used as simple accident prediction models (Elvik
2007, 2008; Peltola et al. 2012; S0rensen, Elvik 2008).
By combining modelled accident number with the accident history the
authors of this article received the estimates of accidents to be
expected in the future with no measures. Additionally, utilising average
severity figures, the fatality estimates were even received. These
empirical Bayesian estimates are as reliable as possible, so they are a
good basis for locating the most dangerous road locations and estimate
the effect of safety measures on those locations.
4. Conclusions
Under restricted financial investments to roads, it is necessary to
ensure that the traffic safety improvement measures are implemented on
the most dangerous road sections and on those road sections where it is
possible with the min costs to achieve the max reduction in accident
number. For this purpose, the road network is divided into homogenous
road sections and the most dangerous sections safety shall be
determined.
The division of road network into homogenous road sections allows
to determine and rank road sections where different traffic safety
measures will give highest accident reductions.
The division of road network into homogenous road sections is
useful for developing mathematical accident models for a particular road
section and to forecasting the number of accidents on it.
Safety ranking of the Lithuanian road network of national
significance was carried out according to the section based and point
based principles.
Road sections, situated between the junctions, were divided
according to the section based principle. Using 2006-2010 data on road
network 4 large groups of homogenous road sections were defined. Based
on certain criteria, these were further divided into 34 subgroups of
homogenous road sections. The road network was divided into 13 254
homogenous road sections.
When defining road network safety levels the highest average
accident rate was determined in the subgroup "Gravel roads".
This subgroup represents 30% of the total length of the roads of
national significance. Taking this into consideration, institutions
responsible for the road network safety management must pay a special
attention to improving traffic safety on gravel roads. Considering the
low traffic volumes, the measures on these roads should be very cheap.
Respectively one should consider even more expensive measures on roads
having high expected accident and fatality densities.
The roads of national significance contain 1454 junctions, which
according to the point based principle were divided into 3 large groups
of homogenous junctions which based on certain criteria were further
divided into 14 subgroups of homogenous junctions.
When defining road network safety levels at junctions, the largest
average accident rate was determined at four-leg at grade junctions
which make 32% of the total number of junctions on the roads of national
significance. Avoiding four-leg crossings and building them into two
three-leg crossings, round abouts or level crossings should be
considered from the safety reasons. The lowest accident rate was
determined in the group of grade-separated junctions.
The created expected accident and fatality fatigues allow
determining the most dangerous sections and crossing from each road
group. Systematic review of those dangerous locations should be done and
safety measures defined for them based on expected safety benefits
easily available using the developed analysis procedures.
doi: 10.3846/bjrbe.2012.18
Acknowledgements
The research has been funded by the Lithuanian Road Administration
under the Ministry of Transport and Communications of the Republic of
Lithuania. Lithuanian road network safety ranking has been made by VTT
Technical Research Centre of Finland, Vilnius Gediminas Technical
University and Lithuanian SE Transport and Road Research Institute. The
authors wish to express their gratitude to Mr. Mikko Virkkunen from
Simsoft Oy Finland for his invaluable help in the accomplishment of
research.
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Received 3 August 2011; accepted 10 March 2012
Vilma Jasiuniene (1) ([mail]), Donatas Cygas (2), Kornelija
Ratkeviciute (3), Harri Peltola (4)
(1,2,3) Dept of Roads, Vilnius Gediminas Technical University,
Sauletekio al.11, 10223 Vilnius, Lithuania
(4) VTT Technical Research Centre of Finland, Vuorimiehentie 3,
Espoo, Finland, P.O. Box 1000, 02044 VTT
E-mails: (1) vilma.jasiuniene@vgtu.lt; (2) dcyg@vgtu.lt; (3)
kornelija.ratkeviciute@vgtu.lt; (4) Harri.Peltola@vtt.fi
Table 1. Typical stages in road network safety and high accident
concentration sections ranking
Stage Explication
1. Data collection Collection of data on roads, traffic
and accidents
2. Definition Definition of road groups and junction
groups
3. Dividing Dividing the road network into
homogenous road sections and
junctions
4. Identification Road network safety ranking and
identification of hazourds road sections
5. Analysis In office analysis of hazourds road
sections and junctions and on-site
observations of road-user behaviour
Table 2. Main data on groups and subgroups of homogenous
road sections
Subgroup Subgroup Road
AADT, length,
vpd km
1. Separated driving
directions
111. Motorway < 9000 160.01
112. Motorway 9000-12000 92.34
113. Motorway [greater than or 59.11
equal to] 12000
121. Four lanes, median < 9000 40
[less than or equal to]
90 km/h
122. Four lanes, median, 9000-12000 57.4
[less than or equal to]
90 km/h
123. Four lanes, median, [greater than or 52.7
[less than or equal to] equal to] 12000
90 km/h
130. Four lanes, median, 59.24
100 km/h
140. Four lanes, median, 14.05
110 km/h
Total: 534.85
2. Main roads, rural
211. Main road, 9 m < 3000 103.14
212. Main road, 9 m 3000-6000 381.32
213. Main road, 9 m [greater than or 244.51
equal to] 6000
221. Main road, 8 m < 4500 269.07
222. Main road, 8 m [greater than or 39.22
equal to] 4500
231. Main road, < 4500 45.98
[less than or equal to] 7 m
232. Main road, [greater than or 37.83
[less than or equal to] 7 m equal to] 4500
Total: 1121.07
3. Minor roads, rural
311. Minor roads, 9 m < 4500 173.44
312. Minor roads, 9 m [greater than or 89.93
equal to] 4500
321. Minor roads, 8 m < 1500 232.27
322. Minor roads, 8 m 1500-4500 598.04
323. Minor roads, 8 m [greater than or 98.52
equal to] 4500
331. Minor roads, 7 m < 1500 2054.54
332. Minor roads, 7 m 1500-4500 752.46
333. Minor roads, 7 m [greater than or 97.11
equal to] 4500
341. Minor roads, < 1500 5242.27
[less than or equal to] 6 m
342. Minor roads, 1500-4500 610.57
[less than or equal to] 6 m
343. Minor roads, [greater than or 14.7
[less than or equal to] 6 m equal to] 4500
351. Gravel roads < 150 3633.82
352. Gravel roads 150-300 2015.21
353. Gravel roads [greater than or 654.11
equal to] 300
Total: 16266.99
4. Urban roads
411. Urban sign, 50 km/h < 3000 3067.83
412. Urban sign, 50 km/h 3000-6000 174.09
413. Urban sign, 50 km/h [greater than or 82.3
equal to] 6000
420. Urban sign, 70 km/h 3.99
430. Urban sign, 80 km/h 12.42
Total: 3340.63
TOTAL: 21263.54
Subgroup The number The average length
of homogenous of homogenous road
road sections sections, km
1. Separated driving
directions
111. Motorway 23 6.96
112. Motorway 14 6.6
113. Motorway 16 3.69
121. Four lanes, median 36 1.11
[less than or equal to]
90 km/h
122. Four lanes, median, 19 3.02
[less than or equal to]
90 km/h
123. Four lanes, median, 29 1.82
[less than or equal to]
90 km/h
130. Four lanes, median, 17 3.48
100 km/h
140. Four lanes, median, 3 4.68
110 km/h
Total: 157 3.92
2. Main roads, rural
211. Main road, 9 m 43 2.4
212. Main road, 9 m 113 3.37
213. Main road, 9 m 95 2.57
221. Main road, 8 m 85 3.17
222. Main road, 8 m 27 1.45
231. Main road, 36 1.28
[less than or equal to] 7 m
232. Main road, 27 1.4
[less than or equal to] 7 m
Total: 426 2.23
3. Minor roads, rural
311. Minor roads, 9 m 182 2.12
312. Minor roads, 9 m 43 2.02
321. Minor roads, 8 m 166 1.4
322. Minor roads, 8 m 238 2.51
323. Minor roads, 8 m 49 2.01
331. Minor roads, 7 m 1119 1.84
332. Minor roads, 7 m 303 2.48
333. Minor roads, 7 m 65 1.49
341. Minor roads, 3116 1.68
[less than or equal to] 6 m
342. Minor roads, 265 2.3
[less than or equal to] 6 m
343. Minor roads, 16 0.92
[less than or equal to] 6 m
351. Gravel roads 1245 2.92
352. Gravel roads 662 3.04
353. Gravel roads 301 2.17
Total: 7770 2.06
4. Urban roads
411. Urban sign, 50 km/h 4568 0.67
412. Urban sign, 50 km/h 222 0.78
413. Urban sign, 50 km/h 100 0.82
420. Urban sign, 70 km/h 4 0.99
430. Urban sign, 80 km/h 7 1.77
Total: 4901 1.01
TOTAL: 13254 2.31
Subgroup Proportion of
AADT, heavy traffic
vpd from the total
AADT, %
1. Separated driving
directions
111. Motorway 7856 15
112. Motorway 10053 17.3
113. Motorway 17637 13
121. Four lanes, median 2060 10.2
[less than or equal to]
90 km/h
122. Four lanes, median, 10548 7
[less than or equal to]
90 km/h
123. Four lanes, median, 19861 14.6
[less than or equal to]
90 km/h
130. Four lanes, median, 21240 15.2
100 km/h
140. Four lanes, median, 19042 16
110 km/h
Total: 13537 13.54
2. Main roads, rural
211. Main road, 9 m 2238 17.6
212. Main road, 9 m 4475 14.8
213. Main road, 9 m 8600 23
221. Main road, 8 m 2862 15
222. Main road, 8 m 6842 14.2
231. Main road, 2975 15.3
[less than or equal to] 7 m
232. Main road, 6396 11.6
[less than or equal to] 7 m
Total: 4913 15.93
3. Minor roads, rural
311. Minor roads, 9 m 4010 26.8
312. Minor roads, 9 m 7385 11.8
321. Minor roads, 8 m 802 11.9
322. Minor roads, 8 m 2616 12.2
323. Minor roads, 8 m 6116 9.2
331. Minor roads, 7 m 579 12.2
332. Minor roads, 7 m 2476 11.1
333. Minor roads, 7 m 6552 9.2
341. Minor roads, 364 11.1
[less than or equal to] 6 m
342. Minor roads, 2376 10.7
[less than or equal to] 6 m
343. Minor roads, 7226 8.5
[less than or equal to] 6 m
351. Gravel roads 86 10.9
352. Gravel roads 206 11.7
353. Gravel roads 518 11.6
Total: 2951 12.06
4. Urban roads
411. Urban sign, 50 km/h 559 1.1
412. Urban sign, 50 km/h 4114 10.6
413. Urban sign, 50 km/h 8616 7.8
420. Urban sign, 70 km/h 23502 14
430. Urban sign, 80 km/h 30371 14.6
Total: 13432 9.62
TOTAL: 8708 12.79
Table 3. The number of homogenous sections of junctions
Junctions group Subgroup of the The number
junctions of homogenous
road sections
1.T-junctions 11. Main road 100
12. Main road 47
13. Main road 25
21. Minor road 266
22. Minor road 265
23. Minor road 195
2. X-junctions 11. Main road 60
12. Main road 47
13. Main road 40
21. Minor road 38
22. Minor road 84
23. Minor road 199
3. Grade-separated 1. Local region 37
junctions 2. Highway auth. 51
Total: 1454
Fig. 3. The average accident rate of the road groups (data of
2006-2010)
Average accident rate
Motorway 5.63
Four lanes, median 9.80
[less than or equal
to]90 km/h
Four lanes, median 6.10
100 km/h
Four lanes, median 4.10
110 km/h
Main roads, 9 m 13.07
Main roads, 8 m 13.45
Main roads, 15.00
[less than
or equal to] 7 m
Main roads, 9 m 15.20
Main roads, 8 m 19.37
Main roads, 7 m 21.93
Main roads, 25.53
[less than
or equal to] 6 m
Gravel roads 39.23
Urban signs, 50 km/h 25.13
Urban signs, 70 km/h 11.6
Urban signs, 80 mkm/h 8.2
Note: Table made from bar graph.
Fig. 4. The average accident
rate of the groups of junctions
(data of 2006-2010)
Average
accident
rate
T-junction 12.57
main road
T-junction 13.53
minor road
X-junction 14.17
main road
X-junction 19.10
minor road
Grade-separated 4.65
junctions
Note: Table made from bar graph.
