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  • 标题:Evaluation of road traffic safety level in the state main road network of Latvia/Latvijos valstybines reiksmes magistraliniu keliu tinklo avaringumo vertinimas/Latvijas galvenas skiras autocelu tikla satiksmes drosibas limena novertejums/Liiklusohutuse hindamine Lati riigi pohimaanteevorgul.
  • 作者:Lazda, Ziedonis ; Smirnovs, Juris
  • 期刊名称:The Baltic Journal of Road and Bridge Engineering
  • 印刷版ISSN:1822-427X
  • 出版年度:2009
  • 期号:December
  • 语种:English
  • 出版社:Vilnius Gediminas Technical University
  • 摘要:Widely in the world to analyse and estimate an accident situation in civil engineering many different methodologies and methods are used (Giretti et al. 2009; Hola 2009; Zavadskas, Vaidogas 2008; 2009). Different methods for the evaluation of sustainable safety (Vaidogas, Juocevicius 2008) and road traffic safety level may be used to determine dangerous sections on roads (Kapski 2006; Kapski et al. 2007; Lama et al. 2006). One of the most frequently used criteria for safety evaluation not only on roads is accident frequency (AF) and accident rate (AR) (Hola 2007; Sokolovskij 2007; Sliupas 2009).
  • 关键词:Highway engineering;Traffic accidents;Traffic safety

Evaluation of road traffic safety level in the state main road network of Latvia/Latvijos valstybines reiksmes magistraliniu keliu tinklo avaringumo vertinimas/Latvijas galvenas skiras autocelu tikla satiksmes drosibas limena novertejums/Liiklusohutuse hindamine Lati riigi pohimaanteevorgul.


Lazda, Ziedonis ; Smirnovs, Juris


1. Introduction

Widely in the world to analyse and estimate an accident situation in civil engineering many different methodologies and methods are used (Giretti et al. 2009; Hola 2009; Zavadskas, Vaidogas 2008; 2009). Different methods for the evaluation of sustainable safety (Vaidogas, Juocevicius 2008) and road traffic safety level may be used to determine dangerous sections on roads (Kapski 2006; Kapski et al. 2007; Lama et al. 2006). One of the most frequently used criteria for safety evaluation not only on roads is accident frequency (AF) and accident rate (AR) (Hola 2007; Sokolovskij 2007; Sliupas 2009).

The analysis done by authors covers the state main road network in Latvia. The function of the state main roads is to provide connections with foreign countries and capital cities of foreign countries. Latvia has 15 state main roads, they lead through 24 out of 26 districts, and their total length in Latvia is 1740.8 km.

Analysis of road traffic accident statistics was carried out basing on the data available at Road Traffic Safety Directorate for the period of three years (2005-2007).

2. Accident frequency

One of the most frequently used analytical methods for determining the road traffic safety level is the calculation of AF. This value was determined for every km of state main roads.

AF = Acc/L x T, (1)

where AF--accident frequency, accident/km); Acc--number of road traffic accidents per 3 years; L--length of analysed road section, 1 km; T--reviewed time period, 3 years.

Usually road sections with similar technical parameters are chosen and average frequency of accidents ([AF.sub.ave]) is calculated for each road section:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII], (2)

where [AF.sub.ave]--average frequency of accidents, accidents/km; [AF.sub.i]-total number of AF in specific section, accidents/km; n--number of sections in general group.

According to PIARC Road Safety Manual the accident frequency limit value is determined which will be regarded as the min dangerous accident frequency [AF.sub.lim]:

[AF.sub.lim] = 2 x [AF.sub.ave]. (3)

After determining the AF for all sections it is compared with [AF.sub.lim]. With this approach the most dangerous road sections according to AF are determined.

3. Accident rate

The AR was determined that characterised the risks to which road users are subjected in a certain road section. The AR was calculated for each road section, as well.

AR = ACC x [10.sup.6]/365 x L x T x N, (4)

where AR--accident rate, accidents/vehicle km x [10.sup.6]; Acc--number of road accidents per 3 years; L--length of reviewed section, 1 km; T--reviewed time period, 3 years; N--annual average daily traffic (AADT) vpd.

The formula given in the PIARC Road Safety Manual is used to determine the limit value of AR; if this value is exceeded it may be stated that the analysed road section is dangerous to traffic:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII], (5)

where [AR.sub.crit]--critical value of AR, accidents/vehicle km x [10.sup.6]; [AR.sub.ave]--average value of AR in specific road network, accidents/vehicle km x [10.sup.6]; T--reviewed time period, 3 years; L--length of reviewed section, 1 km; N--AADT, vpd (for the state main roads AADT = 5305 vpd); C--statistical constant with 95% level of confidence (C = 1.645).

4. Accident frequency and critical accident rate

Basing on the formula given before Eq (3) and Eq (5) [AF.sub.lim] and AR have been found.

Table 1 shows the data on average value of [AR.sub.ave] and [AF.sub.ave] for each state main road. [AR.sub.crit] indicates the limit value of AR which was calculated with respect to the whole state main road network. [AF.sub.lim] indicates the critical value of accident frequency for the whole state main road network.

Relation between traffic volume and AR in the state main road network (Fig. 1) may be expressed as follows:

AR = 1.23364655 - 0.00003516 x N. (6)

Fig. 2 shows that in 99.14% of cases the AR value is in limits between 0 and 5. Reviewing the distribution of AR values we may conclude that at 50% the AF value is approx 0.56 and at 85% the AF value is 1.46.

8846 road traffic accidents have occurred on state main roads in 2005-2007. Out of them 1809 accidents were heavy accidents, 405 persons were killed and 2526 injured.

Considering the AF, the road with the worst properties (AF = 5.74) is the road A4 Riga bypass (Baltezers-Saulkalne), however, considering the AR, the road with the worst properties (AR = 1.96) is the state road A12 Jekabpils-Rezekne-Ludza-Russian border (Terehova).

5. Practical use of accident frequency and accident rate

According to the formulas reviewed above, the AF and the AR was determined for every km of state main roads.

[FIGURE 1 OMITTED]

[FIGURE 2 OMITTED]

As an example the calculations of one state main road A4 Riga bypass (Baltezers-Saulkalne) may be reviewed.

Characteristics of the existing roads:

Road A4 is located in Riga district. Total road length is 20.4 km. Max permitted driving speed outside urban areas is 90 km/h, in urban areas 70 km/h and 50 km/h. In 2005 the AADT on road A4 is shown in Fig. 3.

Analysis of statistical material was done base on the data available at Road Traffic Safety Directorate for three years (2005-2007).

380 accidents happened in the reviewed time period: 82 were heavy road accidents, 15 persons were killed and 140 injured.

In the Table 2 the values of AR are given which were determined according to Eq (4). To determine which road sections are dangerous for traffic the ARcrit was calculated for the whole network of state main roads according to Eq (5) and [AR.sub.crit] = 1.18.

Fig. 4 shows those road sections on state main road A4 where the values of accident factor exceed critical limit values, therefore these road sections may be regarded as dangerous for traffic.

[FIGURE 4 OMITTED]

6. Conclusions

The values of [AR.sub.crit] and [AF.sub.lim] calculated in this paper provide an opportunity to identify dangerous road sections. Calculated values of AR and AF provide an opportunity to define priorities for the needs to reconstruct dangerous road sections in the state main road network of Latvia.

DOI: 10.3846/1822-427X.2009.4.156-160

Received 22 December 2008; accepted 11 November 2009

References

Giretti, A.; Carbonari, A.; Naticchia, B.; De Grassi, M. 2009. Design and First Development of an Automated Real-Time Safety Management System for Construction Sites, Journal of Civil Engineering and Management 15(4): 325-336. DOI: 10.3846/1392-3730.2009.15.325-336

Houa, B. 2007. General Model of Accident Rate Growth in the Construction Industry, Journal of Civil Engineering and Management 13(4): 255-264.

Houa, B. 2009. Methodology of Estimation of Accident Situation in Building Industry, Archives of Civil and Mechanical Engineering 9(1): 29-46. Available from Internet: <http://www. acme.pwr.wroc.pl/repository/229/online.pdf>.

Kapski, D.; Leonovich, I. 2006. Improvement of Road Traffic Safety on The Basis of Forecasting a Potential Danger in Places of Conflict Situations, The Baltic Journal of Road and Bridge Engineering 1(2): 83-92.

Kapski, D.; Leonovich, I.; Ratkeviciute, K. 2007. Theoretical Principles of Forecasting Accident Rate in the Conflict Sections of the Cities by the Method of Potential Danger, The Baltic Journal of Road and Bridge Engineering 2(3): 133-140.

Lama, A.; Smirnovs, J.; Naudtuns, J. 2006. Road Traffic Safety in the Baltic States, The Baltic Journal of Road and Bridge Engineering 1(1): 63-68.

Sokolovskij, E. 2007. Automobile Braking and Traction Characteristics on the Different Road Surfaces, Transport 22(4): 275-278.

Sliupas, T. 2009. The Impact of Road Parameters and the Surrounding Area on Traffic Accidents, Transport 24(1): 42-47. DOI: 10.3846/1648-4142.2009.24.42-47

Vaidogas, E. R.; Juocevicius, V. 2008. Sustainable Development and Major Industrial Accidents: the Beneficial Role of Risk-Oriented Structural Engineering, Technological and Economic Development of Economy 14(4): 612-627. DOI: 10.3846/1392-8619.2008.14.612-627

Zavadskas, E. K.; Vaidogas, E. R. 2008. Bayesian Reasoning in Managerial Decisions on the Choice of Equipment for the Prevention of Industrial Accidents, Inzinerine Ekonomika--Engineering Economics 5(60): 32-40.Zavadskas, E. K.; Vaidogas, E. R. 2009. Multiattribute Selection from Alternative Designs of Infrastructure Components for Accidental Situations, Computer-Aided Civil Infrastructure Engineering 24(5): 346-358. DOI: 10.1111/j.1467-8667.2009.00593.x

Ziedonis Lazda (1), Juris Smirnovs (2)

(1,2) Faculty of Civil Engineering, Riga Technical University, Azenes 16, 1048 Riga, Latvia

E-mails: (1) ziedonis.lazda@csdd.gov.lv; (2) smirnovs@bf.rtu.lv
Table 1. [AR.sub.ave] and [AR.sub.ave] on Latvian
main roads in 2005-2007

 Number of

Road heavy
No. accidents accidents

A1 630 123
A2 937 192
A3 475 100
A4 380 82
A5 460 75
A6 1563 328
A7 590 141
A8 505 132
A9 926 203
A10 997 211
A11 111 17
A12 747 103
A13 485 95
A14 33 6
A15 7 1
Total 8846 1809
[AF.sup.lim]
[AR.sup.crit]

 Number of

Road
No. fatalities injured

A1 28 175
A2 46 276
A3 20 142
A4 15 140
A5 23 106
A6 69 461
A7 30 199
A8 40 138
A9 49 294
A10 33 313
A11 2 24
A12 27 127
A13 19 124
A14 2 5
A15 2 2
Total 405 2526
[AF.sup.lim]
[AR.sup.crit]

Road
No. [AF.sub.ave] [AR.sub.ave]

A1 2.04 1.05
A2 1.58 0.98
A3 1.28 0.94
A4 5.74 1.56
A5 3.62 1.05
A6 1.69 0.86
A7 2.26 0.62
A8 2.16 0.73
A9 1.54 0.99
A10 1.75 0.71
A11 0.67 1.00
A12 1.48 1.96
A13 0.97 1.28
A14 0.65 1.10
A15 0.26 0.48
Total 1.67 1.03
[AF.sup.lim] 3.34
[AR.sup.crit] 1.81

Table 2. Analysis of road traffic accidents
on road A4 in 2005-2007

 Number of

Road heavy
 km accidents accidents fatalities injured

 0 86 23 3 46
 1 32 6 0 10
 2 16 2 0 4
 3 21 4 1 4
 4 11 2 0 2
 5 38 8 1 11
 6 21 2 0 9
 7 10 2 1 4
 8 16 6 3 13
 9 14 4 0 9
 10 8 2 0 2
 11 7 1 0 1
 12 15 3 0 6
 13 15 1 0 1
 14 13 0 0 0
 15 10 3 1 3
 16 5 3 1 2
 17 11 2 2 1
 18 16 4 2 4
 19 5 1 0 2
 20 5 2 0 2
 21 4 1 0 4
Total 380 82 15 140

Road
 km AF AR

 0 28.67 5.94
 1 10.67 2.21
 2 5.33 1.11
 3 7.00 1.45
 4 3.67 0.76
 5 12.67 2.63
 6 7.00 1.68
 7 3.33 0.80
 8 5.33 1.28
 9 4.67 1.12
 10 2.67 0.64
 11 2.33 0.90
 12 5.00 1.94
 13 5.00 1.94
 14 4.33 1.68
 15 3.33 1.29
 16 1.67 0.75
 17 3.67 1.65
 18 5.33 2.40
 19 1.67 0.75
 20 1.67 0.75
 21 1.33 0.60
Total 5.74 1.56

Fig. 3. AADT on state main road A4 Riga bypass
(Baltezers-Saulkalne)

4.87 9889
9.35 9016
14.29 7702
20.45km 6064

Note: Table made from bar graph.
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