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COMPARATIVE STUDY OF REGIONAL CRASH DATA IN TURKEY.

1. INTRODUCTION

Even though there has been significant public policy attention and improvements in traffic safety policies and practices in Turkey, 61 people died per billion vehicle-km in traffic crashes in 2016 (TGDH, 2017; TurkStat, 2018a). In spite of significant improvements in national highway network, there has been an increase in fatal and/or injury (FI) crashes over the last decade (TurkStat, 2018a). The distribution of crashes across the nation is also of importance to transportation system owners. National and local safety programs aim to reduce crashes and the severity of their outcomes within their jurisdictions. Development of geographically appropriate safety strategies requires estimating pertinent crash and exposure data at the relevant spatial scale. While data required to identify safety risks are collected at the local level, published databases are typically available only at larger scales. Thus, there is a need to deduce data at the local level (i.e., lower levels of spatial aggregation) from partially complete or surrogate datasets that are available at a higher level of aggregation.

FI crashes are reported by the traffic police and gendarmerie units according to their areas of responsibility in Turkey. Disaggregate statistics of these crashes are published annually by Turkish Statistical Institute (TurkStat). This aggregate database provides temporal and provincial distribution of the crashes as well as type of vehicles involved, classification of the crash locations as well as gender and age distribution of the crash victims. Due to the lack of disaggregate crash level data at the national level, province and regional variations of traffic safety have not been examined in detail. Recently, Atalay and Tortum (2015) compared the number of fatalities per traffic crashes and per kilometer of road network across the 81 provinces of Turkey. The results showed that number of fatalities per crash are higher in less developed provinces, whereas number of fatalities per length of road network are higher in developed provinces. In other study, Erdogan (2009) studied the provincial level differences in number of FI crashes and number of fatalities. Population and number of registered vehicles were used to quantify safety and results indicated that provinces with higher FI crashes and fatalities were located in the provinces that contain the roads connecting the Istanbul, Ankara, and Antalya provinces. However, there is no study focusing on traffic safety at the regional level in Turkey.

This study provides a comparative analysis of the FI crashes across the seven geographic regions in Turkey from 2006 to 2016 (additional information is provided in Appendix A). The comparisons are performed in relative terms and absolute terms. Since vehicle-km data are not available either province or regional level, number of FI crashes per million population and per million registered vehicles are used to quantify safety. The principal sources of data used in this study is TurkStat.

2. METHODOLOGY

Number of FI crashes per million population and per million registered vehicles were determined for each geographic region annually for the study period. A Geographic Information Systems based thematic maps were used to support these efforts.

Traditional statistical tests based on the normality assumption of the data. Since FI crash rates do not follow normal distribution either across the regions or over the years, nonparametric methods need to be used to study FI crash rates. An appropriate test to use for this purpose is the Kruskal-Wallis nonparametric test. In this study, hypotheses of the Kruskall-Wallis H test was that:

HO: FI crash rates are the same for each region from 2006 to 2016

H1: FI crash rates are not the same for each region from 2006 to 2016.

Based on the Kruskall-Wallis test, the null hypothesis, Ho, is to be rejected at the (100-[alpha]) percent level of confidence if the test statistic, H, falls in the critical region H > [[chi].sub.a.sup.2] with v = (k-1) degrees of freedom. To control the familywise type I error in Kruskall-Wallis H test; the probability of rejecting at least one pair hypothesis given all pairwise hypotheses are true, adjusted p-values are calculated and used to make the decision for each pair. The following equations was used to calculate adjusted p-values for each of pairwise hypothesis. If the adjusted p-value is bigger than 1, it is set to 1.

[p.sub.adj] = pK (K - 1)/2 (1)

where; K = number of pairwise hypothesis, and p = significance level of pairwise hypothesis.

3. RESULTS

FI crash rates were calculated annually for each geographic region based on per million population and per million registered vehicles. The results are presented thematically in Tables B1 to B2 (see Appendix). It is noted that the numbers of the regions are given randomly. In these tables, a graded color pattern is used to indicate FI crash rates. The color gradation ranges from red to yellow or green. Dark red is used to indicate the higher FI crash rates and worse safety records, and dark green is used to indicate lower FI crash rates and best safety records. Lighter red, yellow and lighter green colors are used to achieve gradation.

Table B1 presents FI crash rates of each region per million population for each year during the study period. Table B2 presents FI crash rates of each region per million registered vehicles for each year during the study period. In addition, the average FI crash rates for each measure for the entire 11 year period as a whole are given in these tables. It is seen that FI crash rates for regions significantly increased for each measure from 2006 to 2016. Furthermore, Table B1 and B2 clearly indicate the stability of the relative FI crash rates of regions across the years. They show that regions that tended to have lower FI crash rates, had lower crash rates across the years; and, regions that tended to have higher FI crash rates, had higher crash rates across the years.

Kruskall-Wallis pairwise comparisons implied that FI crash rates per million population are not the same across the regions from 2006 to 2016 (i.e. H = 31.50 > [[chi].sub.0.05,9.sup.2]= 12.59). Fig. 1 and 2 present box plot and 95% confidence interval of FI crash rates of regions per million population. It is seen that FI crash rates in Central Anatolia Region (Region 5), Mediterranean Region (Region 4) and Aegean Region (Region 2) seems relatively higher than the others. FI crash rates in Southeastern Anatolia Region (Region 3) and Eastern Anatolia Region (Region 6) seems relatively lower than the others.

Fig. 3 presents graphical Kruskal-Wallis multiple pairwise comparisons. The number below each region represents the average rank of regional FI crash rates over the 11 years period. Fig. 4 provides Kruskal-Wallis tests results for significant pairwise comparisons. However, most of them are not significant based on adjusted p-value (see Fig. 3). In Fig. 3, yellow lines represent the significant pairwise comparisons based on adjusted p-values. FI crash rates per million population for Central Anatolia Region (Region 5) and Aegean Region (Region 2) are significantly higher than Southeastern Anatolia Region (Region 3) and Eastern Anatolia Region (Region 6); for Mediterranean Region (Region 4) is significantly higher than Southeastern Anatolia Region (Region 3).

Kruskall-Wallis pairwise comparisons implied that FI crash rates per million population are not the same across the regions from 2006 to 2016 (i.e. H = 44.98 > [chi.sub.0.05,9.sup.2] = 16.92). Fig. 5 and 6 present box plot and 95% confidence interval of FI crash rates of regions per million population. It is seen that FI crash rates in Eastern Anatolia Region (Region 6) seems relatively higher than the others. FI crash rates in Marmara Region (Region 1) seems relatively lower than the others. Fig. 7 presents graphical Kruskal-Wallis multiple pairwise comparisons. Furthermore, Fig. 8 provides Kruskal-Wallis tests results for significant pairwise comparisons. However, most of them are not significant based on adjusted p-value. FI crash rates per million registered vehicles for Eastern Anatolia Region (Region 6) are significantly higher than Marmara Region (Region 1), Eagan Region (Region 2) and Mediterranean Region (Region 4). In addition, FI crash rates per million registered vehicles for Marmara Region (Region 1) are significantly lower than Southeastern Anatolia Region (Region 3), Central Anatolia Region (Region 5) and Black Sea Region (Region 7).

Fig. 9 and 10 provide thematic maps based on the average ranks of the provinces for each of the safety measures used in this study. In these maps, the red colored provinces have the highest rates while the green colored provinces have the lowest rates. An examination for Fig. 1 to 2 reveal some interesting patterns in the spatial distribution of the relative safety ranks of the regions. Overall, it can be seen that Marmara Region (Region 1) tend to have best safety records. Relative safety records of Aegean Region (Region 2), Eastern Anatolia Region (Region 6) and Southeastern Anatolia Region (Region 3) are significantly different for million population and million registered vehicles measures. For instance, Eastern Anatolia Region (Region 6) has the best safety records for FI crash rates per million population, however, it has the worst safety records for FI crash rates per million registered vehicles.

4. CONCLUSION

This paper summarized efforts of and findings from a study to examine regional level FI crash trends and perform comparative analyses of safety records 2006 to 2016. The comparisons were performed in relative terms (ordinal scale or based on rates) and absolute terms (cardinal or rank ordered scale). Two safety measures were used to evaluate safety: million population and million registered vehicles. Data were obtained from publications maintained by TurkStat.

An examination of the results indicated that the relative ranks of the regions were stable over the study period for each safety measure. Non-parametric statistical tests and thematic maps used to support comparative analyses. Specifically, the Kruskal-Wallis nonparametric test was used in this study. The results showed that the FI crash rates are not the same across the regions. Furthermore, the analyses also revealed that depending on the safety measure used, the relative rankings of regions varied (i.e., a region ranked at the top (high crash rate) for one safety measure does not need to be ranked again at the top for other safety measure). This figure is resulted from significantly different vehicle ownership rate across the regions in Turkey. For the cardinal analysis the computed rates were used. These results were consistent with those from the ordinal analysis, but it was showed that FI crash rates significantly increased over the time.

For broad macro level analyses a more representative vehicle-km measure is required to study relative safety records of regions. However, it is available only for national level in Turkey. Furthermore, if specific analyses are required, then safety measures should be defined based on the desired evaluations. For example, if the goal were to address rural safety, the measures should be computed using rural fatal and/or injury crashes, rural vehicle-km, and the extent of rural kilometers of road network. This paper explored methods to analyze regional differences in road traffic safety. The results document the validity and promise of the methods. These methods could be expanded for policy and operational analyses.

REFERENCES

Erdogan, S. (2009). "Explorative spatial analysis of traffic accident statistics and road mortality among the provinces of Turkey". Journal of safety research, Vol. 40, No. 5, 341-351.

OECD/ITF. (2016). Organisation for Economic Cooperation and Development/International Transport Forum. Road Safety Annual Report 2016, Paris. OECD Publishing, 2016.

TGDH, Turkish General Directorate of Highways. (2017). Karayollari Uzerindeki Seyir ve Tasimalar. Turkey. http://www.kgm.gov.tr/SiteCollectionDocuments/KGMdocuments/Istatistikler/SeyirveTasimalar/SeyirVeTasimalar.pdf [Accessed 10 Dec 2017].

Tortum, A. and Atalay, A. (2015). "Spatial analysis of road mortality rates in Turkey." In Proceedings of the Institution of Civil Engineers-Transport, Vol. 168, No. 6, pp. 532-542.

TurkStat, Turkish Statistical Institute. (2018a). Road Traffic Accident Statistics, 2015. http://www.turkstat.gov.tr/PreHaberBultenleri.do?id=21611 [Accessed 10 Dec 2017].

TurkStat, Turkish Statistical Institute. (2018b). Road Traffic Accident Statistics, 2016. http://www.turkstat.gov.tr/PreHaberBultenleri.do?id=24606 [Accessed 10 Dec 2017].

Appendix A: Geographic Regions in Turkey

It is noted that the numbers of the regions are given randomly.

* Marmara Region (Region 1): Balikesir, Bilecik, Bursa, Canakkale, Edirne, Istanbul, Kirklareli, Kocaeli, Sakarya, Tekirdag, Yalova.

* Aegean Region (Region 2): Afyon, Aydin, Denizli, Izmir, Kutahya, Manisa, Mugla, Usak.

* Southeastern Anatolia Region (Region 3): Adiyaman, Batman, Diyarbakir, Gaziantep, Kilis, Mardin, Siirt, Urfa, Sirnak.

* Mediterranean Region (Region 4): Adana, Antalya, Burdur, Hatay, Isparta, Kahramanmaras, Mersin, Osmaniye.

* Central Anatolia Region (Region 5): Aksaray, Ankara, Cankiri, Eskisehir, Karaman, Kayseri, Kirikkale, Kirsehir, Konya, Nevsehir, Nigde, Sivas, Yozgat.

* Eastern Anatolia Region (Region 6): Agri, Ardahan, Bingol, Bitlis, Elazig, Erzincan, Erzurum, Hakkari, Igdir, Kars, Malatya, Mus, Tunceli, Van.

* Black Sea Region (Region 7): Amasya, Artvin, Bartin, Bayburt, Bolu, Corum, Duzce, Giresun, Gumushane, Karabuk, Kastamonu, Ordu, Rize, Samsun, Sinop, Tokat, Trabzon, Zonguldak

Murat Ozen (*1)

Mersin University, Engineering Faculty, Department of Civil Engineering, Mersin, Turkey ORCID ID 0000-0002-1745-7483

ozen.murat@mersin.edu.tr

(*) Corresponding Author

Received: 28/01/2018 Accepted: 10/04/2018

DOI: 10.31127/tuje.385008
Sample1   Test       Std.   Std. Test  Sig.  Adj.Sig.
-Sample2  Statistic  Error  Statistic

R3-R5     -37.000    9.539  -3.879     .000   .002
R3-R2      34.273    9.539   3.593     .000   .007
R6-R5      33.000    9.539   3.459     .001   .011
R3-R4     -32.091    9.539  -3.364     .001   .016
116-R2     30.273    9.539   3.173     .002   .032
R1-R5     -28.909    9.539  -3.030     .002   .051
R6-R4      28.091    9.539   2.945     .003   .068
R1-R2     -26.182    9.539  -2.745     .006   .127
R1-R4     -24.000    9.539  -2.516     .012   .249
R3-117    -19.455    9.539  -2.039     .041   .870
117-R2     14.818    9.539   1.553     .120  1.000
R6-R1       4.091    9.539    .429     .120  1.000
R7-R4      12.636    9.539   1.325     .669  1.000
R4-R2       2.182    9.539    .229     .185  1.000
R7-R5      17.545    9.539   1.839     .066  1.000
R3-R1       8.091    9.539    .848     .396  1.000
R4-R5      -4.909    9.539   -.515     .607  1.000
R6-R7     -15.455    9.539  -1.620     .105  1.000
R2-R5      -2.727    9.539   -.286     .775  1.000
113-116    -4.000    9.539   -.419     .675  1.000
R1-R7     -11.364    9.539  -1.191     .234  1.000

Fig. 4. Kruskal-Wallis multiple pairwise comparisons of FI crash rates
per million population

Sample1   Test       Std.   Std. Test  Sig.  Adj.Sig.
-Sample2  Statistic  Error  Statistic

R1-R3     -41.455    9.539  -4.346     .000   .000
R2-R6     -41.727    9.539  -4.374     .000   .000
R1-R6     -57.727    9.539  -6.051     .000   .000
R4-R6     -34.182    9.539  -3.583     .000   .007
R1-R7     -33.182    9.539  -3.478     .001   .011
R1-R5     -31.727    9.539  -3.326     .001   .019
R5-R6     -26.000    9.539  -2.726     .006   .135
R2-R3     -25.455    9.539  -2.668     .008   .160
R7-R6      24.545    9.539   2.573     .010   .212
R1-R4     -23.545    9.539  -2.468     .014   .285
R7-R3       8.273    9.539    .867     .386  1.000
R5-R3       9.727    9.539   1.020     .308  1.000
R4-R3      17.909    9.539   1.877     .060  1.000
R1-R2     -16.000    9.539  -1.677     .093  1.000
R4-R5      -8.182    9.539   -.858     .391  1.000
R5-R7      -1.455    9.539   -.152     .879  1.000
R2-R4      -7.545    9.539   -.791     .429  1.000
R3-R6     -16.273    9.539  -1.706     .088  1.000
R2-R5     -15.727    9.539  -1.649     .099  1.000
R4-R7      -9.636    9.539  -1.010     .312  1.000
R2-R7     -17.182    9.539  -1.801     .072  1.000

Fig. 8. Kruskal-Wallis multiple pairwise comparisons of FI crash rates
per million population

Appendix B: FI Crash Rates

Table B1. FI crash rates for regions per million population

Region          2006  2007  2008  2009  2010  2011  2012  2013  2014


Marmara (R1)     930  1061  1051  1087  1091  1233  1376  1557  1621
Aegean (R2)     1479  1564  1489  1544  1597  1826  2197  2766  2961
Southeastern     707   717   706   794   834   936  1153  1538  1564
Anatolia (R3)
Mediterranean   1388  1481  1432  1522  1608  1848  2164  2749  2796
(R4)
Central         1565  1678  1558  1720  1803  2000  2371  2675  2621
Anatolia (R5)
Eastern          699   749   726   808   942  1017  1159  1558  1688
Anatolia (R6)
Black Sea (R7)  1065  1181  1093  1207  1304  1433  1608  2192  2304

Region          2015  2016  Average 2006-2016

Marmara (R1)    1707  1718  1312
Aegean (R2)     3183  3150  2160
Southeastern    1718  1524  1108
Anatolia (R3)
Mediterranean   3061  3020  2097
(R4)
Central         2745  2786  2138
Anatolia (R5)
Eastern         1815  1797  1178
Anatolia (R6)
Black Sea (R7)  2529  2702  1692

Table B2. FI crash rates for regions per million registered vehicle

Region          2006   2007   2008  2009  2010   2011   2012   2013

Marmara (R1)     4927   5378  5141  5265   5191   5669   6098   6666
Aegean (R2)      6276   6278  5725  5846   5852   6305   7263   8859
Southeastern     8163   7839  7329  7771   7616   8077   9414  12098
Anatolia (R3)
Mediterranean    6626   6673  6130  6346   6469   6997   7802   9571
(R4)
Central          7636   7826  6986  7502   7551   7943   8989   9754
Anatolia (R5)
Eastern         10189  10294  9449  9871  10621  10811  11614  14783
Anatolia (R6)
Black Sea (R7)   7384   7710  6788  7189   7313   7483   7935  10243

Region          2014   2015   2016   Average 2006-2016

Marmara (R1)     6715   6731   6456   5840
Aegean (R2)      9175   9428   8979   7271
Southeastern    12058  12916  11335   9511
Anatolia (R3)
Mediterranean    9403   9867   9459   7758
(R4)
Central          9214   9202   8963   8324
Anatolia (R5)
Eastern         15399  15784  14859  12152
Anatolia (R6)
Black Sea (R7)  10255  10651  10920   8534
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Author:Ozen, Murat
Publication:Turkish Journal of Engineering (TUJE)
Article Type:Report
Geographic Code:7TURK
Date:Sep 1, 2018
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