# ACCIDENT ANALYSIS ASSESSMENT TO THE ACCIDENT INFLUENCE FACTORS ON TRAFFIC SAFETY IMPROVEMENT (CASE: PALANGKA RAYA _ TANGKILING NATIONAL ROAD

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2 1. EAN (EQUIVALENT ACCIDENT NUMBER) AND AR (ACCIDENT RATE) CALCULATIONS EAN (Equivalent Accident Number) and AR (Accident Rates) are normally considered better measures of risk than accident frequencies alone, since they account for different traffic flow. The standard equation for calculating EAN is: EAN = 1 Death + 3 Seriously Injured + 3 Lightly Injured + 1 Material Losses (1) The values for each accident type are shown in Table 1 below. Table 1. Values for Accident Type Accident Type Value Death 1 Seriously Injured 3 Lightly Injured 3 Material Losses 1 The standard equation for calculating AR is: 8 ( AF.10 )(100MVK) AR = () L. n. ADT.365 Where AR = Accident Rate AF = Accident Frequency ADT = Average Daily Traffic (pcu/hour/ lanes) L = Road Section Length (km) MVK = Accident per million Vehicle Kilometers of travel n = Number of accident years. STATISTICAL TESTING OF EXPERIMENTAL RESULTS To determine the significant differences of the effects of driving license, gender and land-use data, the Root Mean Square test was used. Traffic volume and road geometric were investigated using the regression analysis. The Analysis of Variance was applied to observe the driver s characteristic (age, level of education and profession). Goodness of Fit test was used to investigate the weather and time when the accidents occurred. All the tests were done at a significance level of α = Using the Root Mean Square test, the difference for each measurement must be tested first. Then the t-test can be applied (Chatfield, 1983). d do t = sd / n (3) Where t : Statistic value for t-test do : Difference between two means d : Average difference 09

3 The Null Hypothesis is of the form Ho: µ D = do atau µ 1 = µ atau µ D = µ 1 µ = 0. The degree of freedom is ν = n 1. The t distribution was used to find the critical area where t (ν;α) > t. For the Analysis of Variance test, the Null Hypothesis is H 0 : all variances are equal (µ 1 = µ =... = µ n ), against the Alternative Hypothesis H 1 : the variances are not equal. Then the following equations must be computed (Blank, 198). SS T = k n i i= 1 j= 1 T.. y ij (4) N SS SS Tr = k i= 1 T n i i T.. (5) N E = SST SSTr (6) Where SS T : Total sum of squares SS Tr : Between-treatment sum of squares SS E : Error of sum squares Table. General form of ANOVA table Source variation of Sum squares of Degrees freedom of Mean squares f value Between treatments Error SS Tr SS E k-1 k(n-1) s s i SSTr = k 1 SSE = k( n 1) f = s s i Total SS T nk 1 Where n i j= 1 y T... N T i K n i ij ; : Square of sum of sample j for each treatment i : Square of sum of total sample value : Total number of sample : Square of number of sample for each factor i : Number of location : Sample size for each factor i Then Reject H 0 jika f > F (k-1);(k(n-1) (α) 093

4 The Kolmogorov-Smirnov (K-S) Goodness of Fit test does not use an approximate distribution to test the Null Hypothesis which is the form of H 0 : data is from a specified distribution with stated parameter values (Blank, 198). The test is not reliable if the parameters must be estimated from the sample. The cumulative distribution function (cdf) of the observed sample and the hypothesized distribution must be determined to carry out a K-S test. The test statistic D n is the maximum absolute difference between the two cdf s over all observed values. D n = max F( x) S ( x) (7) n Where F(x) is hypothesized cdf at x and S n (x) is observed cdf at x. 0 x < x1 k S n ( x) = n xk x < xk +1 (8) 1 x xn Critical values for this K-S test are: D 5% 1,36 n is (9) n D 1% 1,63 n is (10) n Where 5% D n 1% D n : Deviation critical value at a significance level of 5% : Deviation critical value at a significance level of 1% n : Number of sample 3. DATA COLLECTION 3.1. Location of the Site Observation This research was conducted in West Kalimantan, more precisely in Palangka Raya Tangkiling national road which is part of southern Trans-Kalimantan. This road has 34 km in length and the width were varies from 6 m to 1 m in width. The design speed of this particular road is 80 km/h. Figure 1. presents the location of site observation while Figure. presents the detailed site observation 094

5 T e l u k K o t a w a r ing i n LAUT J AWA Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 5, pp , 005 Figure 1. Location of site observation 095

6 MARANG STREAT INTAN STREAT MUTIAR A STREAT ROUND ABOUT BUBUT STREAT TANTINA STREAT DANAU TAHAI STREAT BADAK STREAT TENDEAN STREAT BAKAKA STREAT BANDENG STREAT KAHAYAN STREAT SD KATOLIK STREAT BANDES STREAT TANGKUHIS STREAT DANAU RANGGAS STREAT KATINGAN STREAT HIU PUTIH STREAT RAMSES STREAT PARIWISATA STREAT ARUT STREAT MAHIR BADAK STREAT PADAT KARYA STREAT UPUNG STREAT RINJANI STREAT GEREJA STREAT MANDANAI STREAT MASA STREAT SAKAN STREAT BA TAS AKHIR SESEP STREAT PUNAI STREAT KUTILANG STREAT KETERANGAN ANTANG STREAT ROUND ABOUT ROAD TANGKASIANG STREAT SHOULDER ROAD BRIDGE GARUDA STREAT DITCH RIVER + 00 TING ANG STREAT ROAD MEDIAN TRAFFIC CONTROL DEVICES KECUBUNG STREAT Figure. Detailed Site Observation 096

7 3.. Accident Data Accident data from 1997 to 001 and driving license data collections were provided by Police Department. Public Works Department provided IRMS (Integrated Road Management System) and traffic volume. All the data provided in section had been summarized by Bahat (Bahat, 003). Accident location in Palangka Raya Tangkiling National Road is presented in Table 3. Figure 3. presents accident location in Palangka Raya Tangkiling National Road Table 3. Accident location in Palangka Raya Tangkiling National Road. No. Location Number of Accidents (STA) Number Source: Palangka Raya Police Dept. 097

8 6 5 Number of Accidents 4 3 Year 1998 Year 1997 Year 000 Year 001 Year Location (STA) Figure 3. Accident location in Palangka Raya Tangkiling National Road Type of collision is shown in Table 4. Table 4. Type of Collision No Type of Collision Total 1 Head on Collision Back - Head Collision Rear - Head Collision Rear - Rear Collision Lost of Control Collision Drivers involved in the accidents on the black spot were classified based on age, driving license, education, sex and profession. Table 5 shows the driver s classification. Table 5. Driver s Classification No Driver Total I Age years years years years years II Driving License 1 A B C No Driving License

9 No Driver Total III Education 1 Elementary School Junior High School Senior High School University Drop Out IV Sex 1 Male Female V Profession 1 Civil Service, Army and Polic University Student High School Student Driver Private Vehicle type involved in the accidents on the black spot is shown in Table 6. Table 6 Vehicle type involved in the accidents on the black spot No Type of Collision Total 1 Non Motorized Motor Cycle Passenger Car Bus Small-Medium Truck Heavy Vehicle Accident victim condition is shown in Table 7. Table 7. Accident Victim Condition No. Victim condition Total 1 Mortal Injured Seriously Injured Lightly Injured Average daily Traffic is presented in Table 8. Table 8. Average Daily Traffic No Years ADT Number of Accidents

10 Number of accidents on curve and straight line roads is shown in Table 9. Table 9. Number of Accidents on Curve and Straight Lines Roads No. Black Spot (STA) Number of Accidents Curve Lines Straight Lines Number of accidents on the black spot is presented in table 10. Table 10. Number of Accidents on the Black Spot Number of Accident No Black Spot Non Intersection ( STA ) Intersection Horizontal alignment characteristics on black spot are presented in Table 11. Table 11. Horizontal Alignment Characteristics on Black Spot No Location (STA) Angle Radius Design Speed LS Elevation L' (m) km/jam (m) (%) (m) ' ,5 354, ' , 196, ' ,5 80, ' ,1 356,1 Accident number in Urban road and Rural road is presented in Table 1. Table 1. Accident number in Urban road and Rural road Years Accident in Urban Accident in Rural Road Road

11 Accident time in the Black Spot is presented in Table 13. Table 13. Accident Time in the Black Spot. No. Black Spot Time (STA) Accident number during rainy and dry season is shown in Table 14. Table 14. Accident number during rainy and dry season Year Rainy Season Dry Season Driver Characteristics. Interview survey had been conducted to get better overview of driver characteristics. 160 drivers had been interviewed; and the results were tabulated and classified according to their age, level of education, type of driving license, possession of driving license. These are presented into Table 15 to Table 0. Table 15. Driver Age Classification No Type of Vehicle Age (Years) Total 1 Motor Cycle Passenger Car Truck & Bus TOTAL 160 Table 16. Driver Education Classification No Type of Vehicle Elementary Junior Senior School High School High School University Total 1 Motor Cycle Passenger Car Truck & Bus TOTAL

12 Table 17. Driver Profession Classification No Type of Vehicle Civil University High School Total Driver Private Service Student Student 1 Motor Cycle Passenger Car Truck & Bus TOTAL 160 Table 18. Possession of Driving License Classification No Type of Vehicle No Driving Motor Heavy Passenger Total License Cycle Vehicle Car 1 Motor Cycle Passenger Car Truck & Bus TOTAL 160 Table 19. Driver Gender classification No Type of Vehicle Man Woman Total 1 Motor Cycle Passenger Car Truck & Bus TOTAL Table 0. Duration of Driving License Possession No Type of Vehicle Driving License Posession (years) > 1 Total 1 Motor Cycle Passenger Car Truck & Bus TOTAL 160 To better understand the driver behavior on the blackspot, an observation to investigate the traffic law infraction had been carried out and summarized in Table 1. Table 1. Driver Behavior on the Blackspot Road Overtaking Over Stop at The Number of No Type of Vehicle Marking From The Speed Forbidden Drivers Infraction Left Site 1 Motor Cycle Passenger Car Medium Size Vehicle Truck & Bus

15 Blank, L. (198) Statistical Procedures For Engineering, Management and Science, McGraw- Hill Kogakusha Ltd. Chatfield, C. (1983) Statistics for Technology, Chapman and Hall. Ross, A., Baguley, C., Hills, B., McDonald, M. and Silcock, D. (1991) Toward Safer Roads in Developing Countries A Guide for Planners and Engineers, TRRL & ODA. 105

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