The 14th FSTPT International Symposium, Pekanbaru, 11-12 November 2011 MOTORCYCLIST ACCEPTABILITY ON ROAD SAFETY POLICY: MOTORCYCLE EXCLUSIVE LANE IN MAKASSAR Arifin Asri Doctoral Student Graduate School of Civil Eng. Civil Eng. Depart. of UNHAS Jln. Perintis K Km10, Tamalanrea Kampus Universitas Hasanuddin Makassar, Sul-Sel, 90145 Telp: (0411) 587 636
[email protected] Muhammad Isran Ramli Head Lector Transport. System & Eng. Lab. Civil Eng. Depart. of UNHAS Jln. Perintis K Km10, Tamalanrea Kampus Universitas Hasanuddin Makassar, Sul-Sel, 90145 Telp: (0411) 587 636
[email protected] Lawalenna Samang Professor Graduate School of Civil Eng. Civil Eng. Depart. of UNHAS Jln. Perintis K Km10, Tamalanrea Kampus Universitas Hasanuddin Makassar, Sul-Sel, 90145 Telp: (0411) 587 636
[email protected] Abstract This paper attempts to describe motorcyclist acceptability on implementation of motorcycle exclusive lane as a road safety policy in Makassar, Indonesia. The survey was conducted on three main roads as pilot project location of the policy in the city. In order to grasp the motorcyclist acceptability, the multinomial logit model was adopted. In this regard, motorcyclist acceptability became response variables, while motorcyclist perception, socio-demographic condition, and trip characteristics were explanatory variables. The results show that the model was acceptable according to the log-likelihood ratio indicator. Further, motorcyclist’s perception to the policy becomes the more significant variable in context the policy implementation. We expect that the result provides a basis for expansion model in further study in order to grasp motorcyclist perception to traffic safety policies. In addition, the result could become input for policy makers on preparing and implementing for the policy and others transportation safety policies in the future. Key Words: Motorcyclist acceptability, road safety, policy, exclusive lane. INTRODUCTION In the two last decades, motorcycle safety constitutes an increasingly significant in many Asian developing countries. For example, motorcyclists contributed more than 60% of the road injuries on Malaysian roads (Radin et al., 1996). In Thailand, 76% of the injured accident victims are either motorcycle drivers or passengers (Hossain, 2006). Especially in Indonesia, during 2003-2007 there were 70% of road accidents involved with motorcycles in Bali (Wedagama and Dissayake, 2010a; 2010b). Responding those situations, many efforts remain to be made. One of the engineering approaches to overcome the motorcycle accident problem is segregating other road users from motorized traffic through an exclusive motorcycle lane that is restricted to motorcyclists with physical barriers and or markings. The effort has been implementing on Malaysian road (Law and Radin, 2005). In Indonesia, this road safety policy has been tried to be implemented in many big cities in Indonesia, such as, Jakarta, Yogyakarta, Makassar, etc. during January in 2007. However, the implementation was only pilot project in order to introduce the policy to road users. Many reasons why the policy could not be continued to established yet, such as readiness of the road lane construction, perception and acceptability of not only for motorcyclists but also for other road users, etc. The 14 th FSTPT International Symposium, Pekanbaru, 11-12 November 2011 Regarding the acceptability of the motorcyclist on the exclusive motorcycle lane in order to reduce motorcycle accident, this paper attempts to describe motorcyclist acceptability on implementation of the traffic safety policy in Makassar, Indonesia. In this regard, a multinomial logit model approach is used to describe relationship between acceptability motorcyclist as response variable and some predictor variables. This paper begins with a review of previous studies and then presents methodological approach. This is followed by a description of data and model estimation results of the acceptability motorcyclist on the exclusive lane policy. Finally, the paper provides discussion related to the result and concludes. LITERATURE REVIEW Previous research on motorcycle accident in developing countries has primarily focused on the issues of the effectiveness of rider equipment safety, i.e. helmet on reducing head injury severity (Chang, 2005), the investigation of influence factors caused motorcycles accident and injuries (Wedagama and Dissayake, 2010a; 2010b), medical investigation of motorcycles accidents (Hossain and Iamtrakul, 2007), causality cost of motorcyclist’s slight injury (Widyastuti, 2007), and comfortability of excluxive lane for motorcycle (Law and Radin, 2005). Most of those previous studies have used logit model approach in order to describe those issues. For example, Wedagama and Dissayake (2010a; 2010b) developed logistic regression in case of multinomial logit model to describe the influence of accident related factors on road fatalities in Bali, Indonesia. As well as, Chang (2005) used the multinomial logit model to analyze effectiveness of mandated motorcycle helmet in Taiwan. Due to the several similarities on behavioral characteristic of motorcyclist in developing countries, those past studies have provided valuable empirical insights and analysis methodologies for this study. METHODOLOGY Multinomial Logit (MNL) Model Multinomial logit model or logistic regression modelis one of model approaches to represent relationship between response (dependent) variable (Y) that categorical and one or more predictor variables (X) that not only categorical but also continual. When the dependent variable consist of more than two category, i.e. Y = 1 (success) and Y = 0 (otherwise), then multinomial logit model model could be applied. Furthermore, the categories of the dependent variable result in Y follow the Bernoulli distribution. The probability function of the Y with parameter γ is stated as below: ( ) y y y Y P − − = = 1 1 ) ( γ γ (1) Where y = 0, 1 The 14 th FSTPT International Symposium, Pekanbaru, 11-12 November 2011 Then, probabilities of each categories are P(Y=1) = γ and P(Y=0) = 1 – γ with E(y) = γ, for 0≤γ≤1. Generally, probability of the logistic regression that deal with n predictor variables could be formulated as follows (Ramli et al., 2010): ( ) ) ... ( ) ... ( 2 2 1 1 0 2 2 1 1 0 1 n n n n x x x x x x e e x y P β β β β β β β β + + + + − + + + + − + = (2) Where xn is a vector of observed variables that represent relevant attributes to dependent variable, Y. β n is parameter of x n that should be estimated, and β 0 is a specific constant of the model. This study uses the Multinomial Logit (MNL) model to grasp the relationships between acceptability level of motorcyclist as response variable and some identified factors. Variable specification Specification of variables that taking account in this research is shown by Table 1. The table shows that the response variable (motorcyclist acceptability) is categorized into 4 categories, i.e. very accepted, accepted, abstain, and un-accepted. Furthermore, the predictor variables that considered in this study include safety perception, age, education, income, origin place of trip, and destination place of trip. Table 1 Variable and Its Attitude Variable Type Variable Title Attribute/Attitude Variable 1. Motorcyclist acceptability Y 0 = Very Accept; 1 = Accept; 2 = Abstain 3 = Un-accept 2. Safety perception Safperc1 Safperc2 Safperc3 1 = Feel safe; 2 = Otherwise 1 = Abstain; 2= Otherwise 1 = Un-feel safe; 2 = Otherwise 3. Age (years old) X 1. ≤ 12 2. 12 – 15 3. 15 – 18 Ag 4. 18 – 25 5. 25 – 55 6. ≥ 55 4.Education Educ1 Educ2 Educ3 Educ4 Educ5 1 = University; 2 = Otherwise 1 = Senior high school; 2 = Otherwise 1 = Junior high school; 2 = Otherwise 1 = Elementary school; 2 = Otherwise 1 = Training; 2 = Otherwise 5. Income (Rp.1x10 6 X ) 1. ≤ 0.5 2. 0.5 – 1.0 3. 1.0 – 1.5 In 4. 1.5 – 2.0 5. ≥ 2.0 6. Origin place Origplc1 Origplc2 Origplc3 Origplc4 1 = Home; 2 = Otherwise 1 = School; 2 = Otherwise 1 = Office; 2 = Otherwise 1 = Shopping place; 2 = Otherwise 7. Destination place Destplc1 Destplc2 Destplc3 Destplc4 1 = Home; 2 = Otherwise 1 = School; 2 = Otherwise 1 = Office; 2 = Otherwise 1 = Shopping place; 2 = Otherwise The 14 th FSTPT International Symposium, Pekanbaru, 11-12 November 2011 Parameters estimation of the multinomial logit model This study adopted maximum likelihood theory in order to estimate the parameter values of the multinomial logit model. The procedure to estimate maximum likelihood value involves development of a joint probability density function of the observed sample, called the likelihood function, through estimation of parameter values which maximize the likelihood function. The likelihood function in case T observation face j categories results is defined as follows (Koppelman and Bhat, 2006): ( ) ( ) ( ) jt T t j j jt P L δ β β ∏ ∏ ∈ ∀ ∈ ∀ = (5) Where δ jt is chose indicator (=1 if j is happen by observation t and 0, otherwise) and P jt is the probability when the observation t give event j. The solution in order to maximize the log-likelihood function is the second derivation of the function with respect to β. In this study, the parameters values of the model are estimated by using statistical package software, i.e. SPSS Version 16.0. Data Collection This study used data from a survey result that conducted by Indonesian Society of Transportation, Branch of South Sulawesi in January 2007. The survey was carried out in order to measure motorcyclists perception and their acceptability on a pilot project implementation of a road safety policy, namely exclusive lane for motorcycle in Makassar, South Sulawesi, Indonesia. The survey was conducted at three primary roads, i.e. Yani Street, Sudirman Street, and Pettarani Street, where the pilot project of the policy had been socialized by traffic police and local government of the city. The survey took two hours duration in order to survey randomly 500 motorcyclists on each the road. On the survey, the surveyor stopped the motorcyclists who were passing on the exclusive lane for motorcycle, to the road side, then interviewed them about their socio demography, origin-destination trip, and perception and acceptability on the exclusive lane policy. The location of three streets where the survey conducted is shown by Figure 1. Sudirman Street Yani Street Survey Location: Makassar Map Pettarani Street Figure 1 The Location of Road Side Survey The 14 th FSTPT International Symposium, Pekanbaru, 11-12 November 2011 RESULT AND DISCUSSION Data Description The data description related to characteristic of motorcyclist is provided in Figure 2. While acceptability level of motorcyclist related to their characteristics is shown by Figure 3. 8 8 3 3 0 8 8 7 0 0 49 99 6 1 0 236 350 58 28 2 10 25 6 4 0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90%100% University Senior High School Junior High School Elementary School Training Percentage of Each Age Category (%) E d u c a t i o n L e v e l <= 12 12 - 15 15 - 18 18 - 25 25 - 55 >= 55 25 73 24 8 0 66 217 37 18 1 99 123 9 3 1 59 52 3 2 0 53 20 2 1 0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% University Senior High School Junior High School Elementary School Training Percentage of Each Income Level in IDR. x 10^6 (%) E d u c a t i o n L e v e l <= 0.5 0.5 - 1.0 1.0 - 1.5 1.5 - 2.0 >= 2.0 a. Education Level vs. Age Category b. Education Level vs. Income Level 132 55 114 102 52 7 11 13 104 11 86 48 91 2 35 35 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Home School Of f ice Shopping Percentage of Each Origin Trip (%) D e s t i n a t i o n T r i p Home School Of f ice Shopping 146 264 48 24 1 58 110 11 3 0 98 111 16 5 1 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% University Senior High School Junior High School Elementary School Training Percentage of Safety Perception (%) E d u c a t i o n L e v e l Feel saf e Abstain Feel un-saf e Figure 2 Motorcyclist Characteristics on the Study Location c. Destination Trip vs. Origin Trip d. Education Level vs. Safety Perception 14 23 7 3 0 153 284 43 20 1 47 72 6 5 0 88 106 19 4 1 0% 10% 20% 30% 40% 50% 60% 70% 80% 90%100% University Senior High School Junior High School Elementary School Training Percentage of Each Acceptability Level (%) E d u c a t i o n L e v e l Very Accept Accept Abstain Un-accept 0 0 1 1 45 1 0 11 27 82 381 31 1 5 4 22 98 3 1 4 13 50 150 10 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% <= 12 12 - 15 15 - 18 18 - 25 25 - 55 >= 55 Percentage of Each Acceptability Level (%) A g e C a t e g o r y ( Y e a r s ) Very Accept Accept Abstain Un-accept a. Education Level vs. Acceptability b. Age Category vs. Acceptability 7 19 9 7 5 69 183 148 56 45 17 58 30 16 9 37 79 48 37 17 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% <= 0.5 0.5 - 1.0 1.0 - 1.5 1.5 - 2.0 >= 2.0 Percentage of Each Acceptability Level (%) I n c o m e L e v e l ( I D R . x 1 0 ^ 6 ) Very Accept Accept Abstain Un-accept 39 379 31 34 5 70 71 36 3 52 28 148 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Very Accept Accept Abstain Un-accept Percentage of Safety Perception (%) A c c e p t a b i l i t y o f t h e P o l i c y Feel saf e Abstain Feel un-saf e c. Income Level vs. Acceptability d. Safety Perception vs. Acceptability Figure 3 Acceptability of Motorcyclist to Variety of Its Characteristics The 14 th FSTPT International Symposium, Pekanbaru, 11-12 November 2011 Figure 2a shows that the motorcyclist majority in the study location has age 25 – 55 years olds for all each education level. In aside, Figure 2a shows that dominant of the motorcyclist has income IDR 0.5 – 1.0 x 10 6 for all each education level. However, there is also significantly motorcyclist that has income IDR 1.0 – 1.5 x 10 6 on university and senior high school level, and less than or equal IDR 0.5 x 10 6 on the other education levels. Furthermore, Figure 2c shows that amount large of motorcyclist as respondent have home as their origin trip for all destination trip categories. Also, there is significant number of motorcyclist having office as their origin trip. In addition, Figure 2d shows that the majority of motorcyclist feel safe as impact of the exclusive lane policy implementation. However, a significant number of the motorcyclist fells unsafe even the policy has been implemented. Figure 3a shows that majority of motorcyclist of the each education level accepted the implementation of exclusive lane policy. However, there was significant number of the motorcyclist that un-accepted the traffic safety policy. Similarly, majority of motorcyclists in each age and income level categories accepted the policy as shown by Figure 3b and Figure 3c respectively. In addition, Figure 3d shows that the safety perception of motorcyclists on the policy is in line with their acceptability level. Table 2 provides additional information on the mean, standard deviation, skewness, and kurtosis of the explanatory variables. Table 2 Descriptions of Variable Data Variable Type Variable Title Mean Std. Deviation Skewness Kurtosis Percept_Lane Feel_Safe Safperc1 1.461 0.499 0.157 -1.980 Abstain Safperc2 1.797 0.403 -1.478 0.186 Un-feel_Safe Safperc3 1.742 0.438 -1.109 -0.771 Age X Ag 36.433 8.809 -0.693 0.395 Income X In 1.102 0.521 0.826 -0.342 Education University Educ1 1.663 0.473 -0.691 -1.527 Senior_High_School Educ2 1.459 0.499 0.166 -1.977 Junior_High_School Educ3* 1.916 0.277 -3.011 7.084 Elementary_School Educ4* 1.964 0.186 -5.012 23.173 Training Educ5* 1.998 0.047 -21.130 445.491 Origin Home Origplc1 1.550 0.498 -0.202 -1.963 School Origplc2* 1.907 0.290 -2.815 5.937 Office Origplc3 1.722 0.448 -0.993 -1.016 Shopping_Place Origplc4 1.820 0.384 -1.671 0.795 Destination Home Destplc1 1.577 0.494 -0.312 -1.907 School Destplc2* 1.916 0.277 -3.011 7.084 Office Destplc3 1.728 0.445 -1.025 -0.952 Shopping_Place Destplc4 1.779 0.415 -1.347 -0.185 Note: * The variable was removed due to its data do not follow a normal distribution The 14 th FSTPT International Symposium, Pekanbaru, 11-12 November 2011 Model Estimation Result According to normal distribution test of data at significant level 95%, the skewness and kurtosis values should be in the range -2.58 – 2.58 to assess a data group has normal distribution, we removed 5 variables on Table 2 (i.e.: education-3 (Junior high school), education-4 (elementary school), education-5 (training), origin place-2 (school), and destination place-2 (school)) from the model estimation. Calibration and validation of the multinomial logit model in order to estimate and assess the parameters values of the logit model for probability of motorcyclist acceptability were conducted in view of statistics. There were two kinds of statistical test which conducted, i.e. significant test (i.e. p value) in order to evaluate contribution of each variable itself to the model, and goodness of fit statistic test in order to validate the goodness of fit of the model. Table 3 provides the parameters values and statistical indicators of the model. Table 3 Result calculation of parameters values Variables of model Parameter values of each acceptability categories 1. Very accept 2. Accept 3. Abstain B Sig. Exp(B) B Sig. Exp(B) B Sig. Exp(B) Constant 77.14 5E-70 1 0.000 6.77 0.024 1 0.000 3.10 0.375 0.000 Safperc1 -4.07 2E-10 1 0.017 -3.47 0.000 1 0.031 -1.61 8E-07 1 0.199 Safperc2 -1.88 0.014 1 0.153 -1.71 0.000 1 0.181 -2.38 2E-15 1 0.093 Safperc3 0.00 - b - 0.00 - b - 0.00 - b - Age 0.05 0.027 1 1.053 0.01 0.336 1.012 0 0.901 1.002 Income 0.09 0.819 1.089 0.17 0.431 1.186 -0.09 0.748 0.918 Educ1 0.6 0.294 1.825 0.05 0.883 1.056 -0.3 0.521 0.742 Educ2 0.36 0.475 1.436 -0.27 0.426 0.764 -0.32 0.455 0.723 Origplc1 1.84 0.005 1 6.268 0.57 0.131 2 1.777 0.63 0.152 2 1.874 Origplc3 0.63 0.308 1.874 0.79 0.046 1 2.208 0.7 0.125 2 2.011 Origplc4 0.49 0.460 1.635 0.16 0.704 1.177 0.4 0.425 1.494 Destplc1 -15.09 8E-244 1 0.000 0.23 0.546 1.263 0.5 0.260 1.649 Destplc3 -15.37 1E-212 1 0.000 0.04 0.925 1.039 0.34 0.457 1.407 Destplc4 -16.06 0.000 1 1 E-07 -0.41 0.325 0.665 -0.05 0.917 0.951 Number of observation 896 Likelihood ratio, ρ 2 : - Cox and Snell 0.390 - Nagelkerke 0.438 - McFadden 0.224 Hit Ratio (%) 66.7 Note: 1 Significant at 95%, 2 Significant at 80% b The reference category is Un-accept on exclusive lane policy This parameter is set to zero because it is redundant As shown in Table 3, the "very accept" category on motorcycle acceptability model had 8 variables that produced statistically significant parameters (i.e.: constant, safety perception- 1 (feel safe), safety perception-2 (abstain), age, origin place-1 (home), destination place-1 (home), destination place-3 (office), and destination place-4 (shopping place)). The "accept" category on the model had only 5 variables that produced statistically significant The 14 th FSTPT International Symposium, Pekanbaru, 11-12 November 2011 parameters (i.e.: constant, safety perception-1 (feel safe), safety perception-2 (abstain), origin place-1 (home), and origin place-3 (office)); however, the origin place-1 (home) variable has only significant level at 80%. The "abstain" category on the model had only 4 variables that produced statistically significant parameters (i.e.: safety perception-1 (feel safe), safety perception-2 (abstain), origin place-1 (home), and origin place-3 (office)); 2 of these 4 variables (i.e. origin place-1 (home) and origin place-3 (office)) produced only statistically significant level on 80%. Furthermore, Table 3 shows that the motorcyclist acceptability model has enough good overall statistical fit with McFadden pseudo-ρ 2 value in the 0.2-0.4 range (0.2 is minimum value to assess that a model is enough good (Alviansyah et al., 2005; Ramli et al., 2010)). As well as, the Cox and Snell pseudo-ρ 2 value and Nagelkerke pseudo-ρ 2 value in the 0.2- 0.4 range and 0.5-0.7 range respectively. To provide additional insight, Table 3 also shows the hit ratio value, correct percentage between observed data and predicted model, more than 60% that indicated the model enough good to predict the motorcyclist acceptability. Generally, perception of motorcyclist on the road safety policy became the more significant variable in order to accept the policy than other variables such as age and education. It means that a road safety policy have to be more socialized in order to build positive perception on the policy, before the policy is established as permanent road safety policy. CONCLUSION This paper has evaluated motorcyclist acceptability on a road safety policy, i.e. implemented exclusive lane for motorcycle. The safety policy has been implemented as pilot project in some main roads in big cities in Indonesia including Makassar, in South Sulawesi Province. The policy was tried to be adopted by traffic police and government in order to increase motorcyclist safety, irrelevant to decrease the motorcyclist accident. This study used data from a survey result that conducted on three primary roads, i.e. Yani Street, Sudirman Street, and Pettarani Street, where the pilot project had been implemented in the city. The survey investigated socio demography, origin-destination trip, and perception and acceptability of motorcyclists who were passing on the exclusive lane. The study adopted a multinomial logit model approach in order to grasp relationship between response variable, i.e. motorcyclist acceptability, and some predictor variables such as socio demography variable, and motorcyclist perception on the policy. In this regard, there are four categories of motorcyclist acceptability that considered, i.e. very accepted, accepted, abstain, and un-accepted. The calculation result based on the model approach showed that the model was acceptable according to the log-likelihood and hit ratio indicators. Furthermore, perception of motorcyclist on the road safety policy became the more significant variable in order to implementation of the policy. The 14 th FSTPT International Symposium, Pekanbaru, 11-12 November 2011 Finally, we expect that the model provide a basis to develop an expansion model in further study, such as structural model of motorcyclist perception and acceptability on the road safety policies, etc. Also we hope that this study should become input to the policy makers on preparing and implementation not only for the policy but also for others transportation safety policies in the future. ACKNOWLEDGEMENT We would like to express our thanks and appreciation to Mr. Muhammad Idris and his surveyor team in the Survey Institute of Transportation and Environmental (SITE) that supported the survey activities in this research. We also many thanks to Indonesian Transportation Society, South Sulawesi Branch and Traffic Unit of Indonesian Police in Makassar City which allow us to access and utilized the survey data for the purpose of this paper. Without their cooperation, this paper would not be possible to be arranged. 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