ANALYSIS OF MOTORCYCLE ACCIDENTS IN DEVELOPING COUNTRIES: A CASE STUDY OF KHON KAEN, THAILAND. Professor

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1 147 ANALYSIS OF MOTORCYCLE ACCIDENTS IN DEVELOPING COUNTRIES: A CASE STUDY OF KHON KAEN, THAILAND Pawinee IAMTRAKUL Doctoral Student Deapartment of Civil Engineering Saga University 1 Honjo-machi, Saga-shi, , Japan Fax: ts52@edu.cc.saga-u.ac.jp Kazunori HOKAO Professor Department of Civil Engineering Saga University 1 Honjo-machi, Saga-shi, , Japan Fax: hokao@cc.saga-u.ac.jp Yordphol TANABORIBOON Professor School of Civil Engineering Asian Institute of Technology Klongluang, Pathumthani, Thailand Fax: yord@ait.ac.th Abstract: This study employed the unconventional method to analyze the motorcycle accident problems in Khon Kaen, Thailand. By using multidisciplinary approach of medical and engineering professions, motorcycle accident information through the Khon Kaen Hospital s Trauma Registry Records were utilized to identify factors that contribute to high accident rate of motorcycles. On the basis of findings, this study provides a systematic tool for motorcycle accident analysis by incorporating probability of survival model in GIS based accident data management system. It was found that not only the time of accident occurrence could affect the severity of motorcyclists, but the rider characteristics as well as risk factors such as wearing helmet or drunken drivers also induce the severity of motorcycle victims. Severity of victims who did not use safety helmet or drunk while riding would have tendency to face higher severity when accident occurred. Key Words: motorcycle, accident, severity indices, GIS 1. INTRODUCTION It is well known that traffic accidents are of high importance to the public health spectrum in the world. Moreover, in developing countries such as the Kingdom of Thailand, the mortality rates from road traffic accidents are rather high compared to other countries in this region (Murray and Lopez, 1990). Not only the majority of the people killed and seriously injured significantly affect the quality of life of the citizens but it also inhibits the economic and social development of this country. The majority of road accident victims (injuries and fatalities) in Thailand are motorcyclists. Since motorcycles account a large portion of the number of motor vehicles used in Thailand, motorcycles play a dominant role in road traffic accidents. The motorcycles are a major factor regarding road accidents, which can no longer be ignored. An insightful knowledge of the accident data, unsafe vehicle conditions and driver behaviors are essential in investigating the underlying factors related to the occurrence of motorcycle accidents. In order to use motorcycle accident data to establish the prevention measures to efficiently support the decision of policy makers, an effective accident data gathering system is the

2 148 most important pre-requisite in solving the motorcycle accident problems. Since there are many factors responsible for the high motorcycle accident rates, therefore process of accident data collection should cover the important accident information such as road type, environmental features and location, as well as the details of the vehicle/driver and casualty information. Moreover, incomplete motorcycle accident data gathered by responsible agency, added to the increasing of difficulties in analyzing motorcycle accidents. This paper intends to identify factors that affect the severity of injuries related to motorcycle accidents in Khon Kaen Municipality since motorcycle is the most popular mode of travel and most of road injuries in this city were motorcyclists. The injury severity of accidents can be analyzed by using the information that have been gathered and established by the Injury Surveillance Management System (ISMS) specifically designed for accident cases. Due to the completeness of accident data, this study can perform in-depth accident analysis based on multidisciplinary approach, combining medical and engineering knowledge. In addition, the ultimate aim of this study is to provide a harmonized system by establish a GIS based accident database management system in the form of interfaces for the data collection, integration and analysis for motorcycle accidents in the selected study area. As such, the tedious tasks of coding accident location can be alleviated by using existing road locational referencing scheme. In addition, counter measures from different disciplines can be integrated and implemented in order to solve or minimize this problem. 2. BACKGROUND The understanding of the data collection process in Trauma Registry Program, Khon Kaen Regional Hospital, is useful for studying motorcycle accidents in Khon Kaen. The process of data collection is as follows; when an accident occurred, nurses and/or other assigned personnel record the patient s information on paper forms manually. Then the locations of accident occurring would be identified on the map and related information were recorded on an additional paper form. Finally, all the data were recorded into a computer file with the completed patient s information. The recording form is shown in Figure 1 and this form is widely known as Injury Surveillance (IS) Form. The IS Form contains all the information regarding the patient. Furthermore, an additional form so called Accident Form was developed specifically for Khon Kaen Hospital and this form (Figure 2) is filled up when the accident occurred in Khon Kaen (Ruengsorn et al., 2001). When an accident occurred, there could be more than one patient involved at the same location. The system developed through Accident ID could enable all involved victims to have the same Accident ID on the accident data form instead of each patient had his/her own Accident ID. This would provide a more accurate data of accident victims and the number of accident cases. The information required in this form included both location and environmental information. 3. STUDY AREA Motorcycles are much more affordable vehicles compared to other motor vehicles, due to this reason, the number of motorcycles have increased at a rapid rate especially in the provincial region. Consequently, it can be expected that the severity rate of accidents involving motorcycles tend to increase as well as the fatality rate resulting from these accidents. Khon Kaen province was selected as a study area for a pilot project in developing a GIS based accident data management system which aims to set up a prototype for other hospitals to

3 149 follow. This study concentrated mainly on the municipal area due to the available and sufficient data collected from the Trauma Management System. Khon Kaen municipality covers an area of 55 km 2 (Figure 3), with a population of 376,148 (year 2000). Figure 1. Injury Surveillance Report Form Source: Critical Care and Trauma Center, Khon Kaen Regional Hospital, 2000 Figure 2. Traffic Accident Report Form Source: Critical Care and Trauma Center, Khon Kaen Regional Hospital, 2000

4 150 Khon Kaen Municipality Figure 3. Sturdy Area (Khon Kaen Municipality) 4. METHODOLOGY In order to have a precise analysis of the motorcycle accidents in Khon Kaen, an effective accident data system has to be established. Since the present accident data collection process does not provide complete information regarding motorcycle accidents and does not make the data readily available, the development of a better system should not make use of manual and repeated processes as it is in the present system. The retrieval of data and specific information for such motorcycle accidents can be simplified by using a database management system with user-friendly interfaces. Before proceeding to develop accident database management system, accident database design is essential to clearly define the process of deciding how to organize data into the classified types of specified records and how these records can be related to each other (Date, 2000). This study employed this concept to develop a database management system to mirror the process of Trauma Registry s data collection. As mentioned earlier, this study developed a

5 151 database management system to be used in the data collection and analysis process, incorporating the concept of probability of survival (PS) in determining the severity indices (Tanaboriboon et al., 1999). Medical professionals generally use Probability of Survival in determining the severity indices. The PS model was incorporated into the database to also determine the risk factors for accident analysis. Furthermore, the structure of this system was well designed and suited to manipulate transactions efficiently. The structure of this system was based on the application and number of inquiries that would be made. The conceptual framework was organized in order to design an appropriate system to facilitate the process of motorcycle accident analysis. The detailed conceptual framework for this system is demonstrated in Figure 4 which proposes the integration of accident database management system and probability of survival concept. There are three modules involved in this system namely; database module, accident analysis module and output module. The database module contains accident data from Trauma Registry data files. Accident analysis module focuses on probability of survival and severity indices. Finally, the output module consists of graphical interfaces and geographical referencing scheme. Patient Information Accident Information Medical Information Database Module Medical Approach Accident Location Revised Trauma Score (RTS) GCS, SBP, RR Injury Severity Score (ISS) AIS Digital Map Probability of Survival Model (PS) Accident Analysis Module Severity Index (SI) Casualty Severity (CS) Development of GIS Based Accident database Management System Output Module Data Editing and Updating Figure 4. Framework for Suggested Accident Database Management System

6 Accident Analysis Module As mentioned earlier, this study adopted the widely used techniques, the TRISS Methodology (Champion et al., 1991) to evaluate probability of survival (PS) of accident patients of the Khon Kaen Hospital. The PS model can be determined by a logistic model as shown in equations (1) and (2). 1 PSi = Z i (1) 1+ e ( ) Z i = b 0 +b 1 (RTS i )+b 2 (ISS i )+b 3 (AGE i ) (2) where PS i = Probability of survival of patient i th RTS i = Revised Trauma Score of patient i th ISS i = Injury Severity Score of patient i th AGE i = 1 if patient age > 54 years, 0 if patient age < 54 year The TRISS weights were determined into two types of injuries (blunt and penetrating) as follows: Z i = RTS i ISS i AGE i ; for blunt injuries (3) Z i = RTS i ISS i AGE i ; for penetrate injuries (4) There are three main components of equation (2), which are RTS, ISS and AGE. There are two variables that are involved, RTS and ISS. RTS is a function of the Glasgow Coma Scale (GCS), systolic blood pressure (SBP) and respiratory rate (RR). The Glasgow Coma Scale (GCS) is the summation of scores of three behavior responses: eye opening, verbal response and motor response. ISS is the summary score for multiple traumatic injuries that consist of the three highest Abbreviated Injury Scale (AIS) scores for injuries to different body regions (head/neck, face, thorax, abdomen and pelvic contents, extremities, and external). After obtaining RTS and ISS values, TRISS methodology was applied to estimate the survival probability of the patient for this study. Subsequently, severity index could be determined as a reduction of probability of survival. This study developed severity indices to access the risk behavior and motorcycle accidents in Khon Kaen (Tanaboriboon et al., 1999). Prior to the determination of the severity index (SI), casualty severity (CS) has to be identified based on the probability of survival of involved victims. CS is defined as reduction of probability of survival. This study assumed that the probability of survival of any victim prior to the accident is equal to 1.0. Therefore, the CS can be described as follows: CS k = i i PS i i= 1 ( 1 ) (5) where CS i = Casualty Severity for i victims involved in accidents PS i = Probability of Survival of patient i th involved in accidents = Total number of victims involved in accidents k i Using this defined CS model, the severity index, SI can be determined to measure the severity of patients when accident occurred from the following relationship: SI = i CS k i i (6)

7 153 where SI i = Severity Index for k victims involved in accidents CS i = Casualty Severity for i victims involved in accidents = Total number of victims involved in accidents k i 4.2 Output Module A Geographic Information System (GIS) is suited to motorcycle accident analysis because it provides georeferenced databases, which are road system and motorcycle accident information. The use of digital map that displays the entire study area for locating any accident occurrence can reduce the error resulting from manual data collection. The distribution of motorcycle accidents in the study area can be depicted immediately as well, for an understanding of the problem leading to efficient solutions. The geographic feature data for this study was modified from Ruengsorn s study (Ruengsorn et al., 2001) that displays road system (road section and intersection), buildings and related information on map. This digital map was incorporated with accident data particularly on motorcycle accident data to develop GIS based accident data management system in Khon Kaen. 5. GIS Based Accident Data Management Interfaces Accident database management system is a collection of electronic accident filing system that enables users to enter, organize, and select specific data in accident database. When this system is used, accident information system can be changed much more easily as the users' information requirements change. New categories of accident data can be added to the database without disrupting the existing system. With graphical user interfaces, users can select desired data to manipulate by moving the pointer to the object or by clicking the mouse button. Consequently, a collection of accident data can be organized in such a way that users can select summarized motorcycle data. Furthermore, as mentioned earlier, the GIS concept was incorporated in the development of this database to alleviate tedious tasks of coding accident location by using existing road location referencing scheme. This system provided the interconnection between both system that were database and GIS to allow users to retrieve accident information on text, graphical as well as geographical data. Accident Data Manipulation From the current process of accident data collection employed by Khon Kaen Hospital, it seems to be a tedious complex task of entering accident data on the paper forms. By using the interfaces, all processes are implemented on clicking process. It takes shorter time and can be completed on one process. Errors as well are reduced from manual data collection. Not only this system can be employed to manage accident data but it also provides useful information for further analysis. Users can also click on the provided buttons to enter to the specific tasks that are available on the given form (displaying, searching, adding and summary of accident data). These works can be executed by providing the interfaces as depicted in Figure 5.

8 154 Search for accident data Summary of accident data Accident Analysis Figure 5. Accident Data Manipulation In order to achieve the desired objectives, this study employed the TRISS methodology to estimate the probability of survival of accident victims along with the determination of the severity index. The complexity of calculation can be decreased due to the automatic computation done by the system. Moreover, the severity of each group of victims can be compared straightforward. However, there are some unusual cases that the value of prediction contradicts the actual status of victims. The system will notify the concerned parties such as the doctors or the nurses regarding these unusual findings by displaying Incorrect. In order to meet such purpose that are mentioned earlier, this study provided the interfaces to deal with the complicated analysis by using multi-disciplinary approach of both engineering and medical experts to co-develop the database system. The procedure of utilizing this system is described in Figure 6. GIS Based Accident Data To facilitate the process of identifying accident locations, this study provided the interconnection that users can display, query, summarize, and organize accident data geographically as well as to locate accident sites by using interfaces. The process of interconnecting to the GIS could be executed by clicking at the GIS button that is provided in interfaces. A digital map would be displayed, reducing the errors from manual data input as well as the distribution of accidents in the study area can be depicted immediately for an understanding of the problem leading to useful solutions (Figure 7).

9 155 Determine Probability of survival Predict the status of victims Identify abnormal case Calculate Severity Index Figure 6. Process of Accident Analysis Figure 7. Graphical Representation the Location of Accident by Using GIS

10 ANALYSIS OF RESULTS It is essential to present the theoretical background of the analysis and the results of the findings on motorcycle accidents in Khon Kaen before presenting the development of the accident database management system. To verify the need to investigate the motorcycle accidents in Khon Kaen, this study used the Khon Kaen Hospital s Trauma Registry data collected between May 2000 and June 2001 to investigate all types of vehicles involved in traffic accidents. It was known that most of the traffic accidents occurred in Khon Kaen involved motorcycles which represented more than 90% of all accidents as presented in Table 1. Thus, it is very evident that motorcycle accidents cannot be overlooked and needs to be investigated further. Table 1. Classifications of Vehicles Involved in Road Accidents in Khon Kaen Municipal Area (May 2000-June 2001) 6.1 Probability of Survival Model Type of Vehicles Number of Accidents Percent Bicycle or Tricycle Motorcycle 2, Tuk Tuk Passenger Car Pick Up Truck Minibus Bus Total 2, TRISS equations have been widely used throughout the world including Thailand to determine the probability of survival of victims. Up to date in Thailand, the Thai medical personnel still employ and use these equations. No attempts have yet been made to deviate the national formula in determining the probability of survival. Nonetheless, this study attempted to derive the PS model by using Khon Kaen Hospital data. The existing 14 months accident data were separated into two sets, eight months data in the year 2000 (May December 2000) and six months data in the year 2001 (January June 2001). The first set of the data was used to calibrate the PS model and the remaining data was used for validation. In addition, Champion Model was also used to compare the results of findings. Although the TRISS Methodology developed two types of victims injuries, this study could only develop the blunt injuries equation for Khon Kaen Hospital. This is due mainly to the fact that there were very few penetrating injuries in patients during the study period. Eventually, the developed PS model for Khon Kaen is: 1 PSi = ( RTS (7) i ISS ) 1+ e i According to equation (7), there is relatively strong relationship between PS value and medical variables (RTS and ISS) since R 2 are by using the mentioned 6 months data period to validate. This study defined the survival status of each patient as the value of probability of survival was greater than or equal to 0.5, otherwise the victims were classified as dead. Results of the validations clearly indicated the developed model yielded satisfactory result as compared to the actual condition and that of Champion s model as shown in Table 2.

11 157 Table 2. Model Validation Results Results No. of Fatalities No. of Injuries Total Patients Khon Kaen s Actual Status Champion s Considering the fact that this model can be used to predict the probability of survival, this study decided to utilize all 14 months data to re-calibrate and re-develop the model. Results of the new proposed PS model based on the entire 14 months data can be shown as follows: 1 PS (8) i = ( RTSi ISS ) 1+ e i Furthermore, this study also re-validated the developed model and compared the results with the actual conditions and that of Champion s. Table 3 presents the results of the validation which clearly indicated that the developed model could produce satisfactory results. Furthermore, value of R 2 is found to be which is considered to be highly correlated. Therefore, this developed model as presented in equation (8) is further used to analyze the accident victims in Khon Kaen and is corporate into the database system as described in the next section. Table 3. Model Validation Results Results No. of Fatalities No. of Injuries Total Patients Khon Kaen s 21 2,314 2,335 Actual Status 22 2,313 2,335 Champion s 17 2,318 2, Analysis of Motorcycle Accidents in Khon Kaen According to the analysis based on the severity approach, this study investigated the factors that contributed to the motorcycle accidents in Khon Kaen Municipality by each category. They are as follows: Trends of Accident There are several factors that induced the severity of injuries borne by the motorcyclists, one of these is time variation. There are two sub categories of time trends: time and monthly accident occurrence, respectively. The effects of both categories are further elaborated as follows: Time of Occurrence The average 24-hour motorcycle accident occurrences during the study periods together with their associated SI values are presented in Figure 8. The high frequencies of accident occurrences mostly fell at night periods except during the two peak periods of 8:00-9:00 hr. and 17:00-18:00 hr. For further investigation, this study combined all accidents that occurred between 6:00-18:00 hr. as a DAY time and the remaining periods as a NIGHT time. Results of the comparison between these two periods (day vs. night) are shown in Table 4. It is clearly revealed that not only the accidents occurred frequently during night time but the motorcyclists were also facing much more severe accidents. The severity was nearly 3 times higher than that of the day time.

12 158 Number of Victims :00 7:00 8:00 9:00 10:00 11:00 12:00 Day time 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 Night time Series2 Number of Victims Figure 8. Motorcycle Accident Occurrences by Time Table 4. Day and Night Time Accidents in Khon Kaen 0:00 1:00 2:00 3:00 4:00 SI in 1,000 Victims 5: Series3 SI in 1,000 Victims Time of Accidents Number of Victims Percent SI in 1,000 Victims Day Night 924 1, Total 2, Monthly Distribution of Accident Occurrences In light of the seasonal effect on the motorcycle accident occurrences in Khon Kaen as presented in Figure 9, it can be seen that variations of accident occurrences indicated an inconsistent trend. While it could be expected that the number of accidents should have been high, if not the highest, in April, as this month was the Songkran Festival (Thai New Year days), it could be noted that there were only 78 accident patients found in April. Its severity index was rather low as compared to the others (July, August, September, October, November, December and January). Considering that there are three seasons in Thailand which are summer (March-May), rainy (June-October) and winter (November-February), it is expected that the occurrence of accidents and its severity should be very high during the rainy season (the highest as compared with other seasons) as the road surfaces are wet and become slippery especially for motorcyclists. Number of Victims SI in 1,000 Victims May June July August September October November December January February March April Series2 No. of Victims May June Series3 SI in 1,000 Victims Figure 9. Monthly Distributions of Accident Occurrences However, as shown in Table 5, the results revealed that severity cases during the rainy seasons are nearly the same with the winter season. Thus, it can be concluded that wet

13 159 conditions have no effect on motorcycle accidents in Khon Kaen. This may be due to the fact that when it rains, most of motorcyclists stop and park their motorbikes waiting for the rain to stop before proceeding to their destinations. Obviously, they may be aware that the roads are wet and they become more conscious and careful in riding. Table 5. Seasonal Variation of Accident Occurrences Season Summer (March-May) Rainy (June-October) Winter (November-February) SI in 1,000 Victims Characteristic of Motorcycle Victims Generally, several conventional methods have been widely used to assess the severity rate or severity index of traffic accident. This study intends to propose the unconventional method by utilizing medical data for motorcycle accident analysis. This method is multidisciplinary approach that makes use of hospital s data by concentrate on motorcycle patients who admitted to Khon Kaen Regional Hospital. Therefore, motorcycle victims that mentioned in this study refer to motorcycle patients for both motorcycles drivers and passengers. Although various characteristics of motorcycle victims that contributed to traffic accidents, this study only considered two characteristics of gender and ages due to the availability of data. Gender Table 6 represents the gender of victims involved in motorcycle accidents and their associated SI values in Khon Kaen. The findings as illustrated in this Table clearly indicated that male motorcycle victims were generally found to be more reckless in driving the motorcycles as their accident occurrences are about twice as much of their female counterparts. Furthermore, when facing accidents, males were also found to be nearly twice as much as of the females in terms of the severity of injuries. Thus, it can be concluded that male motorcyclists were more dangerous in driving than females in Khon Kaen. Age Table 6. Distribution of Victims Involved Motorcycles Accident by Gender Gender of Victims Number of Victims Percent SI in 1,000 Victims Male Female 1, Total 2, Considering the age groups of motorcycle victims involved in accidents in Khon Kaen, this study classified all motorcycle victims into six age groups as shown in Figure 10. Majority of Khon Kaen motorcycle victims were young riders consisting of about 57% of the total victims. However, in spite of the fact that these young riders with ages ranging from had the tendency to face accidents more often than other age group of riders, their injury severity s were not the worst. The most reckless rider group found in Khon Kaen was the adult group with ages ranging from years old as their SI values were the highest among all victims. This is due to the fact that these victims may be drunk while driving and that is the reason why their severity rates are the highest. Furthermore, there were some victims that were classified as illegal drivers since they were younger than 15 years old. In Thailand, the legal age to ride motorcycles is 15 years old and

14 160 above. Therefore, this group of victims need heightened and more efficient law enforcement to curb their driving since their severity was reasonably high as compared with other age groups. Number of Victims 1500 SI in 1,000 Victims > 60 Age of Victims (Years) Series2 No. of Victims Series3 SI in 1,000 Victims Figure 10. Distribution of Victims Involved Motorcycles Accident by Ages Risk Behavior Regarding the risk factors involved with motorcycle victims, it was known that there were two major risk factors that affect the severities of motorcycle accidents. These factors are described as follows: Influence of Alcohol This study investigated the severity of victims who were under influence of alcohol as illustrated in Table 7. Table 7. Distribution of Victims Involved Motorcycles Accident by Alcohol Use Group Number of Victims Percent SI in 1,000 Victims Normal Drunk 1, Total 2,138* *Note: There were 57 unknown cases As can be seen from Table 7 that about one third of motorcycle victims involved in accidents were drunk drivers. Furthermore, considering their severity rates, the severity of drunk victims were about 5 times higher than the normal victims (10.1 vs 2.1) as presented in Table 7. Thus, it can be concluded that drunk-driving is a serious problem in Khon Kaen which require an immediate measure. Use of Safety Helmet Motorcyclists are advised to use their helmet while driving. The number of victims involved in accidents that used and did not use helmet were presented in Table 8. Results indicated that about 77 % of motorcyclists involved in accidents in Khon Kaen did not use helmet. Furthermore, it was clearly seen that motorcycle victims without helmet could face almost about 7 times higher of accident severity comparing with those using helmet when accidents occurred. The ignorance of using helmet was dependent upon the enforcement of the law. Table 8. Distribution of Victims Involved Motorcycles Accident by Safety Helmet Group Number of Victims Percent SI in 1,000 Victims Without Helmet With Helmet 1, Total 2,157*

15 161 *Note: There were 38 unknown cases To support the findings on the helmet used by motorcyclists, this study also conducted the field surveys on two locations in Khon Kaen. One location was located at the out skirt of city limit and another was within the central city. Data were collected on weekday and weekend on those motorcyclists who used and did not use helmet. Figure 11 presents the situation of helmet used on both locations in Khon Kaen. Percent of Helmet Used Weekday Weekend Weekday Weekend Outskirt Area City Area Series1 Day Series2 Night Figure 11. Percentages of Helmet Used in Khon Kaen It was known that during daytime while policemen were still on duty, motorcyclists followed the regulation by wearing helmet especially in the city area. However, they disregarded this regulation at night which was due mainly to the fact that there were no policemen around. This serious problem should be given much attention by concerned authorities. Motorcyclists should be well aware on the significance of helmet and are informed on the safety regulation. 7. CONCLUSION This study presented the results of the investigation of the factors that contributed to motorcycle accident occurrences in Khon Kaen municipality through the development of GIS based accident database management system. This provided the systematic process of data collection, integration and analysis by using the Trauma Registry data of the Khon Kaen Regional Hospital. Furthermore, the new technique, the multidisciplinary approach of both engineering and medical experts was used to co-develop the road accident database system. The medical approach was employed to investigate the severity of victims by using TRISS methodology. Under the TRISS concept, the probability of survival (PS) of any accident patients must be determined. This study attempted to derive PS model by using the available data that has been collected between May 2000 and June Subsequently, the severity indices were then developed to access the risk behavior and motorcycle accidents in Khon Kaen were investigated. Several factors associated with injury and fatality motorcycle accident in Khon Kaen were investigated. In addition, this study utilized GIS to provide visual distribution of motorcycle accidents according to factors related to injuries. It was known that male motorcyclists were generally found to be more reckless in driving the motorcycles as their accident occurrences were about twice as much as their female counterparts. Furthermore, when facing accidents, males were also found to be nearly twice as much as of females in terms of the severity of injuries. Thus, it could be stated that male motorcyclists were more dangerous in driving than females in Khon Kaen. About one third of motorcycle victims involved in accidents were drunk driver. Furthermore, considering their severity rates, results also revealed that the accident severity of drunken drivers was about 5 times higher than normal drivers. Most of motorcycle victims involved in accidents in Khon

16 162 Kaen did not use helmet. Unfortunately, they did not realize how dangerous and how serious this ignorance is. Results of the analysis clearly indicated that motorcycle victims without helmet could face about 6 times of accident severity comparing with those using helmet when accident occurred. Therefore, a number of safety improvements should be implemented in order to reduce the frequency and the severity of motorcycle accident especially for motorcyclists who are more prone to involve in high severity rate. As well as the policy actions such as enforcement of helmet use and prohibiting impaired driving are required to ensure safety improvement measure. Additionally, GIS database management system that developed in this study is readily available to visually ascertain the proximity of locations that occupy more frequency and more severity of motorcycle accidents. For more effectively, the strict regulation should be more vigorous enforcement according to the recommended potential problem sites and the enhancement of graduated licensing for young driver should be also emphasized for safety plan. ACKNOWLEDGEMENTS The authors would like to express their sincere appreciation to Khon Kaen Regional Hospital (KKH) for providing support for the comprehensive study. The authors also gratefully acknowledge Dr. Danai Ruengsorn for the Geographic Information System (GIS) data as well as the digital map of Khon Kaen municipal area. REFERENCES Champion, H.R., Sacco, W. J., and Copes, W. S., (1991) Trauma Scoring, Trauma 2 nd Edition Date, C. J. (2000) An Introduction to Database Systems. Addison Wesley, Massachusetts. Murray, C., J. L. and Lopez, A. (1990) The Global Burden of Disease. A comprehensive assessment of mortality and disability from diseases, injuries, and risk factors in 1990 and projected to 2020, The World Bank, Washington DC. Ruengsorn, D., Tanaboriboon, Y. and Chadbunchachai, W., (2001) Development of GIS Based Traffic Accident Database Through Trauma Management System: The Developing Countries Experiences, A Case Study of Khon Kaen, Thailand, Journal of Eastern Asia Society for Transportation Studies, Vol. 4, No. 5, Tanaboriboon, Y., Ruengrorn, D., Chadbunchachai, W., and Suriyawongpaisal, P. (1999) Analysis of Traffic Accidents through Hospital s Trauma Registry Records: Case Study of Khon Kaen, Thailand. Journal of International Association of Traffic and Safety Sciences, IATSS Research, Vol. 23, No.1,