ROAD ACCIDENTS IN SAUDI ARABIA: A COMPARATIVE AND ANALYTICAL STUDY. Ali. S. Al-Ghamdi 1

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1 1 ROAD ACCIDENTS IN SAUDI ARABIA: A COMPARATIVE AND ANALYTICAL STUDY Ali. S. Al-Ghamdi 1 ABSTRACT: The main goal of this study is to discusses the magnitude of traffic accidents in the Kingdom of Saudi Arabia (KSA) over the last fifteen years and to compare the situation of traffic safety with that of other countries. This developing country has experienced a rapid economic growth resulting in an enormous increase in the motorization rate (vehicle per 1 population) associated with rapidly expanding road construction. As a result, traffic accidents have become a serious problem facing the country. During the period from 1971 to 1994, the numbers of traffic accidents, injuries, and fatalities have increased by 3 times, 6 times, and 7 times, respectively. This study showed that both fatality rate and accident severity have increased and the need for improvement is urgently needed. INTRODUCTION The Kingdom of Saudi Arabia (KSA) has experienced a rapid economic growth since the oil boom in 1973 resulting in an enormous increase in the motorization rate (vehicle per 1 population) associated with rapidly expanding road construction. The number of registered vehicles has increased from 144,768 in 197 to 5,861,614 in 1994, a forty-fold increase in 24 years [General Traffic Directorate ( )]. This growth in motorization has accompanied with a drastic increase in the size of the road network in the country. The length of paved roads has increased dramatically from 85 km in 197 to 43,3 km in 1992, a nearly five-fold increase in 22 years [Ministry of Communications, 1994]. As a result of this remarkable growth in motorization and the road-network size, traffic accidents have become a serious problem facing this developing country. During the period from 1971 to 1994, the numbers of traffic accidents, injuries, and fatalities have increased by 3 times, 6 times, and 7 times, respectively (see Table 1 and Fig.1). Fig.2 depicts that during the period while fatality rates (per person) increased by 157%, the fatality rates (per vehicle) decreased by 82%. This figure also shows that there were tendencies for fatality and injury rates per vehicle to decrease and per person to increase over time. Such trends agree with what Smeed [1949 and 1968] found as will be discussed shortly. Bener and Jadaan (1992) found that road traffic fatalities is at the top of the list of major causes of death. Statistics in USA [National Safety Council, 1994] ranked road traffic fatalities as the third most common cause of death in all age group. The size of the problem can be shown by comparing accident severity and cost in KSA with those in USA, as presented in Table 2. The table reveals that the percentage of injury accidents in KSA is almost double that in USA. The percentage of fatal accidents in KSA is 2.6% and the corresponding percentage for USA is.313. This is more than eight times. The cost of a traffic accident in KSA is 1.7 times greater than that in USA. These percentages and numbers show that the loss of life and the accompanied economic loss to the country are large when compared with 1 Ass. Prof., Dept. of Civi. Eng., King Saud Univ., Riyadh, Saudi Arabia.

2 2 USA. Statistics have also shown that more than about eighty percent of all reported accidents occurred in KSA during the last five years ( ) were attributed to the driver. Therefore, it is of primary importance to study driver-related factors (human factors) than may contribute to the problem. The objective of this study is twofold: 1) to discuss the magnitude of traffic accidents in this developing country over the last fifteen years and to compare the situation of traffic safety with that of other countries and 2) to analyze road accidents with more emphasis on human factors. The firs objective will be achieved by examining changes in accident rates over the past two decades and comparing these rates with those in some developing (e.g., Egypt, Kuwait, Bahrain, and Mexico) and developed countries (e.g., USA, UK, Sweden, Germany, and Canada) by using Smeed s formula. The second objective will be attained by analyzing data obtained from police records using statistical techniques such as odds ratio and proportion comparisons DATA SOURCES AND LIMITATIONS In order to quantify the magnitude of the traffic-accident problem, accident data should be available and reliable. In many countries, especially in the developed world, data may come from different sources, including police, insurance, and hospital records. The situation, however, is different in developing countries, where the only sort of data is the police [Asogwa (1982), Jacobs and Sayer (1983), Gharaybeh (1994)]. In these countries, the police accident data are not collected with a view to providing research information but for the purposes of litigations [Asogwa (1982), Jacobs and Sayer (1983)]. Therefore, such data do not have detailed information to carry out in-depth research. Similar to other developing countries, the main source of road accident data in KSA is the police. The Publication of Road Accident Statistics which is yearly published by the General Directorate of Traffic, Ministry of Interior ( ), contains all reported accidents with information related to the driver (e.g., age, education, and marital status) and the accident (type, cause, time, and severity). Such data reveal three main problems with police records [Al-Ghamdi (1993), (1994), (1995)]: (1) Until 1991, accident data were restricted to the fatal and injury accidents (i.e., no consideration for property-damage-only (PDO) accidents), (2) deficiency in reporting system exists due to incomplete, unclear, and/or incorrect data, and (3) Filling system is primitive (i.e., reports are filled manually and no computerization is made to maintain data). Besides, the reliability of police reports is questionable because policemen are not trained as engineers and look for prosecution data rather than engineering problems [Ergun (1987), Al-Ghamdi (1994)]. Thus, researchers face difficulties in collecting accident data due to manual searching in the files and other problems just mentioned. In this study, great efforts were made to obtain data from police records and to extract other nations data from literature. The definition of developed and developing contries is not given herein. World Bank relates this definition to gross national product (GNP) per capita [see World Tables].

3 3 ACCIDENT RATES COMPARED Three known measures can be used for accident comparisons when related to motorization rate (vehicles per 1 persons (V/P)): 1) fatalities per 1, persons (F/P), 2) fatalities per 1 vehicles (F/V), and 3) fatalities per 1 million vehicle kilometers (F/VK). The last one (F/VK) is the best measure for making reliable comparisons among nations since it takes the total amount of travel into consideration. However, this measure is not available for KSA. Therefore, the other two measures (F/P and F/V) are used herein for comparison purposes. Fig. 3 (based on very recent data) shows that road accident fatality rates (i.e., deaths per 1, vehicles) are high in developing countries very often more than 5 times greater than for those countries of Western Europe and North America (Jacob and Sayer (1983) reported 2 times based on 197s data). Among 4 nations, KSA ranks the 25th as depicted in Fig. 3. About 8 persons per 1, vehicles are killed in traffic accidents in KSA. Taking into account motorization level, the interpretation of this rate is different as discussed below. The work of Smeed (1949, 1968) on data from developed countries have shown that there were tendencies for fatality rates per vehicle to decrease and per person to increase over time. Fig. 2 suggests that the same findings of Smeed apply to KSA as well. It is obvious from the figure that when accidents, injuries, and fatalities are related to population, the rate increases with time, meanwhile when these items are related to registered vehicles, the rate decreases. Smeed represented the trend for fatality rate per vehicle in the following form: (1) F V V = α P β F, the death rate per registered vehicle, It follows from the above formula that V V, the proportion of vehicles in population (motorization), increases. Smeed decreases as P applied this formula on data from 2 developed countries and found that the death rate is varying approximately inversely as the two-thirds power of the proportion of vehicles to are.3 and 2/3, respectively. β and αthe population. In other words, he found that Applying Smeed s formula on data from 35 developing countries, Jacobs and Cutting are.39 and.64, respectively. In addition Jacobs and β and α(1986) found that Cutting (198) repeated the earlier work of Smeed on data from developed countries and are.21 and.72, respectively, indicating that the fatality rates β and αfound that based on registered vehicles in these countries have decreased between 1938 and 198.

4 4 In this study, Smeed formula was used on KSA data for the period from 1971 to. The linear β and α1994 (Table 1). Regression technique is employed to estimate transformation of eq. (1) was first obtained by taking its logarithm: V α P β = log F V log and hence F V log = logα β log V P The linear transformation was then regressed to give the following model: ) R 2 92% ( F V log = log V P for the case of KSA were β and αby taking the antilog of the above mode, the values of found to be.3 and.795, respectively. Thus, the modified Smeed s formula for the case of KSA becomes: (2) F V V =. 3 P 795. The fitted values obtained from this model along with actual fatality rates are plotted against motorization level in Fig. 4. The model shows reasonable fit. When plotted over time ( ), actual and modeled data show a downward trend indicating that an overall improvement in safety levels have achieved over years (Fig. 5). Yet, it is obvious from this figure that the last five years ( ) have depicted a slow raising trend in fatality rates implying that safety levels show no improvement lately. This increasing trend was also detected using time series modeling in earlier studies conducted by the author [Al-Ghamdi (1993) and (1994)]. When actual rates plotted with fitted curves of developing and developed countries found by Jacobs and Cutting (198,1986), the level of traffic safety in terms of death per vehicle has achieved a significant improvement with the increase of motorization as shown in Fig. 6. For example, at the level of motorization level of 3 and above the majority of points are below the developing country curve and become closer from the developed countries curve.

5 5 Fig. 7 illustrates fatality rates related to motorization levels for fourteen countries. The figure shows both fitted curves for developed and developing countries obtained by Jacobs and Cutting. It can be concluded from this figure that KSA lies almost under the fitted line for developing countries. This implies that in relative to its motorization level, KSA has low fatality rate compared to those of other developing countries. On the other hand, KSA lies relatively far above the fitted curve of developed countries suggesting that its fatality rate is still high compared to those of developed countries. It is also apparent from this figure that KSA is relatively in a reasonable position among other countries. For example, KSA has a higher motorization level than some other countries (e.g., Egypt, South Korea, Jordan, Mexico, Brazil, and Venezuela), its fatality rate is yet much lower. ACCIDENT SEVERITY USING ODDS RATIO A commonly used technique in the analysis of categorical data is the examination of odds ratios (ω). Refer to Table 3. Within row 1, the odds that the response is in column. Within row 2, the corresponding Ω 1 = n 11 / n 21 1 instead of column 2 is defined to be. The odds ratio is simply the ratio of these two odds Ω 2 = n 12 / n 22 odds equals [Agresti,199]: (3) Ω1 ω = = Ω 21 n n n n The odds ratio (non negative number) is also termed the cross-product ratio and the approximate relative risk [Fleiss, 1981]. Taking the year of 1971 as a reference, the odds ratios of fatalities among $ω e ± zσ accident victims (injuries + fatalities) with 95% confidence intervals ( [Cristensen,199]) were computed for the years from 1972 to 1994 as presented in Table 4 and plotted in Fig. 8. That is, the measure of odds ratio is used in this study as a severity index to asses the levels of accident severity over time. For illustration, Table 5 gives the frequencies of fatalities and injuries for 1994 and 1971 in KSA. The odds ratio = 1.2).This is an estimate of the $ω computed from this table using (3) is 1.2 ( population odds ratio but it is fairly not far from 1 and it means that the odds of a victim being killed in a traffic accident occurred in 1991 equals to the odds of a victim being killed in a traffic accident occurred in Thus, the levels of accident severity in 1971 and 1994 are almost even suggesting that no improvement in this dimension seems to take place between these two points of time. Yet, it should be perceived from Fig. 8 that, overall, since 1985 the levels of severity have shown some sign of improvement compared to the period between 1975 and The maximum severity was observed in 1977 where the odds ratio equals to 1.51 indicating that the odds of a victim being killed in a traffic accident occurred in 1977 was 1.5 (one and a half) time as large as the odds of

6 6 a victim being killed in a traffic accident occurred in The severity over the past five years has displayed a general increase. FACTORS CONTRIBUTING TO ACCIDENTS Traffic accidents can be attributed to human, vehicular, and environmental factors. When considered alone, human factors have been found to contribute to 57 percent of the accidents in the developed countries. Together with vehicular and environmental factors, human factors account for about 92 percent [Ergun (1984)]. The following sections discuss road, vehicular and human factors. Road Factors Despite more than two decades of modern road building in KSA, knowledge of the safety consequences of highway design decisions is limited. The Ministry of Communications is responsible for road design and construction in the country. This agency relies on design standard implemented in developed countries. Engineering data for investigating relationships between safety and highway design features are not available due to the problems with the current accident reporting system mentioned earlier. Vehicular Factors About 5% (compared to 1.6% in USA [National Safety Council, 1994] of road accidents in KSA were attributed to vehicular factors. In many developed countries 2 to 2 percent of accidents have been related to such factors [Treat,198]. KSA has started a periodic Motor Vehicle Inspection Program (MVIP) in All vehicles must be inspected on an annual basis. The program gives more attention to the vehicle tires, lights, steering and braking system. Recently, inspection stations of MVIP cover 9% of the country [Ministry of Communications,1994]. Ergurn (1987) found that the average condition of vehicles in KSA is worse than that of vehicles in some USA states (Missouri, California, and Pennsylvania). Furthermore, he observed that there was a strong relationship between driver characteristics (e.g., income and education) and vehicle condition. Unfortunately, no in-depth studies have been conducted on the role of various vehicle defects in accident causation in KSA. However, it appears from statistics that involvement of such factors is very small (about 5%) compared with that of human errors. Human Factors As mentioned earlier, about eighty percent of accidents reported in KSA during 1994 were attributed to drivers. Lee (1986) evaluated human factors on traffic accidents in Riyadh (The capital of KSA) and reported very close percentage (84%). Hence, studying human factors such as age, nationality, and education is of interest. Several variables related to the driver are analyzed below. Age

7 7 Among other age groups, drivers of 3-4 year old are more involved in road accidents, as illustrated in Fig.9.a. It should be stated that drivers less than 4 year old (an important slice of society needed badly to move the development wheel in this developing country) represent about 68% of all drivers involved in accidents. more than one third of those drivers stayed in hospitals for treatments [Undergoing study by the other]. This indicates how much loss accidents made to the society. The teenage drivers involved in 2.5% of all accidents occurred in USA during 1993 [National Highway Safety,1994]. The corresponding percentage for KSA is about 7%, i.e. three times greater. Nationality Non-Saudis account for about 38% of the country population[ministry of National Economy and Finance, 1993], they yet involved in 44 percent of accidents. In other words, Saudis and non-saudis are almost equally involved in road accidents (Fig.9.b). This may be attributed to the presence of expatriates from all over the world. The drivers of this population come from different cultures with different habits and attitudes. Thus, the wide differences in their backgrounds may create traffic-safetyrelated problems. This raises the need for a unique educational and training program developed in cooperation with the diplomatic sector for each nationality. Marital Status According to police data, married drivers have found to be involved in more accidents than single ones, as shown in Fig.1.c. Yet, the percentage of the two groups are very close. It should be stated that based on Islamic rules women are not allowed to drive in KSA. Therefore, female drivers are not involved in this analysis. Education Data from police records indicate that 2% of drivers involved in road accidents in KSA over the period had never attended school and were illiterate (Fi.g.9.d). This group in the population of drivers needs a special consideration from traffic safety planners during public awareness campaigns. The interesting observation is that the percentage of illiterate drivers has reduced from 31% in the period to 2% in the period , 11% decrease. It should be mentioned that no data is available to lead us to know the proportion of illiterate drivers in the whole population of drivers in order to conduct more reliable comparison between the two groups of drivers in terms of education. Driver s License Fig.11 depicts the percentages of drivers without a driver s license involved in accidents in the country over fifteen years ( ). During that period the percent reached its peak (69.5%) in 1983 and decreased drastically to 11 percent in 199. Although the percentage of drivers committed this violation has achieved a remarkable reduction between the two five-year periods as given in Table 6 (from 34% to 14%, statistically significant at.5 level), this percentage increased steadily in the past five

8 8 years (i.e., from 11% in 199 to 19% in 1994 (Fig.9.e)). This may raise questions about law enforcement measures for unlicensed drivers. ACCIDENT CHARACTERISTICS In this section, typical characteristics of road accidents are analyzed. These characteristics include accident time, location, type, and cause. Through the analysis the percentages of some characteristics are compared with those in USA. Time of occurrence Government statistics indicate that 63% of traffic accidents occur during day time (Fi.g.1.a) This is a large percentage when compared to that of USA (48%). Moreover, fatality rates are higher in daytime in KSA. Yet, fatality crash rates during nighttime are much higher in USA than daytime rates. In fact they are almost five times higher [IIHS,1992]. The reason could be the smaller percentage of night travel in KSA due to the lack of night entertainment places, low level of industrialization (work time is between 8 a.m. and 2:3 p.m.), and social habits related to traditions. Further, alcohol consumption, which is considered popular cause of accidents in other countries, is forbidden in KSA. In terms of days, Fig.1.b gives the distribution of accident percentages by day of weekdays. It can be observed that the accident occurrence is almost uniformly distributed over days. In other words, the likelihood of accident occurrence in any day of the week is roughly even. Location of occurrence Fig.1.c show that the majority of traffic accidents (8%) occur inside the cities. This may reflect the huge amount of travel (vehicle kilometers) driven within urban areas. Although it is expected that the severity of rural accidents (death per accident) is higher than that of urban accidents, this can not be confirmed for KSA due to the lack of detailed data. A study conducted by the author [Al-Ghamdi,1995] showed that 53% of urban accidents occurred in Riyadh occurred at intersections and more than half of these accidents were right-angle collisions due to running the red light. Types of accidents The official statistics in KSA classify accident types into two categories: 1) collisions (i.e., with other motor vehicle(s), pedestrians, fixed objects, and animal), and 2) noncollision (i.e., roll-over and off-road). Table 7 gives the percentages for classifications under the two categories for KSA and USA. Both countries have almost a uniform distribution for accident types except for collision with pedestrians (KSA is about five six times greater) and collision with animal (USA is about four times greater). The percentages of accidents by type is given in Fig.1.d. Causes of accidents

9 9 The distribution of accidents by cause is shown in Fig.1.e. Among other causes violating speed limit ranks first followed by running the red light. Nearly 7% of accidents were attributed to speeding in excess of posted speed limit and failure to obey traffic signal indication. About forty-two percent of accidents were attributed to speeding. When compared with USA, KSA has 1.6 times more accidents due to speed as presented in Table 7. One fourth of accidents were due to traffic rule violations (e.g., improper turning, overtaking, and stopping). From Table 7 it can be concluded that the percentages of improper-overtaking and disregarded-signal accidents in KSA are about eight times and four times higher than in USA, respectively. As discussed above, speeding and running the red light are the predominant violations among other violations committed by drivers in KSA. Thus, more analysis regarding the two violations are presented below. The question of interest is: have these violations decreased over the last fifteen years? To answer this question the proportions of each violation for two five-year periods (i.e., and ) were ), frequency n statistically compared. Table 6 presents the total number of violations ( ) related to corresponding violation during each of the two p ) and proportion ( x ( periods. The hypothesis test performed, using z-test for comparing two proportions, has the following form: H : p p = versus H : p p > o 1 2 a 1 2 is the proportion of corresponding variable (violation) during the ith 5-year where period and p i i = The hypothesis tests conclude the following: A significant reduction (at.5 level) in speeding violation was observed between the two periods. That is, a sound improvement in lowering the frequency of this dangerous violation has been achieved (Reject the null hypothesis). No significant difference was found between the proportions of running the red light violation indicating that drivers still disregard the red indication (Accept the null hypothesis). USAGE OF SEAT BELTS As discussed above, the severity index has increased recently using odds ratio. One effective way to reduce severity during the occurrence of a road accident is by using seat belts. Less than 2% [Lee, 1983] of the drivers involved in accidents in KSA were belted compared to 62% and 9% in USA and Canada, receptively [IIHS,1995]. Past studies have shown that safety belts reduce the chance of death or serious injury in a crash by almost half. Other studies indicated that in front crashes drivers reported to be

10 1 using their belts enjoyed an extra margin of protection with air bags [IIHS,1992]. Driver deaths in frontal crashes were 2 percent lower among belted drivers of passenger cars equipped with air bags than among belted drivers in cars without air bags. That is, air bags are more effective with the use of safety belts. Despite these facts, KSA has no safety belt use laws. Further, no public awareness campaign has been conducted to educate drivers for the importance of wearing seat belts. DISCUSSION This study has shown that despite the enormous increase in the number of registered vehicles in KSA, fatality rates (per registered vehicle) appears to decline. Using odds ratio, accident severity has declined over the past 25 years. Despite the overall decreasing trend in both fatality rates and severity, data have shown that this developing country has experienced a worsening situation an in safety levels since 199. That is, fatality rate has increased from 5.5 in 199 to 7 in Similarly, the severity index represented by odds ratio has become 1.2 in 1994 compared with.92 in 199. Efforts were made in the present study to compare the situation of traffic safety in KSA with that of other nations using Smeed s formula. The comparison revealed that KSA stands at a reasonable position. In spite of its relatively high motorization level, this country has a lower fatality rate than some other countries. The study has also disclosed that drivers are responsible for nearly eighty percent of accidents. About 68% of drivers involved in road accidents during the last five years were aging below than 4 years. The proportion of teenage drivers were found to be three times that of USA. Approximately one-fifth of drivers involved in accidents were unlicensed. With respect to accident causes, nearly 7% of accidents were attributed to speeding in excess of posted speed limit and failure to obey traffic signal indication. RECOMMENDATIONS Based on the previous discussions and findings, recommendations of this study are outlined as follows: In-depth research should be started soon to investigate the current increasing trend in both fatality rates and accident severity. Accident reporting system is a problem in KSA. No detailed information is available in order to carry out deep research. For example, relationship between accident occurrences and road/vehicle factors is obstructed by data limitations. The manual filling system for accident reports creates difficulties in collecting data for analysis purposes. The data collection system should improved and the need for computerization is urgently needed. There should be a special consideration to the problem of illegal driving (driving without a driver s license). Unlicensed drivers should be strictly enforced to keep them off the road.

11 11 Two driver-related-causes of accidents were found to be predominant, namely, exceeding speed limit and the failure to stop at the red light. Strict low enforcement along with educational campaigns must be seriously considered to bring the numbers of both violations down. The use of safety belts is relatively very low. Using safety belts should be compulsory. Together with publicity, enforcement should be effective in this matter. There should be a permanent road safety committee to supervise the implementation of any safety programs and to evaluate safety measures and strategies implemented in the future. The committee should also be responsible for directing research activities according to the problem needs. To gain some insight into the size and nature of the road accident problem, KSA can approach the problem more realistically by establishing a research institute (long-run strategy) where in-depth studies on human, vehicular and environmental factors contributing to road accidents can be conducted. REFERENCES The General Directorate of Traffic, Ministry of Interior, Riyadh. The Publications of Road Accident Statistics, for the years Ministry of Communications. Roads and Transportation: Facts and Numbers., Saudi Arabia, A. Bener and K. S. Jadaan. A Perspective on Road Fatalities in Jeddah, Saudi Arabia. Accid. Anal. and Prev., Vol. 24, No. 2, pp , World Tables. 3rd edition, World Bank, Washington, D.C., National Safety Council. Accident Facts, USA, S. E. Asogwa. The Use of the Police for Limited Road Accident Data Collected in Developing Countries. Accident Analysis & Prevention, Vol. 14, No. 3, pp , G. D. Jacobs and I. Sayer. Road Accidents in Developing Countries. Accident Analysis & Prevention, Vol. 15, No. 5, pp , F. A. Gharaybeh. Application of Smeed s Formula to Assess Development of Traffic Safety in Jordan. Accid. Anal. and Prev., Vol. 26, No. 1, pp , 1994.

12 12 A. S. Al-Ghamdi, Z. Nemeth, and R. Rogness. Forecasting Traffic Accidents in Saudi Arabia by Using a Time Series Model. Presented at the 72nd Annual Meeting of TRB Conference, Washington, D.C., A. S. Al-Ghamdi. Time Series Forecasts for Traffic Accidents, Injuries and Fatalities in Saudi Arabia. Accepted for publication at the Journal of King Saud University [Engineering Science], A. S. Al-Ghamdi. Analysis of Traffic Accidents at Signalized Intersections in Riyadh. To appear at The Fourth Saudi Engineering Conference. King Abdulaziz Univ., Jeddah, G. Ergun. Condition of Vehicles in Saudi Arabia. Accident Analysis & Prevention, Vol. 19, No. 5, pp , G. Ergun. Effects of Driver Characteristics on Accident Involvement: A Study in Saudi Arabia. The Arabian Journal for Science and Engineering, Vol. 9, No. 4, pp , Saudi Arabia, J. R. Treat. A Study of Precrash Factors Involved in Traffic Accidents. Highway Safety Research Institute, No. HSRI 1/11, 6/1, Ann Arbor, Michigan, 198. A. Mekky. Road Traffic Accidents in Rich Developing Countries: The Case of Libya. Accident Analysis & Prevention, Vol. 16, No.4, pp , R. J. Smeed. Some Statistical Aspects of Safety Research. Journal of the Royal Statistical Society: Series A (General), Part I, pp. 1-23, R. J. Smeed. Variations in the Pattern of Accident Rates in Different Countries and their Causes. Traffic Engineering & Control, pp , Nov A. Agresti. Categorical Data Analysis. New York: Johns Wiley & Sons, 199. J. L. Fleiss. Statistical Methods for Rates and Proportions. New York: Johns Wiley & Sons, Second Edition, R. Christensen. Log-Linear Modes. New York: Springer-Verlag, 199. Ministry of National Economy and Finance. Population Statistics. Saudi Arabia, K. W. Lee. An Analysis of Automobile Accidents in Riyadh. ITE Journal, pp , Feb Insurance Institute For Highway Safety (IIHS). Status Report. Vol. 26, No. 5, May, Insurance Institute For Highway Safety (IIHS). Status Report. Vol. 26, No. 5, October, Table 1. Population, registered vehicles, and traffic accident statistics ( ). Year Population Registered Accidents Injury Fatality

13 13 in millions vehicle Table 2. Severity and cost of accidents for KSA and USA. Item KSA (1993) USA (1992) Severity of accident PDO 82.1% 91.6% Injury 15.3% 8.% Fatal 2.6%.313% Total accidents 85,277 11,9, Total cost (billion) $4.96 $47.5 Cost per accident $58,163 $34,22

14 14 Table 3. A typical 2x2 table for categorical data. Columns 1 2 Totals Rows 1 n 11 n 12 n 1. 2 n 21 n 22 n 2. Totals n.1 n.2 n.. Table 4. Estimated odds ratio (severity index) and 95% confidence limits. Year Severity Index (Odds Ratio) 95% Confidence Interval Upper Limit Lower Limit Table 5. 2x2 for accident victims in 1971 and Victims Totals Fatality Injury Year ,77 32,133 36, ,153 Totals 4,647 36,716 41,363

15 15 Table 6. Proportions of three violations committed during the two periods. Violation n 1 x 1 p 1 n 2 x 2 p 2 Speed* 157,68 99, , , Run-red-light** 157,68 17, ,918 54, Unlicensed.* 191,152 65, ,533 73, at.5 level. H o * Reject at.5 level. H o ** Accept Table 7. A comparison for illustration between KSA and USA. Item KSA* USA** Type of accident Collision with- Other motor vehicles 73.7% 73.1% Pedestrian 9.5% 1.6% Fixed object 7.1% 14.7% Animal.9% 3.7% Noncollision 7.5% 5.6% Cause of accident Speed 41.9% 12.2% Disregarded signal 15.4% 3.5% Improper turn 7.3% 4.5% Improper overtaking 1.7% 1.3% * Source: [The General Directorate of Traffic, ] ** Source: [National Safety Council, Accident Facts, 1994].

16 Vehicles Percent increase [1971= reference] Accidents 5 Injuries Fatalities Population Year Fig. 1. Trends in registered vehicles, accidents, injuries, and fatalities. 4 Acc/person 35 Percent change (1971= reference) Inj/person Fat/person 5 Inj/veh Acc/veh Fat/veh Year Fig. 2. Trends in accident rates per vehicle and per person in KSA ( )

17 17 25 Fatality per 1, vehicles NORWAY UK AUSTRALIA SWEDEN NETHERLANDS CANADA SWITZERLAND JAPAN USA FINLAND GERMANY ITALY AUSTRIA DENMARK FRANCE NEW ZELAND BAHRAIN BELGIUM IRLAND ARGENTINA SPAIN SINGAPORE BULGARIA BULAGARIA HONG KONG KSA CHILE GREECE KUWAIT POLAND POLAND HUNGRY PORTUGAL MEXICO JORDAN THAILAND BRAZIL VENEZUELA EGYPT S KOREA Country Fig.3. Death rates for various developing and developed countries F\V x 1, 3 F\V =.3* (V\P)* * Actual V/P x 1 Fig.4. Actual and fitted values for relationship between death rate and motorization.

18 F\V x 1, 3 F\V =.3*(V\P)**-.795 Actual YEAR Fig.5. Actual and fitted values for death rates over years. 6 5 F\V x 1, Developing countries KSA 1 Developed countries V\P x 1 Fig.6. Smeed s fitted curves for KSA, developing and developed countries.

19 19 6 F\V =.21 x (V\P)**-.72 F\V x 1, F\V =.39 x (V\P)**-.64 S. Kor. Eg. Ven. Braz. Mex. Jord. KSA Kuw. Gr. Sing. Bah. UK & Sw. USA V\P x 1 Fig.7. KSA and other countries with the fitted curves for developing and developed Upper 1.2 Odds ratio Est im at ed Low er Year Fig.8. Accident severity represented by odds ratio.

20 2 1 1 Percent of drivers Saudi Other Nationality Percent of drivers <18 >=18 >=3 >=4 >=5 Age (b) Nationality factor. (a) Age factor. 1 1 Percent of drivers Literate Illiterate Percent of drivers Married Not married Education status Marital status (d) Education factor. (c) Marital-status factor. 1 Percent of drivers Yes No Licience status (e) Licensee status. Fig.9. Distributions of accidents by variables related to the driver.

21 21 2 Percent of accidents Day Percent of accidents Day Night Time of accident (b) Distribution by day. (a) Time occurrence factor. Percent of accidents Urban Rural Location of accident (c) Location factor. Percent of accidents Percent of accidents Parking U-Turn Overtaking Run red light Speed Alcohol Other Other vehicle Fixed object Pedestrian Animal Turnover Off-road Other Cause of accident Type of accident (e) Accident-cause factor. (d) Accident-type factor. Fig.1. Accident characteristics ( ).

22 Percent of drivers Year Fig.11. Percentages of unlicensed drivers involved in road accidents ( ).

23 23 ROAD ACCIDENTS IN SAUDI ARABIA: A COMPARATIVE AND ANALYTICAL STUDY Ali Saeed Al-Ghamdi King Saud University, College of Engineering, P. O. Box 8, Riyadh 11421, Saudi Arabia ABSTRACT The main goal of this study is to discusses the magnitude of traffic accidents in the Kingdom of Saudi Arabia (KSA) over the last fifteen years and to compare the situation of traffic safety with that of other countries. This developing country has experienced a rapid economic growth resulting in an enormous increase in the motorization rate (vehicle per 1 population) associated with rapidly expanding road construction. As a result, traffic accidents have become a serious problem facing the country. During the period from 1971 to 1994, the numbers of traffic accidents, injuries, and fatalities have increased by 3 times, 6 times, and 7 times, respectively. This study showed that both fatality rate and accident severity have increased and the need for improvement is urgently needed. Using odds ratio, accident severity has declined over the past 25 years. Despite the overall decreasing trend in both fatality rates and severity, data have shown that this developing country has experienced a worsening situation in safety levels since 199. That is, fatality rate has increased from 5.5 in 199 to 7 in Similarly, the severity index represented by odds ratio has become 1.2 in 1994 compared with.92 in 199. In addition, efforts were made in the present study to compare the situation of traffic safety in KSA with that of other nations using Smeed s formula. The comparison revealed that KSA stands at a reasonable position. In spite of its relatively high motorization level, this country has a lower fatality rate than some other countries. Based on the findings, the study recommends short-run and long-run strategies in order to improve traffic safety in this developing country.

24 24 ROAD ACCIDENTS IN SAUDI ARABIA: A COMPARATIVE AND ANALYTICAL STUDY Ali Saeed Al-Ghamdi King Saud University, College of Engineering, P. O. Box 8, Riyadh 11421, Saudi Arabia Registered Vhicles from 144,768 in 197 to 5,861,614 in 1994 (4-fold). Paved oad length from 85 km in 197 to 43,3 km in 1992 (5-fold). From 197 to 1994: Traffic accidents have increased 3 times. Injuries have increased 6 times. Fatalities have increased 7 times.

25 25 Using Smeed s A pproach for Compariosn: KSA stands at a reasonable position. Unlicience Drivers 19% in 1994.

26 26 Discussions and Results KSA stands at a reasonable position. 8% of accidents due to human error. Speeding is the major cause. Computerized Data Collection System!! Education and Public Campaigns!! Enforcement!!

27 27 Table 1. Population, registered vehicles, and traffic accident statistics ( ). Year Population Registered Accidents Injury Fatality in millions vehicle Table 2. Severity and cost of accidents for KSA and USA. Item KSA (1993) USA (1992) Severity of accident PDO 82.1% 91.6% Injury 15.3% 8.% Fatal 2.6%.313% Total accidents 85,277 11,9, Total cost (billion) $4.96 $47.5 Cost per accident $58,163 $34,22

28 28 Table 4. Estimated odds ratio (severity index) and 95% confidence limits. Year Severity Index (Odds Ratio) 95% Confidence Interval Upper Limit Lower Limit Table 5. 2x2 for accident victims in 1971 and Victims Totals Fatality Injury Year ,77 32,133 36, ,153 Totals 4,647 36,716 41,363

29 29 Table 6. Proportions of three violations committed during the two periods. Violation n 1 x 1 p 1 n 2 x 2 p 2 Speed* 157,68 99, , , Run-red-light** 157,68 17, ,918 54, Unlicensed.* 191,152 65, ,533 73, at.5 level. H o * Reject at.5 level. H o ** Accept Table 7. A comparison for illustration between KSA and USA. Item KSA* USA** Type of accident Collision with- Other motor vehicles 73.7% 73.1% Pedestrian 9.5% 1.6% Fixed object 7.1% 14.7% Animal.9% 3.7% Noncollision 7.5% 5.6% Cause of accident Speed 41.9% 12.2% Disregarded signal 15.4% 3.5% Improper turn 7.3% 4.5% Improper overtaking 1.7% 1.3% * Source: [The General Directorate of Traffic, ] ** Source: [National Safety Council, Accident Facts, 1994].

30 Vehicles Percent increase [1971= reference] Accidents 5 Injuries Fatalities Population Year Fig. 1. Trends in registered vehicles, accidents, injuries, and fatalities. 4 Acc/person 35 Percent change (1971= reference) Inj/person Fat/person 5 Inj/veh Acc/veh Fat/veh Year Fig. 2. Trends in accident rates per vehicle and per person in KSA ( )

31 31 25 Fatality per 1, vehicles NORWAY UK AUSTRALIA SWEDEN NETHERLANDS CANADA SWITZERLAND JAPAN USA FINLAND GERMANY ITALY AUSTRIA DENMARK FRANCE NEW ZELAND BAHRAIN BELGIUM IRLAND ARGENTINA SPAIN SINGAPORE BULGARIA BULAGARIA HONG KONG KSA CHILE GREECE KUWAIT POLAND POLAND HUNGRY PORTUGAL MEXICO JORDAN THAILAND BRAZIL VENEZUELA EGYPT S KOREA Country Fig.3. Death rates for various developing and developed countries F\V x 1, 3 F\V =.3* (V\P)* * Actual V/P x 1 Fig.4. Actual and fitted values for relationship between death rate and motorization.

32 F\V x 1, 3 F\V =.3*(V\P)**-.795 Actual YEAR Fig.5. Actual and fitted values for death rates over years. 6 5 F\V x 1, Developing countries KSA 1 Developed countries V\P x 1 Fig.6. Smeed s fitted curves for KSA, developing and developed countries.

33 33 6 F\V =.21 x (V\P)**-.72 F\V x 1, F\V =.39 x (V\P)**-.64 S. Kor. Eg. Ven. Braz. Mex. Jord. KSA Kuw. Gr. Sing. Bah. UK & Sw. USA V\P x 1 Fig.7. KSA and other countries with the fitted curves for developing and developed Upper 1.2 Odds ratio Est im at ed Low er Year Fig.8. Accident severity represented by odds ratio.

34 Percent of drivers Saudi Other Nationality Percent of drivers <18 >=18 >=3 >=4 >=5 Age (b) Nationality factor. (a) Age factor. 1 1 Percent of drivers Literate Illiterate Percent of drivers Married Not married Education status Marital status (d) Education factor. (c) Marital-status factor. 1 Percent of drivers Yes No Licience status (e) Licensee status. Fig.9. Distributions of accidents by variables related to the driver.

35 35 2 Percent of accidents Day Percent of accidents Day Night Time of accident (b) Distribution by day. (a) Time occurrence factor. Percent of accidents Urban Rural Location of accident (c) Location factor. Percent of accidents Percent of accidents Parking U-Turn Overtaking Run red light Speed Alcohol Other Other vehicle Fixed object Pedestrian Animal Turnover Off-road Other Cause of accident Type of accident (e) Accident-cause factor. (d) Accident-type factor. Fig.1. Accident characteristics ( ).

36 Percent of drivers Year Fig.11. Percentages of unlicensed drivers involved in road accidents ( ).