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ROAD ACCIDENTS IN SAUDI ARABIA: A COMPARATIVE AND ANALYTICAL STUDY

Ali. S. Al-Ghamdi1

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 1000 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 30 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 1000 population) associated with rapidly expanding road construction. The number of registered vehicles has increased from 144,768 in 1970 to 5,861,614 in 1994, a forty-fold increase in 24 years [General Traffic Directorate (1971-1994)]. 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 8500 km in 1970 to 43,003 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 30 times, 6 times, and 7 times, respectively (see Table 1 and Fig.1). Fig.2 depicts that during the period 1971-1994 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 0.313. 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.

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USA. Statistics have also shown that more than about eighty percent of all reported accidents occurred in KSA during the last five years (1990-1994) 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 (1971-1994), 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].

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ACCIDENT RATES COMPARED Three known measures can be used for accident comparisons when related to

motorization rate (vehicles per 1000 persons (V/P)): 1) fatalities per 10,000 persons (F/P), 2) fatalities per 1000 vehicles (F/V), and 3) fatalities per 100 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 10,000 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 20 times based on 1970s data). Among 40 nations, KSA ranks the 25th as depicted in Fig. 3. About 8 persons per 10,000 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:

FV

VP

= ⎛⎝⎜

⎞⎠⎟−

αβ

(1)

It follows from the above formula that F

V, the death rate per registered vehicle,

decreases as VP

, the proportion of vehicles in population (motorization), increases. Smeed

applied this formula on data from 20 developed countries and found that the death rate is varying approximately inversely as the two-thirds power of the proportion of vehicles to

the population. In other words, he found that α and β are 0.0003 and 2/3, respectively. Applying Smeed’s formula on data from 35 developing countries, Jacobs and Cutting

(1986) found that α and β are 0.00039 and 0.64, respectively. In addition Jacobs and Cutting (1980) repeated the earlier work of Smeed on data from developed countries and

found that α and β are 0.00021 and 0.72, respectively, indicating that the fatality rates based on registered vehicles in these countries have decreased between 1938 and 1980.

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In this study, Smeed’ formula was used on KSA data for the period from 1971 to 1994 (Table 1). Regression technique is employed to estimate α and β. The linear transformation of eq. (1) was first obtained by taking its logarithm:

log FV

= log αβV

P⎛⎝⎜

⎞⎠⎟−

and hence

log log logF

VVP

= −α β

The linear transformation was then regressed to give the following model:

log . . logF

VVP

= − −810 0 795 (R 2 92%≈)

By taking the antilog of the above mode, the values of α and β for the case of KSA were

found to be 0.0003 and 0.795, respectively. Thus, the modified Smeed’s formula for the case of KSA becomes:

FV

VP

= ⎛⎝⎜

⎞⎠⎟−

0 00030 795

..

(2)

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 (1971-1994), 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 (1990-1994) 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 (1980,1986) , 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 300 and above the majority of points are below the developing country curve and become

closer from the developed countries curve.

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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 1 instead of column 2 is defined to be Ω1 11 21= n n/. Within row 2, the corresponding

odds equals Ω2 12 22= n n/. The odds ratio is simply the ratio of these two odds [Agresti,1990]:

ω = =

ΩΩ

1

21

11 22

12 21

n nn n

(3)

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

accident victims (injuries + fatalities) with 95% confidence intervals ($ω σe z± [Cristensen,1990]) 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

computed from this table using (3) is 1.02 ($ω = 1.02).This is an estimate of the 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 1971. 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 1985. 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

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a victim being killed in a traffic accident occurred in 1971. 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 20 percent of accidents have been related to such factors [Treat,1980]. KSA has started a periodic Motor Vehicle Inspection Program (MVIP) in 1986. 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 90% 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

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Among other age groups, drivers of 30-40 year old are more involved in road accidents, as illustrated in Fig.9.a. It should be stated that drivers less than 40 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 2.05% 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-safety-related 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.10.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 20% of drivers involved in road accidents

in KSA over the period 1990-1994 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 1980-1984 to 20% in the period 1990-1994, 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 (1980-1994). During that period the percent reached its peak (69.5%) in 1983 and decreased drastically to 11 percent in 1990. 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 0.05 level), this percentage increased steadily in the past five

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years (i.e., from 11% in 1990 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.10.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 2:30 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.10.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.10.c show that the majority of traffic accidents (80%) 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.10.d.

Causes of accidents

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The distribution of accidents by cause is shown in Fig.10.e. Among other causes violating speed limit ranks first followed by running the red light. Nearly 70% 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., 1980-1984 and 1990-1994) were

statistically compared. Table 6 presents the total number of violations (n), frequency (x) and proportion (p) related to corresponding violation during each of the two

periods. The hypothesis test performed, using z-test for comparing two proportions, has the following form:

H p p versus H p po a: :1 2 1 20 0− = − >

where pi is the proportion of corresponding variable (violation) during the ith 5-year period and

i =−−

⎧⎨⎩

1 1980 19842 1990 1994

.

The hypothesis tests conclude the following:

• A significant reduction (at 0.05 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 90% 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

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using their belts enjoyed an extra margin of protection with air bags [IIHS,1992]. Driver deaths in frontal crashes were 20 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 1990. That is, fatality rate has increased from 5.5 in 1990 to 7 in 1994. Similarly, the severity

index represented by odds ratio has become 1.02 in 1994 compared with 0.92 in 1990.

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 40 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 70% 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.

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• 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 1971-1994.

Ministry of Communications. Roads and Transportation: Facts and Numbers., Saudi Arabia, 1994.

A. Bener and K. S. Jadaan. A Perspective on Road Fatalities in Jeddah, Saudi Arabia. Accid. Anal. and

Prev., Vol. 24, No. 2, pp. 143-148, 1992.

World Tables. 3rd edition, World Bank, Washington, D.C., 1984.

National Safety Council. Accident Facts, USA, 1994.

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. 203-208, 1982.

G. D. Jacobs and I. Sayer. Road Accidents in Developing Countries. Accident Analysis & Prevention, Vol.

15, No. 5, pp. 337-353, 1983.

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. 113-120, 1994.

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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., 1993.

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], 1994.

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, 1995.

G. Ergun. Condition of Vehicles in Saudi Arabia. Accident Analysis & Prevention, Vol. 19, No. 5, pp.

343-358, 1987.

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. 309-319, Saudi Arabia, 1984.

J. R. Treat. A Study of Precrash Factors Involved in Traffic Accidents. Highway Safety Research Institute,

No. HSRI 10/11, 6/1, Ann Arbor, Michigan, 1980.

A. Mekky. Road Traffic Accidents in Rich Developing Countries: The Case of Libya. Accident Analysis & Prevention, Vol. 16, No.4, pp. 263-277, 1987.

R. J. Smeed. Some Statistical Aspects of Safety Research. Journal of the Royal Statistical Society: Series A

(General), Part I, pp. 1-23, 1949.

R. J. Smeed. Variations in the Pattern of Accident Rates in Different Countries and their Causes. Traffic Engineering & Control, pp. 364-371, Nov. 1968

A. Agresti. Categorical Data Analysis. New York: Johns Wiley & Sons, 1990.

J. L. Fleiss. Statistical Methods for Rates and Proportions. New York: Johns Wiley & Sons, Second

Edition, 1981.

R. Christensen. Log-Linear Modes. New York: Springer-Verlag, 1990.

Ministry of National Economy and Finance. Population Statistics. Saudi Arabia, 1993.

K. W. Lee. An Analysis of Automobile Accidents in Riyadh. ITE Journal, pp. 35-39, Feb 1986.

Insurance Institute For Highway Safety (IIHS). Status Report. Vol. 26, No. 5, May, 1991.

Insurance Institute For Highway Safety (IIHS). Status Report. Vol. 26, No. 5, October, 1992.

Table 1. Population, registered vehicles, and traffic accident statistics (1971-1994).

Year Population Registered Accidents Injury Fatality

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in millions vehicle 1971 6.25 144768 4147 5483 570 1972 6.5 180185 7197 6530 834 1973 6.75 242974 9808 7901 1058 1974 6.8488 355022 10897 8771 1154 1975 7.3754 514361 13475 10532 1594 1976 7.902 774443 15709 11606 1975 1977 8.4287 1112973 15785 11413 2033 1978 8.9553 1432909 18051 14824 2378 1979 9.4819 1723116 17743 16832 2871 1980 10.0085 2069479 18758 16218 2731 1981 10.5352 2467903 17897 15872 2427 1982 11.0618 3018811 21597 18616 2953 1983 11.5884 3569009 24594 21475 3499 1984 12.115 3919871 27348 21850 3338 1985 12.6417 4144245 29052 22630 3276 1986 13.1683 4280986 32092 22602 2703 1987 13.6949 4427991 32024 23723 2814 1988 14.2215 4574244 32584 23059 2585 1989 14.7482 4767922 35744 23278 2647 1990 15.2748 4950466 35799 23526 2697 1991 15.8014 5117441 37127 25516 3232 1992 16.328 5328505 40076 27385 3495 1993 16.8547 5588013 85277 34880 3719 1994 17.3813 5861614 125324 32133 4077

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% 8.0% Fatal 2.6% 0.313%

Total accidents 85,277 11,900,000Total cost (billion) $4.96 $407.5

Cost per accident $58,163 $34,202

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Table 3 . A typical 2x2 table for categorical data.

Columns Totals 1 2

Rows 1 n11 n12

n1.

2 n21 n22

n2.

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 Limit1972 1.026899 0.986298 1.069172 1973 1.07666 1.031543 1.12375 1974 1.057869 1.012483 1.105289 1975 1.216893 1.15927 1.27738 1976 1.368231 1.29852 1.441685 1977 1.432229 1.358496 1.509965 1978 1.289797 1.21951 1.364136 1979 1.371426 1.291116 1.456732 1980 1.35394 1.276176 1.436442 1981 1.229456 1.161951 1.300884 1982 1.275417 1.199911 1.355674 1983 1.310044 1.227062 1.398637 1984 1.228315 1.151979 1.30971 1985 1.16395 1.09216 1.240459 1986 0.961555 0.906573 1.019871 1987 0.953739 0.898349 1.012544 1988 0.901353 0.850692 0.955032 1989 0.914289 0.862431 0.969264 1990 0.921739 0.869082 0.977587 1991 1.018436 0.955968 1.084986 1992 1.026147 0.961194 1.095488 1993 0.857284 0.801639 0.916792 1994 1.020151 0.951371 1.093903

Table 5 . 2x2 for accident victims in 1971 and 1994.

Victims Totals Fatality Injury

Year 1994 4,077 32,133 36,210 1971 570 4583 5,153 Totals 4,647 36,716 41,363

15

Table 6. Proportions of three violations committed during the two periods.

Violation 1980-1984 1990-1994

n1 x1

p1 n2

x2 p2

Speed* 157,680 99,679 0.63 353,918 148,219 0.42 Run-red-light** 157,680 17,974 0.11 353,918 54,578 0.15 Unlicensed.* 191,152 65,239 0.34 545,533 73,551 0.14

* Reject Ho at 0.05 level. ** Accept Ho at 0.05 level.

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 0.9% 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 10.7% 1.3%

* Source: [The General Directorate of Traffic, 1971-1994.] ** Source: [National Safety Council, Accident Facts, 1994].

16

Year

Perc

ent i

ncre

ase

[197

1= r

efer

ence

]

0

500

1000

1500

2000

2500

3000

3500

4000

1971

1972

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

Vehicles

Fatalit iesInjuries

Populat ion

Accidents

Fig. 1 . Trends in registered vehicles, accidents, injuries, and fatalities.

Year

Perc

ent c

hang

e (1

971=

ref

eren

ce)

0

50

100

150

200

250

300

350

400

1971

1972

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

Acc/person

Inj/personFat/person

Acc/vehFat/vehInj/veh

Fig. 2. Trends in accident rates per vehicle and per person in KSA (1971-1994)

17

NO

RW

AY

UK

AU

STR

ALI

A

SWED

EN

NET

HER

LAN

DS

CA

NA

DA

SWIT

ZER

LAN

D

JAPA

N

USA

FIN

LAN

D

GER

MA

NY

ITA

LY

AU

STR

IA

DEN

MA

RK

FRA

NC

E

NEW

ZEL

AN

D

BA

HR

AIN

BEL

GIU

M

IRLA

ND

AR

GEN

TIN

A

SPA

IN

SIN

GA

POR

E

BU

LGA

RIA

BU

LAG

AR

IA

HO

NG

KO

NG

KSA

CH

ILE

GR

EEC

E

KU

WA

IT

POLA

ND

POLA

ND

HU

NG

RY

POR

TUG

AL

MEX

ICO

JOR

DA

N

THA

ILA

ND

BR

AZI

L

VEN

EZU

ELA

EGY

PT

S K

OR

EA

Country

0

5

10

15

20

25

Fata

lity

per

10,0

00 v

ehic

les

Fig.3. Death rates for various developing and developed countries.

V/P x 1000

F\V

x 1

0,00

0

0

10

20

30

40

50

60

0 50 100 150 200 250 300 350

F\V = 0.0003* (V\P)* * -0.795 Actual

Fig.4. Actual and fitted values for relationship between death rate and motorization.

18

YEAR

F\V

x 1

0,00

0

0

10

20

30

40

50

60

1970 1975 1980 1985 1990 1995

F\V = 0.0003*(V\P)**-0.795 Actual

Fig.5 . Actual and fitted values for death rates over years.

V\P x 1000

F\V

x 1

0,00

0

0

10

20

30

40

50

60

0 50 100 150 200 250 300 350

Developed countries

KSA

Developing countries

Fig.6. Smeed’s fitted curves for KSA, developing and developed countries.

19

V\P x 1000

F\V

x 1

0,00

0

0

10

20

30

40

50

60

0 100 200 300 400 500 600 700 800

F\V = 0.00021 x (V\P)**-0.72

KSA

USA

Eg.

UK & Sw.

Braz.

S. Kor.

Bah.

Ven.

Sing.

Jord.Mex.

Gr.

F\V = 0.00039 x (V\P)**-0.64

Kuw.

Fig.7. KSA and other countries with the fitted curves for developing and developed

Year

Odd

s ra

tio

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1972

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

Upper

Low erEst im at ed

Fig.8. Accident severity represented by odds ratio.

20

<18 >=18 >=30 >=40 >=50

Age

0

20

40

60

80

100

Perc

ent o

f dri

vers

Saudi O ther

Nationality

0

20

40

60

80

100

Perc

ent o

f dri

vers

(a) Age factor. (b) Nationality factor.

Married Not married

Marital status

0

20

40

60

80

100

Perc

ent o

f dri

vers

Literate Il l i terate

Education status

0

20

40

60

80

100

Perc

ent o

f dri

vers

(c) Marital-status factor. (d) Education factor.

Yes No

Licience status

0

20

40

60

80

100

Perc

ent o

f dri

vers

(e) Licensee status.

Fig.9. Distributions of accidents by variables related to the driver.

21

Day Night

Time of accident

0

20

40

60

80

100

Perc

ent o

f acc

iden

ts

D a y

0

5

10

15

20

Perc

ent o

f acc

iden

ts

(a) Time occurrence factor. (b) Distribution by day.

Urban Rural

Location of accident

0

20

40

60

80

100

Perc

ent o

f acc

iden

ts

(c) Location factor.

Oth

er v

ehic

le

Fixe

d ob

ject

Pede

stri

an

Ani

mal

Tur

nove

r

Off

-roa

d

Oth

er

Type of accident

0102030405060708090

100

Perc

ent o

f acc

iden

ts

Park

ing

U-T

urn

Ove

rtak

ing

Run

red

ligh

tSp

eed

Alc

ohol

Oth

er

Cause of accident

0

20

40

60

80

100

Perc

ent o

f acc

iden

ts

(d) Accident-type factor. (e) Accident-cause factor.

Fig.10. Accident characteristics (1990-1994).

22

Year

Perc

ent o

f dri

vers

0

10

20

30

40

50

60

70

1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994

Fig.11. Percentages of unlicensed drivers involved in road accidents (1990-1994).

23

ROAD ACCIDENTS IN SAUDI ARABIA: A COMPARATIVE AND

ANALYTICAL STUDY

Ali Saeed Al-Ghamdi King Saud University, College of Engineering, P. O. Box 800, 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 1000 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 30 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 1990. That is,

fatality rate has increased from 5.5 in 1990 to 7 in 1994. Similarly, the severity index

represented by odds ratio has become 1.02 in 1994 compared with 0.92 in 1990. 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

ROAD ACCIDENTS IN SAUDI ARABIA: A COMPARATIVE AND ANALYTICAL STUDY

Ali Saeed Al-Ghamdi

King Saud University, College of Engineering, P. O. Box 800, Riyadh 11421, Saudi Arabia

• Registered Vhicles from 144,768 in 1970 to 5,861,614 in 1994 (40-fold).

• Paved oad length from 8500 km in 1970 to 43,003 km in 1992 (5-fold).

• From 1970 to 1994:

⇒Traffic accidents have increased 30 times.

⇒Injuries have increased 6 times.

⇒Fatalities have increased 7 times.

25

Using Smeed’s A

pproach for Compariosn:

• KSA stands at a reasonable position.

Unlicience Drivers

⇒19% in 1994.

26

Discussions and Results

• KSA stands at a reasonable position.

• 80% of accidents due to human error.

• Speeding is the major cause.

• Computerized Data Collection System!!

• Education and Public Campaigns!!

• Enforcement!!

27

Table 1. Population, registered vehicles, and traffic accident statistics (1971-1994).

Year Population

in millions Registered

vehicle Accidents Injury Fatality

1971 6.25 144768 4147 5483 570 1972 6.5 180185 7197 6530 834 1973 6.75 242974 9808 7901 1058 1974 6.8488 355022 10897 8771 1154 1975 7.3754 514361 13475 10532 1594 1976 7.902 774443 15709 11606 1975 1977 8.4287 1112973 15785 11413 2033 1978 8.9553 1432909 18051 14824 2378 1979 9.4819 1723116 17743 16832 2871 1980 10.0085 2069479 18758 16218 2731 1981 10.5352 2467903 17897 15872 2427 1982 11.0618 3018811 21597 18616 2953 1983 11.5884 3569009 24594 21475 3499 1984 12.115 3919871 27348 21850 3338 1985 12.6417 4144245 29052 22630 3276 1986 13.1683 4280986 32092 22602 2703 1987 13.6949 4427991 32024 23723 2814 1988 14.2215 4574244 32584 23059 2585 1989 14.7482 4767922 35744 23278 2647 1990 15.2748 4950466 35799 23526 2697 1991 15.8014 5117441 37127 25516 3232 1992 16.328 5328505 40076 27385 3495 1993 16.8547 5588013 85277 34880 3719 1994 17.3813 5861614 125324 32133 4077

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% 8.0% Fatal 2.6% 0.313%

Total accidents 85,277 11,900,000Total cost (billion) $4.96 $407.5

Cost per accident $58,163 $34,202

28

Table 4. Estimated odds ratio (severity index) and 95% confidence limits.

Year Severity Index (Odds Ratio)

95% Confidence Interval

Upper Limit Lower Limit1972 1.026899 0.986298 1.069172 1973 1.07666 1.031543 1.12375 1974 1.057869 1.012483 1.105289 1975 1.216893 1.15927 1.27738 1976 1.368231 1.29852 1.441685 1977 1.432229 1.358496 1.509965 1978 1.289797 1.21951 1.364136 1979 1.371426 1.291116 1.456732 1980 1.35394 1.276176 1.436442 1981 1.229456 1.161951 1.300884 1982 1.275417 1.199911 1.355674 1983 1.310044 1.227062 1.398637 1984 1.228315 1.151979 1.30971 1985 1.16395 1.09216 1.240459 1986 0.961555 0.906573 1.019871 1987 0.953739 0.898349 1.012544 1988 0.901353 0.850692 0.955032 1989 0.914289 0.862431 0.969264 1990 0.921739 0.869082 0.977587 1991 1.018436 0.955968 1.084986 1992 1.026147 0.961194 1.095488 1993 0.857284 0.801639 0.916792 1994 1.020151 0.951371 1.093903

Table 5 . 2x2 for accident victims in 1971 and 1994.

Victims Totals Fatality Injury

Year 1994 4,077 32,133 36,210 1971 570 4583 5,153 Totals 4,647 36,716 41,363

29

Table 6. Proportions of three violations committed during the two periods.

Violation 1980-1984 1990-1994

n1 x1

p1 n2

x2 p2

Speed* 157,680 99,679 0.63 353,918 148,219 0.42 Run-red-light** 157,680 17,974 0.11 353,918 54,578 0.15 Unlicensed.* 191,152 65,239 0.34 545,533 73,551 0.14

* Reject Ho at 0.05 level. ** Accept Ho at 0.05 level.

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 0.9% 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 10.7% 1.3%

* Source: [The General Directorate of Traffic, 1971-1994.] ** Source: [National Safety Council, Accident Facts, 1994].

30

Year

Perc

ent i

ncre

ase

[197

1= r

efer

ence

]

0

500

1000

1500

2000

2500

3000

3500

4000

1971

1972

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

Vehicles

Fatalit iesInjuries

Populat ion

Accidents

Fig. 1 . Trends in registered vehicles, accidents, injuries, and fatalities.

Year

Perc

ent c

hang

e (1

971=

ref

eren

ce)

0

50

100

150

200

250

300

350

400

1971

1972

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

Acc/person

Inj/personFat/person

Acc/vehFat/vehInj/veh

Fig. 2. Trends in accident rates per vehicle and per person in KSA (1971-1994)

31

NO

RW

AY

UK

AU

STR

ALI

A

SWED

EN

NET

HER

LAN

DS

CA

NA

DA

SWIT

ZER

LAN

D

JAPA

N

USA

FIN

LAN

D

GER

MA

NY

ITA

LY

AU

STR

IA

DEN

MA

RK

FRA

NC

E

NEW

ZEL

AN

D

BA

HR

AIN

BEL

GIU

M

IRLA

ND

AR

GEN

TIN

A

SPA

IN

SIN

GA

POR

E

BU

LGA

RIA

BU

LAG

AR

IA

HO

NG

KO

NG

KSA

CH

ILE

GR

EEC

E

KU

WA

IT

POLA

ND

POLA

ND

HU

NG

RY

POR

TUG

AL

MEX

ICO

JOR

DA

N

THA

ILA

ND

BR

AZI

L

VEN

EZU

ELA

EGY

PT

S K

OR

EA

Country

0

5

10

15

20

25

Fata

lity

per

10,0

00 v

ehic

les

Fig.3. Death rates for various developing and developed countries.

V/P x 1000

F\V

x 1

0,00

0

0

10

20

30

40

50

60

0 50 100 150 200 250 300 350

F\V = 0.0003* (V\P)* * -0.795 Actual

Fig.4. Actual and fitted values for relationship between death rate and motorization.

32

YEAR

F\V

x 1

0,00

0

0

10

20

30

40

50

60

1970 1975 1980 1985 1990 1995

F\V = 0.0003*(V\P)**-0.795 Actual

Fig.5 . Actual and fitted values for death rates over years.

V\P x 1000

F\V

x 1

0,00

0

0

10

20

30

40

50

60

0 50 100 150 200 250 300 350

Developed countries

KSA

Developing countries

Fig.6. Smeed’s fitted curves for KSA, developing and developed countries.

33

V\P x 1000

F\V

x 1

0,00

0

0

10

20

30

40

50

60

0 100 200 300 400 500 600 700 800

F\V = 0.00021 x (V\P)**-0.72

KSA

USA

Eg.

UK & Sw.

Braz.

S. Kor.

Bah.

Ven.

Sing.

Jord.Mex.

Gr.

F\V = 0.00039 x (V\P)**-0.64

Kuw.

Fig.7. KSA and other countries with the fitted curves for developing and developed

Year

Odd

s ra

tio

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1972

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

Upper

Low erEst im at ed

Fig.8. Accident severity represented by odds ratio.

34

<18 >=18 >=30 >=40 >=50

Age

0

20

40

60

80

100

Perc

ent o

f dri

vers

Saudi O ther

Nationality

0

20

40

60

80

100

Perc

ent o

f dri

vers

(a) Age factor. (b) Nationality factor.

Married Not married

Marital status

0

20

40

60

80

100

Perc

ent o

f dri

vers

Literate Il l i terate

Education status

0

20

40

60

80

100

Perc

ent o

f dri

vers

(c) Marital-status factor. (d) Education factor.

Yes No

Licience status

0

20

40

60

80

100

Perc

ent o

f dri

vers

(e) Licensee status.

Fig.9. Distributions of accidents by variables related to the driver.

35

Day Night

Time of accident

0

20

40

60

80

100

Perc

ent o

f acc

iden

ts

D a y

0

5

10

15

20

Perc

ent o

f acc

iden

ts

(a) Time occurrence factor. (b) Distribution by day.

Urban Rural

Location of accident

0

20

40

60

80

100

Perc

ent o

f acc

iden

ts

(c) Location factor.

Oth

er v

ehic

le

Fixe

d ob

ject

Pede

stri

an

Ani

mal

Tur

nove

r

Off

-roa

d

Oth

er

Type of accident

0102030405060708090

100

Perc

ent o

f acc

iden

ts

Park

ing

U-T

urn

Ove

rtak

ing

Run

red

ligh

tSp

eed

Alc

ohol

Oth

er

Cause of accident

0

20

40

60

80

100

Perc

ent o

f acc

iden

ts

(d) Accident-type factor. (e) Accident-cause factor.

Fig.10. Accident characteristics (1990-1994).

36

Year

Perc

ent o

f dri

vers

0

10

20

30

40

50

60

70

1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994

Fig.11. Percentages of unlicensed drivers involved in road accidents (1990-1994).