ANALYSIS OF THE TRENDS IN ACCIDENT RATES IN SRI LANKA

Transcription

1 ANALYSIS OF THE TRENDS IN ACCIDENT RATES IN SRI LANKA Amal S. Kumarage 1, Cammilus R. Abeygoonawardena 2 and Ravindra Wijesundera 3 ABSTRACT INTRODUCTION In Sri Lanka, both the vehicle population as well as the number of accidents have been steadily increasing. There are growing concerns regarding the social and economic implications of the constantly increasing number of traffic accidents and fatalities in particular. The attempts made to improve road designs, vehicle inspections and road user education are increasingly received with public skepticism and ridicule as traffic accident statistics do not appear to indicate any improvement worthy of the efforts. OBJECTIVES This paper investigates the historic trends in traffic accidents in Sri Lanka from 1977 to It uses data from Police accident records, vehicle registration data, estimates of active vehicle population and vehicle kms operated as well as key socioeconomic indicators such as population, urbanization which have an impact on accident rates. METHOD The trends are computed in terms of accident and traffic fatality rates per 10,000 population; 10,000 operational vehicles; per billion passenger kms and billion vehicle kms operated. The analysis further investigates the road user vulnerability between motorized and non-motorized users. It also derives comparative accident rates for operators of different vehicles such as buses, trucks, taxis, cars, 3-wheelers, motor cycles, pedal cyclists etc. RESULTS The trends show that while the number of accidents still continues to increase, the accident rate including the accident fatality rate in most cases have been reversed. This implies that the rate of increase in accidents have been reduced. It also identifies the risk to different categories of road users. CONCLUSIONS The paper concludes with hypothesis for the observations by referring to improvements that have been introduced over the period of analysis. These include regulatory, safety education and enforcement as well as road design improvements. 1 Dr. Amal S. Kumarage, Senior Lecturer, Dept. of Civil Engineering, University of Moratuwa, Sri Lanka. amal@civil.mrt.ac.lk 2 Mr. Camillus R. Abeygoonawardena, Deputy Inspector General (Traffic), Sri Lanka Police, Colombo, Sri Lanka. 3 Mr. Ravindra Wijesundera, M.Phil. student in Transportation Engineering at the Department of Civil Engineering, University of Moratuwa. 94 th Annual Sessions, Institution of Engineers, Sri Lanka Page - 1

2 INTRODUCTION Road Traffic Accidents are a matter of concern in Sri Lanka as it is in all countries that have experienced a growth in motorization. While road safety reports and guidelines have shown the relative placement of Sri Lanka in terms of accident statistics, this paper develops these statistics further. It also analyses the trends observable through these statistics. DATA AND STATISTICS The data used in this analysis has been collected from a number of different sources. The Sri Lanka Police has provided the accident data (Traffic Police Sri Lanka, 1997). The vehicle and passenger kms have been computed from the Transport database at the University of Moratuwa (UoM, 1999). Comparisons with international data have been made by reference to recent publications (OECD, 1999). ANALYSIS OF ACCIDENT TRENDS Accidents can be analysed using a number of different statistics. These include the analysis of the absolute number of accidents, fatalities etc. as an unadjusted indicator. Measures of risk are very important parameters in explaining the road safety situation in a country as they enable us to compare different countries and to observe the development of road safety situation. Such measures if available on a time series are especially useful in assessing the impact of road safety improvement programs. Any such measure should calculate a risk factor. A risk in this instance may be defined as the ratio between some measure of the safety problem (e.g. number of accidents, fatalities and injuries) and some measure of the exposure (e.g. vehicle fleet, population, vehicle kms and person kms) to the risk. In order to generate different measures of risk, this paper will investigate accident trends in Sri Lanka with the aid of the following statistics. a) Annual Accidents Reported- refers to the actual number of accidents for a given year reported to the police and recorded under different categories. However, it has been found that the number of accidents reported is significantly lesser than the actual number of accidents (Kumarage, 1992). Hence, although this statistics is widely used in Police and other data publications, it alone is clearly inadequate. The same report does however indicate that fatal accidents reported are a more accurate measure. b) Fatalities per 10,000 Registered Vehicles- refers to the total number of fatalities in road accidents for a given year divided by the number of vehicles on register at end of that year (with the Department of Motor Traffic), multiplied by 10,000. According to definitions adopted by Sri Lanka, only the victims succumbing to their injuries within 30 days of an accident are considered as accident fatalities. One of the main drawbacks of using registered vehicles, as a measure of exposure is that the Department of Motor Vehicles does not adjust sufficiently for the number of vehicles scrapped when reporting the registered vehicle fleet. But this definition is retained for the analysis as most of the developed countries report this figure correctly based on annual licensing records. 94 th Annual Sessions, Institution of Engineers, Sri Lanka Page - 2

3 c) Fatalities per 10,000 Operational Vehicles- refers to the total number of fatalities in road accidents for a given year divided by the number of operational vehicles at the end of that year, multiplied by 10,000. This indicator highlights the severity of the road accident problem in a country. The estimation of operational vehicle fleet is based on a study conducted by University of Moratuwa (1992). This research has established a relationship of scrappage of vehicles with time and the age of vehicles. The following model was developed to estimate the survival rate for vehicles after n years. Box 1: 1 if x <= n yrs Y n = Exp -α(x-n) if x>=n yrs Where Y n is the survival rate after x years and α and n are calibrated coefficients for each vehicle types. d) Fatalities per 100,000 Population- refers to the total number of fatalities in road accidents for a given year divided by the population estimated by the Department of Census and Statistics for that year, multiplied by 100,000. This may be interpreted as the risk for the population of a country due to road accidents. This is a static measure of risk. e) Fatalities per 1,000,000,000 Vehicle kms Travelled - refers to the number of fatalities among road users divided by estimated vehicle kms for that year. The annual vehicle kms were calculated using a model developed by University of Moratuwa (1992) taking into account the vehicle classification, fuel consumption and economic growth of the country. The following model was used to estimate the annual vehicle kms. Box 2: Z n = C o exp(-βn) Where Z n is the estimated annual vehicle kms by a vehicle of age n years and C o and β are coefficients calibrated for each vehicle type in Sri Lanka. In estimating the bicycle kms, the modal share of bicycles in traffic surveys on different roads have been used as a control variable for estimation purposes. Weighted averages have been used in calculating overall cycle kms, However, since no mathematical models have been calibrated for this purpose, estimates for bicycle use in this analysis are less reliable than for motorised travel. f) Fatalities per 1,000,000,000 (Billion) Passenger kms Travelled- refers to the number of fatalities among vehicle users divided by the estimated passenger kms travelled for that year. This indicates the risk for people in mobility (when actually travelling). Passenger 94 th Annual Sessions, Institution of Engineers, Sri Lanka Page - 3

4 kms were estimated using vehicle kms and average occupancy data for each vehicle category using the TransPlan database (University of Moratuwa, 1999). g) Fatality Index- refers to the percentage of fatalities among all casualties due to road accidents. This index is very useful for identifying quality of country s health and emergency services because better the above services, more is the survival chances of accident victims. It may also be an indicator of the degree of protection in vehicle design, and also where the severity of accident injury may be reduced by the use of safety accessories such as seat belts and safety helmets. CALCULATION OF RISK FACTORS Following the process mentioned above several risk factors have been derived. These have been discussed under the respective parameter measuring the exposure levels. Accidents in Absolute Numbers Accidents and the resulting casualties as well as fatalities have grown in absolute numbers in Sri Lanka (Sri Lanka Traffic Police, 1997), as has been the case in almost all developing countries (ADB, 1996). But then, growth is experienced in most areas of society and the economy. Figure 1 clearly shows the trend of increase in accidents and accident fatalities when plotted to a base index of 100 for the year The comparative increases in population, vehicle fleet and mobility are also shown in this figure. The latter is shown in terms of the growth in passenger kms and vehicle kms. The trends show that population growth is the lowest among these, while the growth of the vehicle fleet is the highest, followed by the increase in vehicle kms operated. Passenger kms, fatalities and accidents appear to have increased at a lower but near equal rate. Accordingly, the average annual growth rates (AAGR) for this period could be estimated. This is given in Table 1. Table 1: Rates of Growth in Accidents and Related Characteristics ( ) AAGR (%) Population 1.3 Operational Vehicle Fleet 8.7 Vehicle Trips 6.8 Passenger Trips 4.3 Accidents Reported 4.3 Fatalities Reported 3.6 The comparative rates of growth indicate that vehicle fleet is growing at six to seven times the population growth. Overall mobility in terms of vehicle trips is increasing at five fold of population, while passenger trips is increasing at around three to four times. Accidents too are increasing at this rate, while fatalities reported are increasing at two to three times the increase in population. Rapid increase in vehicle population as shown by Table 1, has put considerable pressure on the road network and its traffic control system most of which were never designed for the - 94 th Annual Sessions, Institution of Engineers, Sri Lanka Page - 4

5 Figure 1 Trends in Growth Rates (1980=100) Growth Rate (1980=100) Oper. Veh Veh. km Accidents Passenge Fatality Population th Annual Sessions, Institution of Engineers, Sri Lanka Page - 5

6 - traffic flows now using them. One of the main reasons for the rapid growth of vehicle population is that with the economic growth, two and three wheeler motor vehicles have become more affordable. These as will be shown later are high-risk vehicles. It should be noted that motor cycles, which were introduced to Sri Lanka in the 80 s, presently account for 45% of vehicle population. Fatality Risk with Increasing Vehicles When the vehicle fleet in a given country increases, it is expected that the accident level will also increase correspondingly (ADB, 1996). One statistic that has been used to measure fatalities in traffic accidents as a function of vehicle ownership has been to compute a fatality rate (or risk) in terms of fatalities per 10,000 vehicles. This calculates the increase of risk with increase in the exposure level. That is if more vehicles are introduced to our roads, what would be the corresponding increase to the fatality risks. Many countries compile this statistic based on the registered fleet of vehicles. However in Sri Lanka, registered is referred to as the historical fleet of vehicles on register. The active vehicle on register at any time is not known. In order to overcome this problem, more recent calculations are based on licensed or operational vehicles, which is more accurate as this refers to the vehicle that are active and have renewed their annual license. Figure 2, shows the trends in fatality rate per 10,000 vehicles both in terms of the operational fleet and the registered fleet. 60 Figure 2 Road Accident Rate per 10,000 Vehicles in Sri Lanka ( ) Operational Registered The registered vehicles are included purely for comparison. This rate shows a decreasing trend during the period under review. This observation indicates that the contribution to the total fatality rate caused by the introduction of an additional vehicle on to the vehicle fleet (and the road network) is decreasing with the increasing number of total vehicles already in 94 th Annual Sessions, Institution of Engineers, Sri Lanka Page - 6

7 the fleet. However, the rate of decrease has slowed down in the last decade with a slight increase recorded in recent years. This shows a possible inadequacy in the capacities of the infrastructure and services required for maintaining road safety. Further analysis in this respect is beyond the scope of this paper. Fatality Risk with Increasing Population Even though, trends show the risk level to reduce with an increasing vehicle fleet, it means nothing to people (not vehicles) who are the victims we are concerned with. Thus we should ascertain the risk factor as an exposure to the population level. In this respect, fatality rates are computed as a ratio of 100,000 population. This statistic for the period under review is shown in Figure 3. It clearly shows a steadily increasing trend. This means that the probability of succumbing to a road accident has nearly doubled during the period of review. By a simple comparison of road accident fatalities with total deaths recorded in Sri Lanka in 1997 (Statistical Abstracts, Department of Census and Statistics), it transpires that 1 in 60 deaths in Sri Lanka occur due to a road accident. In 1977 this ratio was 1 in 127 deaths. It should be noted that in developed countries, the probability of death due to road traffic accident is even higher recording 1 in 25 deaths (WHO, 1999). Fatality Risk by Different Road Use It is important to determine if this increase in the risk affects all road user categories equally or otherwise. Figure 3, shows separately the fatality rates of pedestrians and vehicle users per 100,000 population. Vehicle users are namely occupants of vehicles including passengers, drivers and/or crew. It is clearly seen from the trends that the risk is seen to increase for vehicle users (i.e. motorists) rather than for pedestrians. The fatality rate for pedestrians too has increased by around 10% over the study period. But this is marginal when compared to the increase of nearly 200% for vehicle users. Thus it can be concluded that while the fatality rate among pedestrians indicates that safety has deteriorated marginally for them 4, the most significant increase in accidents is observable among those using vehicles. This of course is mostly due to the increasing vehicle use by the population. 4 This does assume that average pedestrian activity has not reduced with motorization observed during this period. While there are no studies to adjust for this, if it has deteriorated it would mean that the risk level to pedestrian is actually higher than shown in Figure th Annual Sessions, Institution of Engineers, Sri Lanka Page - 7

8 Figure 3 Road Accident Fatalities per Population in Sri Lanka by User Type ( ) all users veh. user pedestrians Fatality Risk with Increasing Personal Mobility Another proposition therefore, is to investigate the relationship of accidents with an index of increasing personal mobility. Mobility could be measured in terms of passenger kms or vehicle kms. The former maybe a suitable indicator for vehicle user fatalities, while for pedestrians and drivers of vehicles, the latter may be considered as more appropriate. Figure 4 shows that the based on passenger kms travelled has a reducing trend except for a sharp increase in the last three years. The overall trend indicates that the fatalities incurred in providing mobility have decreased from 33 deaths to around 25 deaths per billion passenger kms travelled. Figure 4 Road Accident Fatalities per Billion Passenger kms Carried in Sri Lanka ( ) th Annual Sessions, Institution of Engineers, Sri Lanka Page - 8

9 A further analysis of the fatality rate among different vehicle users is given as Figure 5. The 225 Figure 5 Road Accident s (per billion pax km) for Sri Lanka by User Type ( ) Ped Cyc. MC Rider OtherVeh User results show that the fatality rate is highest among pedal cyclist, followed by motor cyclist. The lowest fatality rate is for other motorized vehicle users. According to the trends, the relative safety levels have remained unchanged over the study period. This means that the probability or risk of being killed riding a pedal cycle is approximately ten times 5 higher than travelling in a motor vehicle, other than a motor cycle, where it is five times higher. Fatality Risk for Bus Passengers Buses carry nearly 70% of the passenger trips in Sri Lanka (University of Moratuwa, 1999). The safety in bus travel is therefore quite important to the overall improvements to road safety. Figure 6 shows the fatality trends observed in both the State owned and privately operated buses. It is observed that bus travel, which had a very low fatality rate for passengers at around 2 deaths per billion passenger kms increased by 50% to 3 in just six years following the decentralisation of the State owned bus operations. But the fatality rate has gradually decreased since then and now stands at one death per billion-passenger kms. At the same instance, private buses, which started with an even better safety record than the State owned services quickly overtook them within the first five years of operation. It reached a high of 4 deaths per billion passenger kms, before reducing gradually in the last ten years. But is still is less safe compared to the State owned bus services, having a risk factor nearly three times higher than the State operations. 5 As discussed previously the estimate of bicycle kms used for this analysis has a lower reliability than the estimates used for motorised vehicles. 94 th Annual Sessions, Institution of Engineers, Sri Lanka Page - 9

10 Figure 6 Bus Passenger Fatalities per Billion Passenger kms in Sri Lanka ( ) Private State However, it must be stated that bus passengers even at the worst of times have enjoyed a level of safety much higher than any other mode of road transport. For example, travel by car or van appears to be around ten times riskier than undertaking the same journey by bus. Travel by motor cycle it is over 50 times riskier than bus! Fatality Risk with Increasing Vehicle Use The fatality rate of different road users when analysed with increasing vehicle use shows that as expected, the risk level for drivers has remained unchanged for every km of vehicle use. This implies that driver safety in spite of vehicle and road design improvements and user education has not improved in Sri Lanka. Figure 7 also shows the relative risk factors for different road users with the increasing fleet of vehicles (exposure level). The decreasing pedestrian fatality rate has now been overtaken by the increasing passenger fatality rate. The trend clearly suggests that while driver fatality rates may be expected to remain constant, the passenger rates are likely to increase. 94 th Annual Sessions, Institution of Engineers, Sri Lanka Page - 10

11 Figure 7 Road Accident s per Billion Vehicle kms in Sri Lanka by User Categories ( ) Pedestrian Passenger Driver Fatality Risk as a Percentage of Casualties A more recent addition to the array of accident statistics used internationally, has been the Fatality Index, which is computed as a percentage of fatalities to total road accident casualties. This is given in Figure 8 and indicates periods of increase as well as periods of decrease. However, there is an overall increase in the fatality index from 7.8% of casualties in 1980 to 9.7% in The largest peak at 11.6% coincides with the rapid popularisation of motor cycles in Sri Lanka. Figure 8 Variations in Road Accident Fatality Index for Sri Lanka ( ) Fatality Index (%) th Annual Sessions, Institution of Engineers, Sri Lanka Page - 11

12 COMPARISONS WITH OTHER COUNTRIES There is constant comparison of accident statistics between countries. The Smeed equation (Smeed, 1968) used even today, draws attention to the relationship that the accident rate is largely dependent on increasing vehicle ownership (rather than numbers of vehicles) levels. This is given in the following equation. Box 3: F/V = A (V/P)^B Where F = Number of fatalities per year V = Number of motor vehicles P = Population A and B = Regression constants As shown in Figure 10, this is re-enforced when Sri Lanka s fatality rates are plotted against a few selected countries. It is clear that when vehicle ownership usually measured in vehicles per 100 (or 1000) population increases, the fatality rate measured as a proportion of population also increases. This is because the increase in vehicle ownership results in (a) an increase in mobility due to increase in incomes and (b) a shift from safer modes of public transport to more accident prone modes such as cycles, motorcycles, cars and vans. Figure 10 s by Vehicle Ownership (1993) India Pakistan Sri Lanka Sri Lanka India Pakistan Hong Kong Fuji Fiji Hong Kong Malaysia Malaysia Vehicle Ownership per 100 Population Fatalities Per 10,000 reg. veh. Fatalities Per 100,000 pop. On the other hand, increasing vehicle ownership also indicates a reducing risk when measured with respect to vehicles registered (or operated). This is to be understood on the basis that as the exposure levels increase with increasing vehicle ownership among the persons of any country, its familiarisation also increases. Consequently, as seen in the Sri Lankan trends, the risk factor, particularly through pedestrian related accidents can be expected to reduce. CONCLUSIONS 94 th Annual Sessions, Institution of Engineers, Sri Lanka Page - 12

13 The number of road accidents reported in Sri Lanka has been steadily increasing at over 4.3% per annum for the last 20 years. Among these are many accident fatalities, which are also increasing at 3.6% per annum. This increase can be best understood in relation to a number of features such as; Increasing population; Increasing vehicle ownership rate (where vehicle fleet is growing much faster than the population); The subsequent shift from safer modes of public transport to less safer private transport modes; The decentralization of bus operations and the subsequent lowering of safety standards especially among private bus operators and The increasing mobility of Sri Lankans due to increasing incomes. When calculating accident statistics with vehicle ownership rates, it compares well with the experiences of many other countries from both the developed and developing world. Trends in accident fatality rates observed over the last 20 years in Sri Lanka corroborates the fact that as vehicle ownership levels increase, user induced risk factors also increase, while non-user related risk factors reduce. REFERENCES: Asian Development Bank, (1997), Road Safety Guidelines for the Asian and Pacific Region, Manila, Philippines. Kumarage A.S. and N. Wijesuriya (1992), Safety in Mobility: The Sri Lanka Record, Annual Sessions Chartered Institute of Transport, Colombo. Kumarage A.S., (1998), Update of Accident Rates in Sri Lanka, University of Moratuwa. Kumarage, A.S., (1997). Estimation of Operational Vehicle Fleet 1996 Update, University of Moratuwa, Sri Lanka. OECD, (1999), International Road Traffic and Accident Database, Organization for Economic Co-operation and Development, Paris, France. Smeed, R.J., (1968), Variation in Pattern of Accident of Accident Rates in Different Countries and their Causes. Traffic Engineering and Control, 14, 432. Traffic Police, (1997), Accident Statistics Sri Lanka. Transport Studies and Planning Centre, (1996), Transport Statistics, Ministry of Transport & Highways, Sri Lanka. University of Moratuwa, (1999), Transport Statistics Database, Sri Lanka. World Health Organisation, (1999), Injury: A Leading Cause of the Global Burden of Disease, Geneva, Switzerland. 94 th Annual Sessions, Institution of Engineers, Sri Lanka Page - 13