Background: Traffic accidents rank fifth among the leading cause of deaths in Malaysia. The country is burdened with more than ten billion ringgit of losses due to traffic accidents every year. Despite implementation of various intervention measures over the years, the number of traffic accidents continues to rise. For instance, the number of traffic accidents in the year 2007 was approximately twice the number of accidents recorded in 1997.
Objectives: The aim of this paper is to provide an initial understanding of the crash exposure pertaining to the mobility level in various states of Malaysia. It is of interest to explore the relationship of the exposure pattern and crash risk before planning effective countermeasures. Method: Travelling information based on odometer reading was obtained through Postcard Survey. 40,000 postcards were sent randomly to new vehicle owners registered with the Road Transport Department. Results: A total of 6,681 motorists responded to the survey. From their odometer readings, it was noted that males travelled 99.06 billion km while their female counterparts travelled only 58.69 billion km. The results also indicated that male drivers were nearly three times more at risk of being involved in road accidents as compared to female drivers. Significance: The findings are very useful to the relevant authorities as intervention countermeasures in relation to the different characteristics and demographics of the states can be designed. The results also serve as a reference point for state decision makers to adjust their countermeasures for the betterment of road safety. Keywords: Exposure; Survey; Risk
Malaysia shares similar profiles of crash patterns with other developing
countries in the world in the past decade. The tremendous increase of motorised vehicles on the roads has invariably led to significant rise in the number of traffic accidents. The number of traffic accidents in 2007 almost doubled occurred in 1997. as compared to the number of traffic accidents that
Sixty percent of total fatalities reported over the years involved motorcyclists. This high accident rate has led to road accidents being the 5th leading cause of death in Malaysia (Department of Statistics, 2008) and caused 9.3 billion ringgit of losses to the country in the year 2003 (ADB-ASEAN, 2003) . In the list of world rankings, Malaysia is ranked 46th of 172 countries with regards to occurrence of deaths in registered vehicles due to road accients (WHO, 2009). Figure 1 shows the rate of occurrence of accidents between 2001 and 2010.
Figure 1 Accident Records from 2001 to 2010
Many road safety studies have led to the convergence that a measure of risk exposure is important for a comprehensive analysis of causal factors (Joly et al., 1993). By definition, “exposure to risk” means the vulnerability of a driver or a system that may lead to an accident (Chapman, 1973).
Factors of exposure can be the mileage driven, the number of trips, the number of registered vehicles, fuel consumption or the number of driver hours. Risk on the other hand, is the ratio of accidents over the exposure parameters.
Exposure analysis has been widely used to explain the variation or to rationalise how a certain group or person may be exposed to a higher risk of accidents than others. One of the the more common parameters is the number of kilometres travelled (KT). People argue that the risk of accidents rises with the amount of travelperformed. Studies by Janke (1991) and Maycock (1997) showed that while distance driven increased linearly with the risk of road accidents, it was not the case for those drivers who clocked lower mileage. Drivers who drove shorter distances but who travelled on busy roads
even at lower speeds were exposed to just as many traffic conflicts which could consequently increase their risk of accidents. Chu (2003) in his study concludes that merely comparing the risk of accidents with exposure to driving over long distances can be over or under representing when the differences in travel speed and environmental factors were not taken in consideration. Thus, there are many other influencing factors, but vehicle kilometre travelled (VKT), an indicator relating to the number of vehicles and total distance travelled, is one of the leading factors influencing the road safety performance within Malaysia or neighbouring regions.
The aim of this paper is to provide an initial understanding of the crash exposure pertaining to the mobility level in the various states of Malaysia. It is of interest to explore the relationship of the exposure patterns and crash risks before planning effective countermeasures.
In Malaysia, the number of accidents and deaths in 2007 was extracted from the MIROS Road Accident Analysis and Database System (M-ROADS) which was compiled from the original data kept by the Royal Police of Malaysia (RPM). The data regarding the registered vehicles and motorists in Malaysia were obtained from the Road Transportation Department Malaysia (RTD). The Population information for each state in Malaysia was obtained from the Department of Statistics Malaysia. All the secondary data were then used to estimate the death per 100,000 populations and death per 10,000 vehicles.
Information on travel based on odometer readings was obtained from the Postcard Survey conducted in 2007 and has been reported elsewhere (Nurulhuda, 2010) but briefly described as follows:
The sampling in this study is random sampling, stratified by type of registered vehicle within the states of Malaysia. Forty thousand postcards were sent to new vehicle owners and 6681 respondents completed the questionnaire.
The Postcard Survey had 4 questions: purpose of travel , income, odometer reading and date odometer reading was taken. The personal information of the driver (age, gender, etc.) and vehicle information (type of vehicle, engine size, etc.) was obtain from the JPJ Database. Figure 2 shows a sample of the filled Postcard returned to the researcher. Estimates of Average Annual Kilometers Travelled (AAKT) were classified by state and type of vehicle.
Figure 2 Example of Postcard Survey returned
Table 1 shows the number of fatalities by state in Malaysia and its associated fatality rate. A total of 6282 people were killed in road accidents in the year 2007. Selangor and Johor recorded the highest number of fatalities with 16% each. Perlis reported the least number of fatalities with 41 deaths.
Table 1: Fatalities and Death among vehicles registered with RTD in year 2007 State Perlis Kedah Pulau Pinang Perak Selangor WP KL Negeri Sembilan Melaka Johor Pahang Terengganu Kelantan Sabah Sarawak TOTAL Fatalities 41 492 376 811 1025 234 320 227 1023 437 374 290 316 316 6282 Death per 100,000 population 17.7 25.6 24.8 35.0 20.7 14.6 32.7 30.7 31.6 29.5 35.0 18.6 10.3 13.1 22.8 Death per 10,000 vehicles registered 6.20 5.84 2.10 5.21 5.24 0.62 4.74 3.98 4.39 6.54 10.10 5.47 4.70 3.04 3.73
When the population and number of new vehicles registered were considered, the results show that the highest fatality rate per 100,000 population was reported in Perak and Terengganu, with both recording 35.0 deaths per 100,000 population. Sabah ranked ninth among the states, with 4.7 deaths per every 10,000 vehicles registered. It is interesting to note here that the use of a different denominator yields a different perspective of road safety.
The comparison of exposure to risk of accidents also took into account the amount of motor traffic, land use and associated traffic conditions in each state. (IRTAD, 2010). On the other hand, in the year 2007, for every 10,000
vehicles registered in Terengganu there were 10.1 fatalities reported. The greater risk of road accidents among road users in Terengganu requires serious attention from the relevant parties.
Table 2 shows the total population, registered number of vehicles, accident data, vehicle kilometres travelled (VKT) by state in Malaysia for year 2007. Al-Haji (2005), defines the population size, number of vehicles, and VKT as indicators of exposure to risk of accidents. VKT is a more accurate exposure measure than population or number of vehicles because it is also linkd to the differences in socio-economic conditions in each state.
Motorcars nationwide clocked 247,045 km in the year 2007, while motorcycles clocked 25 percent less in vehicle kilometres travelled.Selangor reported the highest AAKT for motorcycles while Negeri Sembilan had the highest record of AAKT for motorcars.
Table 2: Total population, number of registered vehicles, and Accident data by State for year 2007 Population (‘000) 231.9 1918.7 1518.5 2314.6 4961.6 1604.4 978.2 738.8 3,240.9 1483.6 1067.9 1560.5 3063.6 2404.2 27087.4 Registered Vehicles Motorcars 13,502 212,866 728,493 510,013 869,169 2,271,722 236,300 218,568 953,439 247,491 123,193 182,768 379,878 472,241 7,419,643 Motorcycles 49,225 572,614 979,853 948,255 886,970 1,108,324 389,453 320,657 1,205,058 368,294 220,222 312,293 134,129 448,017 7,943,364 Accidents AAKT Motorcars 15008 17661 15857 18144 19135 19228 21322 18924 17003 18033 19344 16524 14938 15926 247045 Motorcycles 11626 14323 14234 12902 15637 14066 13924 12957 13798 13196 12989 12074 12340 10469 184534 Motorcars (In Billion) 202,634,047 3,759,459,781 11,551,861,268 9,253,639,738 16,631,402,097 43,681,185,702 5,038,475,520 4,136,232,397 16,211,145,110 4,462,690,665 2,382,994,003 3,019,990,257 5,674,458,001 7,520,858,755 VKT Motorcycles (In Billion) 572,271,266 8,201,469,535 13,946,948,551 12,234,471,808 13,869,290,422 15,589,979,983 5,422,705,095 4,154,713,743 16,627,083,780 4,860,167,228 2,860,469,727 3,770,619,900 1,655,096,320 4,690,149,830
Perlis Kedah Pulau Pinang Perak Selangor WP KL Negeri Sembilan Melaka Johor Pahang Terengganu Kelantan Sabah Sarawak TOTAL
1,364 16,172 33,881 29,203 99,157 49,454 16,079 11,720 46,584 13,982 8,155 8,116 15,196 14,256 363,319
As of year 2007, there were 6.2 million active male drivers and 3.8 million active female drivers registered with RTD (see Table 3). “Active drivers” here refers to those with valid terms of license during the course of this survey. Based on Table 3, it was noted that on average there is not much difference between female and male drivers in their annual average distance travelled. In terms of VKT, female drivers recorded 58.69 billion vehicle kilometres travelled, which was 40% lower as compared to their male counterparts. Translating the deaths recorded into VKT, it was estimated that male drivers were nearly 3 times more at risk than female drivers.
Table 3: Crash rate (fatality) and exposure data disaggregated by gender Active Drivers 6,168,238 3,804,872 Driver km (billion) 99.06 58.69 Risk (per billion driver km) 53.1 17.5
Further analysis on the risk of motorcyclists being involved in a traffic accident was also conducted to check the safety performance of motorcyclists as compared to drivers of motorcars in Malaysia.
DISCUSSION AND CONCLUSION
The objective of this paper is to shed some light on road safety performance in the country. The results showed that the absolute number of accidents required exposure data to evaluate the road safety performance. For instance, the fatalities records in Terengganu were 374 deaths but when the population and number of vehicles registered were considered, the risks tended to increase.
The kilometres travelled is the estimate of exposure identified in the study and obtained from odometer survey via postcard method. It should be noted that it was based on representative sample and influenced by certain degree of bias.
The results in this paper are not free from limitation and argument. The data presented in this study can be classified into two categories: primary data and secondary data. The primary data were gathered from the interview survey where the initial targets were motorcyclists and car drivers. The decision to focus on these two groups was due to the fact that they were overrepresented either in the accident data or the vehicle population. However, problems were encountered during the extrapolation of secondary data sourced from RTD and the traffic police database.
The authors acknowledge their shortcomings, while due effort was put into refining the findings. Therefore, the trade-off in the richness of data should be interpreted with care. At this stage, it does not fully depict the picture of exposure and risk patterns of the population in the country. Nevertheless, the authors believed that this paper has introduced the exposure and risk elements in explaining road safety from another perspective.
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