Descriptive statistics are reported for the four levels of severity (fatal, serious, slight, and property damage only), with different variables from the three dataset files (participant, crash, and vehicle files), such as age, nationality, cause, location, time of the crash, road surface, lighting condition, day of the week, and day or night.
Table 5.4 shows the frequency of different levels of crash severity, coded as 1, 2, 3, and 4, for fatal, serious injury, slight injury, and property damage only (PDO) respectively: Table 5-4 Frequency of different levels of crash severity (AH 1425 to 1429)
Severity Category Frequency Percentage
Fatal 2498 0.36
Serious injury 7835 1.12
Slight injury 1127 0.16
PDO 686785 98.36
Total 698245 100
It is noticeable that the vast majority of the crashes were recorded as property damage only (98.36%). In the USA in 2003 the figures were 1% fatal, 11.6% serious injury, 10.5% minor injury, 12.3% possible injury and 64.6% PDO (Eluru and Bhat, 2007). In the UK, figures for injuries were 2% fatal, 15% serious injury and 83% slight injury (1991 – 2003) as UK crash data do not include ‘property damage only’ crashes (Gray et al., 2008). It is therefore clear that the percentage of slight injury crashes recorded in Riyadh city appears to be very low compared with other countries. The low percentage of slight injury crashes recorded in Riyadh city may be due to the following reasons:
- Crashes involving both slight injury to people and damage to property may be recorded as ‘property damage only’ crashes.
- Slight injury crashes may suffer from under-reporting (Al-Katib, 2009).
- The government target is to reduce fatal and serious injury crashes and hence there is less focus on collecting data on slight injury crashes.
- There might actually be a much lower percentage of slight injury crashes. However, this is unlikely as slight injuries are the most common injury outcome.
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In KSA there is a need to register each crash for insurance and repair purposes. Saudi law does not allow vehicle workshops to receive or repair any damaged vehicle without a letter from the Traffic Police Department, according to the Saudi Council of Ministers distinguished decisions numbers 222 and 271 dated AH 25.12.1422, on compulsory insurance on the vehicle and the need for a repair paper. Therefore, all ‘property damage only’ crashes will be reported. The traffic safety strategy in Riyadh for road crashes concentrates on fatal and serious injury crashes, which take the highest priority when reported in the annual published statistical reports. Since the crash data are heavily biased towards ‘property damage only’ crashes, the inclusion of this category of crashes may influence the analysis. Therefore, ‘property damage only’ crashes are not considered in this research. The total number of injury crashes over the five years is 12,039.
A comparison between neighbouring countries and Riyadh on the numbers of crashes with different levels of severity was also made. Then, a t-test was used to compare the two sets of data for validation purposes. The t-test allowed us to determine a p-value (probability value) that shows the possibility that these results could occur by chance, or to decide whether we have enough evidence to reject the null hypothesis and say our research hypothesis is supported by the data.
A comparison between Bahrain, which is one of the Gulf Cooperation Countries (GCC), and Riyadh on the numbers of crashes with different levels of severity in the year AH 1429 is shown in Table 5.5 below:
Table 5-5 A comparison between Riyadh and Bahrain on number of crashes for the year 1429AH
Severity Riyadh Percentage Bahrain Percentage
Fatal 320 0.25 75 0.10
Serious injury 1026 0.82 522 0.69
Slight injury 51 0.04 1446 1.91
Damages 124852 98.89 73538 97.30
(Reference: Bahrain General Directorate of Traffic and Licensing - Ministry of the Interior) http://www.traffic.gov.bh/arabic/index.asp
The Kingdom of Bahrain was chosen for comparison because it is similar to Riyadh in area and shares a similar culture and style of life. From the above table there is a noticeable difference in the number of slight injury crashes between Riyadh and Bahrain
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which could be arguable knowing that the population density of Riyadh city is about twice that of Bahrain (according to: www.wikipedia.org). This difference can be associated to the under-reporting problem, or the HCDR has decided to not count the slight injury crashes and rather consider them as PDO crashes. While in Bahrain these types of crash injuries are taken more seriously.
In addition, damage and slight injury crashes were recorded for the purpose of estimating the costs resulting from these crashes to the national economy of the Kingdom of Saudi Arabia and were not included in the traffic safety strategy. The traffic safety strategy in Riyadh for road crashes concentrated on the fatal and serious injury crashes, which received the highest priority and the most concern when reported in the annual published statistical reports.
It should be noted that the observation in severity analysis is the crash rather than the participants involved in the crash. This makes it difficult to obtain data related to age and nationality of driver (or other participant) involved in the crash. To address this issue, data should be obtained on the age and nationality of participants who have 100% of the blame (are wholly at fault) for the crash. Data suggest that participants with 100% of the blame are mostly drivers. This would, however, reduce the number of observations.
The review of literature indicates that two common factors affecting the severity of traffic crashes are the age and nationality of the drivers (at fault) involved in the crashes. The datasets supplied by the HCDR do not implicitly identify whether a driver is at fault or not for the crashes, and therefore it was not straightforward to distinguish crashes with drivers at fault. However, the participant data file contains information on the distribution of blame attributed to drivers (0%, 25%, 50%, 75% and 100%) involved in a crash. The crash data analysed in this thesis were created by extracting cases where a driver was allocated 100% of the blame for the crash. The sample with 100% of the blame was used because there will be a single value for age and nationality for each driver. The number of such crashes is 3,648.
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Based on the literature review (see Chapter 2) the functional relationship between the severity of a traffic crash and its contributing factors can be expressed as:
The severity of a crash = f (age, nationality, time of the crash, cause of the crash type of collision, location of the crash, road surface, lighting condition, weather condition, number of vehicles, crash year, and number of casualties). Among these contributory factors, gender will not be included as females are not allowed to drive according to the Saudi law.
The most widely used measure of exposure is the number of kilometres travelled for each travel mode. Additional useful insight can be is provided by taking into account the speed of travel, in which case exposure is expressed as the amount of time spent in the traffic system. One of the developments in recent years has been the installation of electronic and telecommunication equipment inside vehicles and along roads. Another development is the increasingly widespread use of mobile telephone data. As a result it is becoming easier to collect up-to-date and reliable information on a variety of parameters that could be of importance in the calculation of vehicle exposure and risk. Additional information on the distribution of speeds, types of vehicles and following distances also seems to be a future possibility to measure aspects of exposure. In many road safety analyses, different exposure measures are used, according to data availability and quality, as well as the particular objective of the analysis. These measures may vary significantly in terms of the potential level of desegregation and the possible underlying bias in their estimates. No general rule is available concerning the preferred measures of exposure. Vehicle- and person kilometres of travel, as well as the time spent in traffic, are conceptually closer to the theoretical definition of exposure and can be theoretically available to a satisfactory level of detail. In this particular research the dataset used didn’t contain the parameters described above to measure exposure rates (such as traffic volume, travelled distances, fuel consumption or driver’s mobile phone movement data) which lead to omission of this factor from the study.
In the frequency analysis the full sample of the crash dataset is used. However, the dataset to be used in the severity analysis contains only those drivers who were 100% to blame for the crash based on information in the participants file from 573,206 cases. The crash data contains personal data for all drivers. In order to allow for age and
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nationality in the analysis it is necessary to have data for one driver only. Therefore, this analysis is based on cases where one driver was 100% to blame for the crash. Three variables will be used from the participant file as follows: age, nationality, and percentage of blame. Each variable will be used in the following manner: The nationality will be either Saudi or non-Saudi and the age of the driver is classified into one of five age groups.
Table 5-6 Crashes by age group and level of severity
Age group Severity 13-17 18-24 25-39 40-64 65+ Fatal 60 342 374 166 18 Serious injury 171 946 1,204 398 29 Slight injury 11 48 64 22 4 PDO 37 355 602 219 4 Total 279 1,691 2,244 802 55 Percentage 5.5 33.35 44.25 15.82 1.08
The legal driving age in Saudi is eighteen years but as shown in Table 5.6 the under-age drivers represent 5.5% of the total number of crashes.
The above table, with data on drivers with 100% of the blame, shows that lower age groups and especially group two (25-40) are involved in a high number of crashes at all levels of severity compared to the other age groups. According to HCDR, in the latest census, made in October 2004, the population of Riyadh was 4,260,192; 66% of the population are Saudis and 34% of the population are Non-Saudis. According to HCDR, 40% of the Saudis in Riyadh are below 15 years of age, while the figure is only 23% for the non-Saudis because they come to Saudi to work, which means they should be within the working age. The tabulated values for age group with nationality are given below in Table 5.7.
As noted in Table 5.7, the non-Saudis have more crashes than the Saudis in the age groups 25-39 and 40-64 while Saudis have many more crashes between the ages of 14 and 24. In addition, the average age among the Saudis in Riyadh is 18 years while it is 30 years for the non-Saudis, and the percentage of males among the Saudis is 53% while it is 63% for the non-Saudis, which are normal because the most non-Saudis who are employed as drivers are males.
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Table 5-7 Crashes by age group and nationality only for those with 100% of the blame Nationality
Age group Saudi Non-Saudi
14-24 1,480 215 25-39 1,076 1,170 40-64 304 502 65+ 44 11 Total 2,904 1,898 Percentage 60.48 39.52
Generally, the percentage of Saudis in all age groups who are involved in crashes is more than the percentage of non-Saudis.