Ali S Al-Ghamdi

King Saud University, Riyadh, Mintaqat ar Riyad, Saudi Arabia

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Publications (9)13.21 Total impact

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    Ali S Al-Ghamdi
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    ABSTRACT: Highway safety is a major concern to the public and to transportation professionals, so the number of crashes caused by poor visibility due to fog form an alarming statistic. Drivers respond to poor visibility conditions in different ways: some slow down; others do not. Many drivers simply follow the taillights of the vehicle ahead. Accordingly, hazardous conditions are created in which speeds are both too high for the prevailing conditions and highly variable. Findings are presented from a study of traffic crashes due to fog in the southern region of Saudi Arabia. The primary objective was to assess the effectiveness of fog detection and warning system on driver behavior regarding speed and headway. This warning system includes visibility sensors that automatically activate a variable message sign that posts an advisory speed when hazardous conditions due to fog occur. The system was installed on a 2 km section of a two-lane, rural highway. A data set of 36,013 observations from both experimental and control sections at two study sites was collected and analyzed. The data included vehicle speed, volume, and classification; time headway, time of day, and visibility distance. Although the warning system was ineffective in reducing speed variability, mean speed throughout the experimental sections was reduced by about 6.5 kph. This reduction indicates that the warning system appeared to have a positive effect on driver behavior in fog even though the observed mean speeds were still higher than the posted advisory speed. From relationships found in the literature between mean driving speed and number of crashes, a speed reduction of only 5 kph would yield a 15% decrease in the number of crashes.
    Accident Analysis & Prevention 12/2007; 39(6):1065-72. · 1.87 Impact Factor
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    Ali S Al-Ghamdi, Saad A AlGadhi
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    ABSTRACT: The camel-vehicle collision (CVC) problem has been increasing in Saudi Arabia and countermeasures are urgently needed to alleviate the heavy losses from such accidents. A research project was funded by the Saudi Arabian government to investigate the problem and to develop techniques to deal with it. Among the different techniques investigated were camel-crossing warning signs. In this study, seven camel-crossing warning signs were tested to determine if they would reduce the number of CVCs on rural roads. The measure of effectiveness utilized was the mean speed reduction of motorists passing such signs. In this paper, the experiments of warning sign testing are detailed, and the evaluation of the signs, based on the results of the testing experiments, is presented. Although most of the signs brought about significant reductions in mean speed, indicating statistical effectiveness, the speed reductions were not relatively large; they ranged from around 3 to about 7 km/h. Furthermore, statistical analysis was used to rank the signs according to their effectiveness. A triangular warning sign with a black camel silhouette and diamond reflective material (220 cm x 220 cm x 220 cm) is recommended in this study. This sign is similar to the standard warning sign used in Saudi Arabia except that it is twice the standard size and uses diamond reflective material.
    Accident Analysis & Prevention 10/2004; 36(5):749-60. · 1.87 Impact Factor
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    Ali S Al-Ghamdi
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    ABSTRACT: Previous studies have shown that intersection-related accidents account for about 50% of all accidents registered annually in Riyadh, the capital of the Kingdom of Saudi Arabia (KSA). More than half of these accidents are classified as severe. In this study, an attempt was made to investigate traffic accidents that occurred at both intersections and non-intersection sites. The goal was to analyze the nature of such accidents to determine their characteristics so that remedies could be sought or at least future research could be suggested. For this purpose, a sample of 1774 reported accidents was collected in a systematic random manner for the period 1996-1998 (651 severe accidents (accidents resulting in at least one personal injury or fatality) and 1123 property-damage-only (PDO) accidents). Conditional probability and contingency table analyses were used to make inferences from the data. The study found that improper driving behavior is the primary cause of accidents at signalized urban intersections in Riyadh; running a red light and failing to yield are the primary contributing causes. The analysis indicates that there is an urgent need to review existing intersection geometry along with the traffic control devices installed at these sites. In addition, public education campaigns and law enforcement strategies are urgently needed.
    Accident Analysis & Prevention 10/2003; 35(5):717-24. · 1.87 Impact Factor
  • Ali S Al-Ghamdi
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    ABSTRACT: Logistic regression was applied to accident-related data collected from traffic police records in order to examine the contribution of several variables to accident severity. A total of 560 subjects involved in serious accidents were sampled. Accident severity (the dependent variable) in this study is a dichotomous variable with two categories, fatal and non-fatal. Therefore, each of the subjects sampled was classified as being in either a fatal or non-fatal accident. Because of the binary nature of this dependent variable, a logistic regression approach was found suitable. Of nine independent variables obtained from police accident reports, two were found most significantly associated with accident severity, namely, location and cause of accident. A statistical interpretation is given of the model-developed estimates in terms of the odds ratio concept. The findings show that logistic regression as used in this research is a promising tool in providing meaningful interpretations that can be used for future safety improvements in Riyadh.
    Accident Analysis & Prevention 12/2002; 34(6):729-41. · 1.87 Impact Factor
  • Ali S Al-Ghamdi
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    ABSTRACT: The emergency medical service (EMS) in Saudi Arabia is managed by each hospital through the Saudi Red Crescent Society (SRCS). There are approximately 165 ambulance stations in the country, each with two ambulances. The SRCS collects data on EMS requests and ambulance arrival times at the accident scene. Each emergency incident has its own implications (accident, fire, injury, etc.) and must be dealt with individually. The aims of this study are to evaluate ambulance rescue time, which includes response time, in the city of Riyadh, the capital of Saudi Arabia; to analyze this time for road traffic accidents; and to compare the response time in Riyadh with corresponding times in other countries. A sample of 874 emergency calls was collected during 1999. Ambulance rescue time consists of three components: response time, time at the scene and travel time to the hospital. Data analysis showed that rescue time is, on average, 35.84 min (S.D. = 6.43 min). Within this time, the average response time is 10.23 min (S.D. = 5.66 min). Other service components (e.g. ambulance time at the accident scene and travel time to the hospital) are analyzed and detailed statistics are given. Ambulance speed to the accident averages approximately 55.05 km/h (S.D. = 27.42 km/h). One primary finding is that there is room for improvement in the rescue time in Riyadh, which would save more lives, through an increase in the efficiency of ambulance team performance. A test statistic is developed in this study to carry out a simple hypothesis testing for percentiles. This test statistic, which is generic and can be used for other applications, is used to compare EMS response time in Riyadh with that in other parts of the world.
    Accident Analysis & Prevention 08/2002; 34(4):499-505. · 1.87 Impact Factor
  • ALI S. AL-GHAMDI
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    ABSTRACT: The headway between vehicles in a traffic stream is of fundamental importance in traffic engineering applications. Previous research in this subject has focused on modeling theoretical distributions for low and medium traffic flow conditions. Yet little research has studied congested traffic conditions, that is, the high traffic flow state. In the same context, there appears to be a lack of clear-cut boundaries for the three flow states (low, medium, and high). This study attempts to determine such boundaries on the basis of traffic conditions observed at the study sites. Although observed headways at arterial sites follow a gamma distribution, distributions that fit freeway headways differ according to the traffic flow state. The Erlang distribution provided a good fit to the observed headways at sites with high traffic flows.
    CIVIL ENGINEERING SYSTEMS. 06/2002; 19(2):169-185.
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    Ali S Al-Ghamdi
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    ABSTRACT: In 1999 there were 450 fatalities due to road crashes in Riyadh, the capital of Saudi Arabia, of which 130 were pedestrians. Hence, every fourth person killed on the roads is a pedestrian. The aim of this study is to investigate pedestrian-vehicle crashes in this fast-growing city with two objectives in mind: to analyze pedestrian collisions with regard to their causes, characteristics, location of injury on the victim's body, and most common patterns and to determine the potential for use of the odds ratio technique in the analysis of stratified contingency tables. Data from 638 pedestrian-vehicle crashes reported by police, during the period 1997-1999, were used. A systematic sampling technique was followed in which every third record was used. The analysis showed that the pedestrian fatality rate per 10(5) population is 2.8. The rates were relatively high within the childhood (1-9 years) and young adult (10-19 years) groups, and the old-age groups (60 - > 80 years), which indicate that young as well as the elderly people in this city are more likely to be involved in fatal accidents of this type than are those in other age groups. The analysis revealed that 77.1% of pedestrians were probably struck while crossing a roadway either not in a crosswalk or where no crosswalk existed. In addition, the distribution of injuries on the victims' bodies was determined from hospital records. More than one-third of the fatal injuries were located on the head and chest. An attempt was made to conduct an association analysis between crash severity (i.e. injury or fatal) and some of the study variables using chi-square and odds ratio techniques. The categorical nature of the data helped in using these analytical techniques.
    Accident Analysis & Prevention 03/2002; 34(2):205-14. · 1.87 Impact Factor
  • Source
    Ali S Al-Ghamdi
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    ABSTRACT: The headway between vehicles in a traffic stream is of fundamental importance in traffic engineering applications. Previous research in this subject has focused on modeling theoretical distributions for low and medium traffic flow conditions. Yet little research has studied congested traffic conditions, that is, the high traffic flow state. In the same context, there appears to be a lack of clear-cut boundaries for the three flow states (low, medium, and high). This study attempts to determine such boundaries on the basis of traffic conditions observed at the study sites. Although observed headways at arterial sites follow a gamma distribution, distributions that fit freeway headways differ according to the traffic flow state. The Erlang distribution provided a good fit to the observed headways at sites with high traffic flows.
    Journal of Transportation Engineering-asce - J TRANSP ENG-ASCE. 01/2001; 127(4).
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    ABSTRACT: More researchers started using real-time traffic surveillance data, collected from loop/radar detectors (LDs), for proactive crash risk assessment. However, there is a lack of prior studies that investigated the link between real-time traffic data and crash risk of reduced visibility related (VR) crashes. Two issues that have not explicitly been addressed in prior studies are; (1) the possibility of predicting VR crashes using traffic data collected from the Automatic Vehicle Identification (AVI) sensors installed on Expressways and (2) which traffic data are advantageous for predicting VR crashes; LDs or AVIs. Thus, this study attempts to examine the relationships between VR crash risk and real-time traffic data collected from LDs installed on two Freeways in Central Florida (I-4 and I-95) and from AVI sensors installed on two Expressways (SR 408 and SR 417). Also, it investigates which data are better for predicting VR crashes. The approach adopted here involves developing Bayesian matched case-control logistic regression models using the historical crashes, LDs and AVI data. Regarding the model estimated based on LDs data, the average speed observed at the nearest downstream station along with the coefficient of variation in speed observed at the nearest upstream station, all at 5–10 min prior to the crash time, were found to have significant effect on VR crash risk. However, for the model developed based on AVI data, the coefficient of variation in speed observed at the crash segment, at 5–10 min prior to the crash time, affected the likelihood of VR crash occurrence. The results showed that both LDs and AVI systems can be used for safety application (i.e., predicting VR crashes). It was found that up to 73% of VR crashes could be identified correctly. Argument concerning which traffic data (LDs or AVI) are better for predicting VR crashes is also provided and discussed.
    Transportation Research Part C Emerging Technologies 24:288–298. · 2.01 Impact Factor