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Recently, the severity of injuries resulting from traffic crashes has been extensively investigated in numerous studies. However, the number of studies that addressed the severity of the run-off-road (ROR) crashes is relatively low. In the Emirate of Abu Dhabi (AD), approximately 22% of the total serious crashes and fatalities that occurred from 2007 to 2013 were ROR crashes. Despite these facts and the uniqueness of the composition of licensed drivers in AD (approximately 87% of them are non-Emiratis), the factors affecting the occurrence and severity of ROR crashes in AD have not been explicitly addressed in any prior studies. Therefore, this study aims to investigate the characteristics of at-fault drivers involved in ROR crashes in AD, the nature and main causes of those crashes. In this regard, conditional distribution and two-way contingency tables were developed. In addition, this study aims to identify and quantify the factors affecting the severity of ROR crashes such as driver, road, vehicle and environment factors. To achieve this goal, ordered probit model approach was employed. Crash data for a total of 3819 ROR crashes that occurred in AD were employed in the analysis. The results indicated that driver factors (carelessness, speeding, and nationality), vehicle characteristics (vehicle type), and road and environment factors (road type, crash location and road surface condition) were the significant factors influencing the severity of ROR crashes in AD. Countermeasures to improve traffic safety and reduce numbers and severity of ROR crashes in AD were discussed.

The main objective of this research project is to develop, implement and test an efficient real-time system for the allocation of patrol cars to various locations within the boundaries of the Abu Dhabi Emirate. Patrol cars are allocated initially to provide adequate coverage over a wide area that is divided into geographic zones. However, during daily operations the patrol cars move to deal with traffic accidents or calls for assistance originating from various locations in each zone. The proposed patrol allocation system is essentially an automated decision support system that relies on Geographic Information System (GIS) and other data related to current and real-time traffic flow to assist the dispatch operators in making effective patrol allocation decisions. The system also computes the number of patrol vehicles required in order to make sure that the response time falls below a given threshold or upper limit. The basic system concept and structure are presented.

Based on historical evidence, driving in heavy fog conditions is one of the most serious causes that lead to massive highway accidents. For example, the Abu Dhabi-Dubai Highway (E10) faced two record accidents in recent times. The first accident was in March 2008 in which more than 200 vehicles were involved in a mass collision. The second was in April 2011 and it involved 130 vehicles. These two massive accidents, and several other relatively minor ones, were due to poor visibility conditions caused by dense fog. Vehicles driving at high speed suddenly enter road sectors covered by dense fog without warning and are then implicated in mass collisions. The main objective of this research is to improve road safety in Abu Dhabi when drivers face poor visibility conditions caused by dense fog. This is achieved by sending early real-time warning signals to all drivers who are about to enter poor visibility sections of the highway of the dangers ahead, using radio signals or cell phone voice-based short messages. Warning signals can also be displayed to the drivers using Changeable Message Signs (CMS) installed along the highway. The concept and architecture of a novel, modular fog warning system are presented. 

The municipality of Abu Dhabi is in the process of updating its long-range master transportation plan. The initial step in this process was to collect substantial data on existing transportation system characteristics. The extensive data-collection program made possible a comprehensive analysis of traffic characteristics for the first time in more than 20 years. Traffic characteristics in Abu Dhabi have changed significantly during this time. Recent changes in government working hours have caused a dramatic shift in peaking patterns. Some characteristics, such as the availability and performance of taxis, are unique. Other characteristics, such as general peak period factors, are typical of most Arab Gulf cities. Presented is an analysis of existing traffic characteristics in Abu Dhabi. Peaking patterns, vehicle classifications, vehicle occupancies, and other characteristics are analyzed and described. The characteristics that are unique to Abu Dhabi are identified. Characteristics transferable to other Gulf Cooperation Council countries are highlighted and discussed.

Red light running crashes have always been a major concern to both researchers and practitioners. In Abu Dhabi, United Arab Emirates, the red light crashes contribute to about 60% of the total severe crashes at signalized intersections. This fact called for a project in 2013, for which new red light cameras (RLCs) were planned to cover 150 intersections in Abu Dhabi City. With the completion of the second stage of this project, 36 signalized intersections have been covered either fully (all intersection approaches) or partially (only major approaches) with a total of 108 RLCs. These RLCs are now in place and have been fully functioning since January 2014. The primary aim of this study was to examine the impact of the installed RLCs on the traffic safety performance in the city. To waive the effects of other factors, two groups were created; they include a study group (36 signalized intersections with RLCs) and a comparison group (36 similar intersections without RLCs). The results indicate a reduction of about 40% to 52% for the number of crashes and 48% to 60% for the number of fatalities and injuries. The majority of at-fault drivers were young male drivers from Asian countries with read-and-write educational level. Moreover, crashes, fatalities, and injuries were modeled using the negative binomial technique. Among 13 tested variables describing the traffic exposure, traffic violations, number of lanes, and coverage of intersections by RLCs, only the number of lanes was found significant in two significant models.

The city of Abu Dhabi has witnessed a major growth in its population over the past two decades. This growth has resulted in a significant increase in the number of vehicles in the city. Abu Dhabi Police Department (ADPD) is currently working on the development of a traffic monitoring and response center. The main objective of this paper is to present the main framework for ADPD's traffic monitoring and response center, which will allow for a more robust operation of the police department activities. The core element of the response system is a microsimulation model for the city. This paper presents the main framework for ADPD traffic center and the initial results of the microsimulation model development. The well-known microsimulation model VISSIM is utilized to create the core of the traffic monitoring and response center, which will allow ADPD to test and investigate different scenarios.