A Framework for Abu Dhabi Police Traffic Monitoring and Response Center

Abstract—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

Exploring the Nature and Severity of Heavy Truck Crashes in Abu Dhabi, United Arab Emirates

Traffic crashes involving heavy trucks long have been a major concern in the field of traffic safety because of their great effect on accident severity. The emirate of Abu Dhabi, capital of the United Arab Emirates, features a unique situation: several roads designed mainly for truck movement. Even though those roads were constructed more than 10 years ago to decrease the severity of truck-related crashes, no prior studies have examined their effects on traffic safety improvements. The goals of this study were to understand better the nature, characteristics, and causes of heavy truck crashes occurring in Abu Dhabi; to identify the factors associated with crash severities; and to examine the probability of truck crashes involving fatalities on truck roads versus on mixed-vehicle roads. Data were analyzed from a sample of 1,426 heavy truck–related crashes with reported fatalities or injuries that occurred in Abu Dhabi between 2007 and 2013. First, conditional distributions, two-way analysis, and odds ratios were performed. Second, ordered probit and structural equation models were developed. Results indicated that the likelihood of truck crashes involving fatalities was 35% higher on truck roads than on mixed-vehicle roads. In addition, findings showed that human error, driver education, location, road type, and road speed variables were significant in affecting the severity of heavy truck– related crashes. Finally, practical suggestions on how to reduce the number of heavy truck–related crashes in Abu Dhabi are presented and discussed. </jats:p

Examining the factors affecting the severity of run-off-road crashes in Abu Dhabi

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. </jats:p

Efficient real-time allocation of patrol cars in traffic management

Efficient allocation and dispatch of emergency vehicles is a common problem encountered by law enforcement and public safety agencies. An example of such agencies is the traffic patrol department, which has the responsibility of regulating and managing the movement of road traffic as well as responding to road incidents in a timely manner. A brief analysis of the patrol car allocation problem is presented. The problem involves determining the minimum number of patrol cars required to maintain a required service standard and the optimum location of patrol cars to achieve the best response times. An algorithm for determining the optimal number of patrol cars and the prepositioning of the vehicles is presented. The algorithm combines an analytical model with a Monte Carlo simulation, keeping execution times manageable. Even when applied to large geographic areas, the computational requirements of the algorithm remain modest