Examining the direct effect of the use of traffic safety technologies in Abu Dhabi highways on other traffic safety dimensions
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Abstracthis paper presents the findings of a study, implemented in Abu Dhabi, which aimed to examine the direct effects of the use of traffic safety technologies on the mitigation of risks associated with traffic accidents. The study adopted the use of a questionnaire-based survey with traffic safety experts in Abu Dhabi Emirate. The views of more than a hundred respondents were collected on areas such as the status of existing traffic safety technologies in Abu Dhabi’s highway network, the impact of traffic safety technologies on enforcement, existing highway design practices, effects of driver education on safety and the impact of safety technologies on the efficiency of emergency responses. Factor analysis and Freidman tests were employed for the interrogation of the data in order to extract findings from the views of different experts on the aforementioned areas. The analysis showed that the deployment of traffic safety technologies has a positive impact on the efficiency of enforcement practices and improvements on traffic safety, and on enhancing operators’ efficiency and capability in taking appropriate and prompt action in situations calling for emergency responses. Moreover, speed cameras and VMS deployment are highly favoured in addressing engineering design shortfalls. Also, training and awareness enhance the efficiency and effectiveness of traffic safety technologies.
CitationAl Junaibi, MM., Panos, G., and Mushatat, S. 'Examining the Direct Effect of the Use of Traffic Safety Technologies in Abu Dhabi Highways on Other Traffic Safety Dimensions,' Journal of Traffic and Logistics Engineering, (5) 1 pp. 1-9 doi: 10.18178/jtle.5.1.1-9
JournalJournal of Traffic and Logistics Engineering
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A FRAMEWORK FOR THE DEPLOYMENT OF TRAFFIC SAFETY TECHNOLOGIES IN ABU DHABI HIGHWAYSAl Junaibi, Musallem (2016-05)There has been a good effort made in Abu Dhabi for the last couple of years between government stakeholders to develop a road safety strategy, define rules and responsibilities, and gain a fully coordinated and integrated framework to deal with road safety. According to my point of view, the challenges that might be seen as a problem for the future development of Abu Dhabi can be the management and the usage of traffic safety technologies to reduce serious road traffic accidents. This study focused on the relationship between the use of traffic safety technologies and serious road traffic accidents on Abu Dhabi Highways. The motivation for this research is to implement correctly the traffic safety technologies in Abu Dhabi highways as a part of the need to adopt plans, programmes, and preventive measures to reduce or prevent the occurrence of traffic accidents in order to ensure the safety of individuals and property, in addition to preserving the security of the state and its human and economic components. The overall approach to this study is a mixed methodology, which combines quantitative and qualitative methods. A questionnaire is one method used in this regard, and is designed to be quantitative. In the quantitative method, comparing statistics of fatalities and injuries before and after installation of the speed cameras is used. As a result of this study and by making the connectivity between reviewing the results and findings of the literature review, identifying the questionnaire results, and exploring the before and after statistics led to findings which were used to develop a decision support framework that can be used to advise the regional safety strategy to be sustainable. The design framework was also validated through Abu Dhabi highways by a panel of experts, which was carried out using the focus group method, which was qualitative in nature. It is recommended from this research to invest much in traffic safety technologies, focus more on driver support systems and rapid response systems, improve driver behaviour as a priority in Abu Dhabi highways using traffic safety technologies, and integrate the compatibility of all of the above through an integrated system and specific performance indicators that are measured and followed up on an ongoing basis, and supported by geographic information systems (GIS).
Deep reinforcement learning-based driving strategy for avoidance of chain collisions and its safety efficiency analysis in autonomous vehiclesMuzahid, Abu Jafar Md; Kamarulzaman, Syafiq Fauzi; Rahman, Md Arafatur; Alenezi, Ali H. (IEEE, 2022-04-18)Vehicle control in autonomous traffic flow is often handled using the best decision-making reinforcement learning methods. However, unexpected critical situations make the collisions more severe and, consequently, the chain collisions. In this work, we first review the leading causes of chain collisions and their subsequent chain events, which might provide an indication of how to prevent and mitigate the crash severity of chain collisions. Then, we consider the problem of chain collision avoidance as a Markov Decision Process problem in order to propose a reinforcement learning-based decision-making strategy and analyse the safety efficiency of existing methods in driving security. To address this, A reward function is being developed to deal with the challenge of multiple vehicle collision avoidance. A perception network structure based on formation and on actor-critic methodologies is employed to enhance the decision-making process. Finally, in the safety efficiency analysis phase, we investigated the safety efficiency performance of the agent vehicle in both single-agent and multi-agent autonomous driving environments. Three state-of-the-art contemporary actor-critic algorithms are used to create an extensive simulation in Unity3D. Moreover, to demonstrate the accuracy of the safety efficiency analysis, multiple training runs of the neural networks in respect of training performance, speed of training, success rate, and stability of rewards with a trade-off between exploitation and exploration during training are presented. Two aspects (single-agent and multi-agent) have assessed the efficiency of algorithms. Every aspect has been analyzed regarding the traffic flows: (1) the controlling efficiency of unexpected traffic situations by the sudden slowdown, (2) abrupt lane change, and (3) smoothly reaching the destination. All the findings of the analysis are intended to shed insight on the benefits of a greater, more reliable autonomous traffic set-up for academics and policymakers, and also to pave the way for the actual carry-out of a driver-less traffic world.
Integrated Framework Development For Intelligent Transport Enforcement SystemsDr. Panos Georgakis; Rangwala, Noman (University of Wolverhampton, 2012-10)This thesis presents the Ph.D. research from the initial stages of investigation, to design and development of an intelligent architecture for vehicles. It was identified that vehicles, intelligent transport systems (ITS) and infrastructure lack a shared platform that allows them to be integrated and work together. With a robust and intelligent framework, distributed ITS can work and improve traffic efficiency. If these gaps are addressed, then they can provide reductions in cost, space and integration opportunities for enhanced functionality as well as additional services. As a part of this research a novel framework was developed, and two ITS systems were integrated such that remote communication with the infrastructure was achieved. Evaluation of this framework indicated that information can be shared across vehicle systems and other ITS systems could be added to the network to improve performance, safety and enforcement. To support the framework design, a Traffic Improvement Algorithm (TIA) was developed that improves traffic efficiency. This was validated using micro simulation tool that showed improvement in traffic efficiency when the algorithm was used. When bringing new technology into the market, there are some fundamental influencing factors affecting the selection and development prior to entering the end-user market. These factors are often neglected, and the current market lacks the ability to analyse the time it would take the new technology to come into the market. As a part of this research, a toolkit was developed that helps in estimating the time the technology takes to penetrate the market.