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.
CitationMusallem M. Al Junaibi, Panos Georgakis, and Sabah Mushatat, "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, Vol. 5, No. 1, pp. 1-9, June 2017. 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).
Real-Time Traffic Event Detection Using Twitter DataJones, Angelica Salas; Georgakis, Panagiotis; Petalas, Yannis; Suresh, Renukappa; Faculty of Science and Engineering, University of Wolverhampton, United Kingdom; Faculty of Science and Engineering, University of Wolverhampton, United Kingdom; Faculty of Science and Engineering, University of Wolverhampton, United Kingdom; Faculty of Science and Engineering, University of Wolverhampton, United Kingdom (ICE Publishing, 2018-03-21)Incident detection is an important component of intelligent transport systems and plays a key role in urban traffic management and provision of traveller information services. Due to its importance, a wide number of researchers have developed different algorithms for real-time incident detection. However, the main limitation of existing techniques is that they do not work well in conditions where random factors could influence traffic flows. Twitter is a valuable source of information as its users post events as they happen or shortly after. Therefore, Twitter data have been used to predict a wide variety of real-time outcomes. This paper aims to present a methodology for a real-time traffic event detection using Twitter. Tweets are obtained through the Twitter streaming application programming interface in real time with a geolocation filter. Then, the author used natural language processing techniques to process the tweets before they are fed into a text classification algorithm that identifies if it is traffic related or not. The authors implemented their methodology in the West Midlands region in the UK and obtained an overall accuracy of 92·86%.
Investigating the influence of vehicular traffic on a major trunk road on rural air qualityWilliams, Craig D.; Obara, Paul Goodluck (University of Wolverhampton, 2012-07)Traffic population in the UK has grown by 27% in 2002 and predicted to continue to an estimated 38% in 2016 and up to 60% by 2031. This means vehicular emissions from road transport may account for higher proportion of total emissions of pollutants resulting in air pollution with its attendant consequences. Although poor air quality concerns has often been linked to urban areas, many rural areas apparently have locations where air quality objectives may be threatened especially in the wake of increasing vehicular population. Thus, this elicits the necessity to investigate the relationship between vehicular emissions and air quality. This study investigated the influence of vehicular traffic on a major trunk road on rural air quality through continuous measurements of nitrogen dioxide, sulphur dioxide and hydrocarbon between June 2008 and April 2010 along a major trunk road in a catalogued rural environment in the UK. Collection and analysis of pollutants was by Dräger short-term tubes and Dräger passive diffusion tube techniques. Throughout the sampling period, concentrations of sulphur dioxide were not detected using the short-term tube technique but were detected by the passive diffusion tubes. The study found that variations in mean concentrations of the pollutants were synonymous with traffic frequency and were influenced by meteorological conditions especially wind speed, temperature and relative humidity. Results observed concentration decline trend with increasing distance and showed maximum concentrations during winter, mainly in areas of close proximity to anthropogenic source, and minimum in summer. Values between winter year 1 and winter year 2 monitoring campaigns showed significant difference (P<0.05 and R=0.91) as was in summer year 1 and year 2 (P<0.05 and R=0.94), spring year 1 and year 2 (P<0.05 and R=0.84) and autumn year 1 and year 2 (P<0.05 and R=0.79). When compared with the guidance limits, NO2 Page ii showed exceededance at roadside and 50 m, and at some sample sites, up to 100 m from the road. Conversely, SO2 did not show any exceedance but statistical analyses was mostly significant between concentrations and distance at p≤0.05, suggesting the variability of pollutants, as well as the influence of distance on their temporal and spatial distribution. Results also show that pollutants correlated very well with daily traffic population with strong positive r2 and R-values. Similarly, the study considered the application of hazel leave (Corylus avellana) and ryegrass (Lolium perenne) vegetation samples in monitoring rural air quality. Both samples were collected in different seasons and distances (5m, 50m, and 100m) from the A49 trunk road at four rural sites characterised with diverse traffic densities and anthropogenic activities. The aim was to determine the elemental content and trends within the samples and to investigate the influence of distance from the road, height from ground level, and sampling season on the elemental levels. The levels of Al, As, Ba, Ca, Si, Mg, S, Cd, Cr, Na, Ni, Sb, Se, Sn, Mo, Mn, C, K, P, Cl, Ti, Fe, Zn, and Pb were determined using X-ray fluorescence (XRF), inductively coupled plasma-mass spectrometer (ICP-MS), and Scanning Electron Microscopy-Energy Dispersive X-ray spectrometer (SEM-EDX). Results show that despite the traffic differentials between the sampling sites, the pollution level of heavy metals were generally low in all sampling site and concentrations of Cr, Cu, Ni, Pb, and Ti exhibited inverse relationship with distance, decreasing in levels with increasing distance from the trunk road. Although root uptake from the soil is a potential source of heavy metals, geochemistry research of the study area did not show any evidence that proves any major heavy metals deposit concerns in the soil. It is therefore possible that heavy metal emissions were deposited in a form that was not readily available for root uptake, thereby narrowing the presence of heavy metal pollutants to other potential Page iii sources. However, this study found high level of heavy metals at the roadside measurements in the order of Zn (0.703 ppm) > Ti (0.346 ppm) > Cr (0.111 ppm) > Cu (0.106 ppm) > Pb (0.026 ppm) > Ni (0.025 ppm). They were found in different magnitudes higher than their respective levels at 50 and 100 m from the trunk road and therefore tend to support traffic origin. Findings from this study show that heavy metals exhibited different degree of correlation between individual elements, ranging from very strong positive to weak, as well as negative correlations. Statistical analyses show that the elements predominantly exhibited statistically significant differences between elements and between distances from the road. Overall, findings from this study demonstrate that both vegetation species prove to be successfully useful in determining the pollution status and trends of traffic-related heavy metals.