It is now well recognized that road safety is a worldwide public health problem and there is a high public awareness about road traffic injuries, their grave consequences and enormous costs to society. Road safety developments are correlated with socioeconomic factors such as level of motorization and economic growth which differs significantly between developed and developing countries. This paper discusses and compares the magnitude, trends and causes of traffic accidents, accident costs and cost estimation methods, strategies and countermeasures in both developing and developed countries. Traffic safety data for the period 2003-2013 from selected developing countries are analyzed and compared with European countries (EU). The fatality rates per population for the developing countries were found to be substantially higher than those in EU countries. EU strive to make their fatality rates dropping towards their zero vision while those for developing countries may continue to be high unless effective measures are implemented to reduce the magnitude and severity of their accidents. Accident costs were found to be a real economic burden in developing countries estimated at more than 2% of their Gross Domestic Product (GDP) much higher compared to developed countries. The results suggest that road safety is more appreciated in developed countries. Although developed countries have a good experience in applying road safety programs, it is more difficult to apply the same safety programs in developing countries. This research also highlights the countries' experiences in road safety improvements. Index Terms-Road fatalities, accidents cost, safety programs, developing countries
Abstract-Highway related accidents are considered one of the most serious problems in the modern world as traffic accidents cause serious threat to human life worldwide. Jordan, a developing country, has high and growing level of traffic accidents resulting in more than 13000 fatalities between 1989 and 2012 with an average annual cost of over $500 million. Prediction of future traffic accidents is therefore of utmost importance in order to appreciate the magnitude of the problem and speed up the decision making towards its alleviation. In this paper, a traffic accident prediction model was developed using the novel Artificial Neural Network (ANN) simulation with the aim of identifying its suitability for prediction of traffic accidents under Jordanian conditions. The results demonstrated that the estimated traffic accidents, based on sufficient data, are close enough to actual traffic accidents and thus are reliable to predict future traffic accidents in Jordan.
Road traffic noise along the Jordanian road network is drawing an increasing attention due to its growing magnitude and various impacts as a result of the high increase in vehicular traffic. This study investigates the issue with the aim of providing an understanding of its social impact on residents of Amman, the capital of Jordan and developing a noise level prediction model under local conditions. Thirty four sites along urban arterials, representing different characteristics, were included in the study and used for model development. Traffic noise levels were measured at the selected locations and a social survey was performed, using a predesigned questionnaire, to examine the reactions and attitudes of the neighbouring residents towards these levels of traffic noise. The results of the study revealed that the impact of traffic noise on people can cause annoyance while performing daily activities to the extent that 65% of the respondents think of moving to a quitter place, and about 54% were willing to pay for attenuation measures. The resulting prediction model incorporated variables describing traffic and site conditions. The developed model was validated by comparing it's predicted noise levels with those measured and found to be valid under local conditions.
This study provides an evaluation of road traffic noise pollution in Amman, the capital of Jordan through measuring and predicting the statistical noise index L10 (18 hr) at selected sites using the British CRTN method after validation. The measured and future noise levels were found high and exceed the maximum allowable limit of 63 dB(A) at all survey sites calling for the need to apply mitigation measures. The effectiveness of noise barriers in reducing noise levels was investigated and 3-5 m noise barriers were found appropriate.
Amman, the capital of Jordan has been subjected to persistent increase in road traffic due to overall increase in prosperity, fast development and expansion of economy, travel and tourism leading to the traffic noise being a growing environmental problem. This study investigates the changes over the years in the magnitude of the traffic noise pollution, the attitude of the residents towards the problem and estimates its economical impact.Measurements were made at selected locations and compared with published figures at the same locations in order to identify the changes over time. The impact of the problem on the exposed residents was also evaluated through carrying out a social attitudinal survey and the results were compared with those of similar studies. An attempt is also made to valuate and put a monetary value for traffic noise.The results confirm that traffic noise levels are growing over the years and their social and economic impacts are also both growing and becoming more significant
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.