Time filter

Source Type

Beirut, Lebanon

Alshalalfah B.,SETS International | Shalaby A.,University of Toronto | Dale S.,Creative Urban Projects CUP
Journal of Urban Planning and Development

The main purpose of conventional transit systems is to serve concentrated travel patterns in urban areas, where they usually have high levels of success. Unconventional transit modes have also found success in specific conditions, fuelled by the need for transit modes that handle different demand levels, urban environment patterns, and even natural constraints and barriers. In many urban contexts, geographical and topographical barriers such as mountains, valleys, and bodies of water, and the very large infrastructure costs associated with overcoming these barriers, may not permit the implementation of conventional public transportation systems. In such cases, transit agencies may look to unconventional modes of travel to serve the needs of the residents of these areas. Aerial ropeway transit (ART), a type of aerial transportation in which passengers are transported in cabins that are suspended and pulled by cables, is one of the solutions that has shown its implementation rise in the past decade. This paper attempts to shed some light on ART technology by presenting experiences with this technology from both the United States as well as other parts of the world including the reasons for building these systems and their service and operational characteristics as well as other case-specific information. The paper concludes with an assessment of experiences with these systems including their benefits and limitations as well as a discussion of the advancements needed for ART technologies to be a fully recognized transit mode. © 2013 American Society of Civil Engineers. Source

Sayegh A.S.,SETS International | Munir S.,University of Umm Al - Qura | Habeebullah T.M.,University of Umm Al - Qura
Aerosol and Air Quality Research

The ability to accurately model and predict the ambient concentration of Particulate Matter (PM) is essential for effective air quality management and policies development. Various statistical approaches exist for modelling air pollutant levels. In this paper, several approaches including linear, non-linear, and machine learning methods are evaluated for the prediction of urban PM10 concentrations in the City of Makkah, Saudi Arabia. The models employed are Multiple Linear Regression Model (MLRM), Quantile Regression Model (QRM), Generalised Additive Model (GAM), and Boosted Regression Trees1-way (BRT1) and 2-way (BRT2). Several meteorological parameters and chemical species measured during 2012 are used as covariates in the models. Various statistical metrics, including the Mean Bias Error (MBE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), the fraction of prediction within a Factor of Two (FACT2), correlation coefficient (R), and Index of Agreement (IA) are calculated to compare the predictive performance of the models. Results show that both MLRM and QRM captured the mean PM10 levels. However, QRM topped the other models in capturing the variations in PM10 concentrations. Based on the values of error indices, QRM showed better performance in predicting hourly PM10 concentrations. Superiority over the other models is explained by the ability of QRM to model the contribution of covariates at different quantiles of the modelled variable (here PM10). In this way QRM provides a better approximation procedure compared to the other modelling approaches, which consider a single central tendency response to a set of independent variables. Numerous recent studies have used these modelling approaches, however this is the first study that compares their performance for predicting PM10 concentrations. © Taiwan Association for Aerosol Research. Source

Kaysi I.,American University of Beirut | Alshalalfah B.,SETS International | Shalaby A.,University of Toronto | Sayegh A.,SETS International | And 2 more authors.
Transportation Research Record

Each year during the ninth month of the Muslim lunar calendar, more than 2 million Muslim pilgrims from around the world travel to the Holy City of Mecca in Saudi Arabia for Hajj, an annual religious pilgrimage. A significant milestone in the effort to improve the existing transport system in the Holy City was the introduction of the Southern Masha'er Rail Line during the 2010 pilgrimage season. In the first year of operation, the line operated at only 30% of its full capacity before full implementation in the following year, when the line operated at full capacity of 72,000 passengers per hour. Results are presented of a users' survey that aimed to assess the performance of the rail line from the perspective of its users. The analysis revealed that rail users faced longer access, waiting, and egress times compared with regular rail operations standards. However, survey results showed that the majority of pilgrims found these times to be tolerable. Moreover, the majority of users found the rail line and its stations to be of excellent quality and gave positive recommendations for using the rail line in the future. The analysis also produced some interesting observations that may be of relevance to rail operation in similar crowded events. Those observations are highlighted. Source

Discover hidden collaborations