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    Browsing Qatar Transportation and Traffic Safety Center by Type "Poster"

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        Enhancing Pedestrian Safety through the Development of Advanced Operational Strategies for Crosswalks in Residential Areas 

        Hussain, Qinaat; Alhajyaseen, Wael; Kharbeche, Mohamed ( Qatar University Press , 2021 , Poster)
        Pedestrians are the most vulnerable group in the traffic. Every year approximately 40,000 pedestrians are killed in the world due to road traffic crashes. In the state of Qatar, the situations are even worse with around ...
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        Impact of Attention Deficit Hyperactivity Disorder on Driving among Drivers in Qatar 

        Alhajyaseen, Wael; Timmermans, Chantal; Soliman, Abdrabo; Brijs, Tom; Bedair, Khaled; Ross, Veerle; Mamo, Wondwesen Girma... more authors ... less authors ( Qatar University Press , 2021 , Poster)
        This study aims to investigate the impact of ADHD traits on young drivers' deviant driving behaviors that may contribute to their involvement in traffic crashes. Methods: A sample of 450 young drivers from the State of ...
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        Investigating the impact of innovative treatments on driving behavior at school bus stops: A driving simulator study 

        Almallah, Mustafa Suhail; SayedMohammed, Shabna; Hussain, Qinaat; Alhajyaseen, Wael K. M. ( Qatar University Press , 2021 , Poster)
        The illegal overtaking/crossing of stopped school buses has been identified as one of the leading causes of students' injuries and fatalities. The likelihood of students in getting involved in a school bus-related crash ...
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        Machine Learning Approach to Predict Metro Ridership based on Land Use Densities 

        Alkhereibi, Aya Hasan; Wakjira, Tadesse; kucukvar, Murat; Qidwai, Uvais; Muley, Deepti; Siam, Abdalla... more authors ... less authors ( Qatar University Press , 2021 , Poster)
        Predicting metro ridership is an essential requirement for efficient metro operation and management. The dependence of metro ridership on the land use densities entails a need for an accurate predictive model. To this end, ...

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