Transportation Management Plan of Tubas Main Street
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Date
2023
Authors
علاء بانا
محمد طنبور
نهاد الشخشير
ابراهيم قرنفله
Journal Title
Journal ISSN
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Abstract
Tubas Main Street is one of the most important streets in the city of Tubas. It has
heavy traffic volumes almost all day long. This region and its surrounding areas are expected
to grow at a rapid rate in the future and are expected to face emerging problems due to such
growth. Therefore, it is important to shed light on the problem, find the causes, and find some
applicable solutions so that the competent authorities can apply these solutions as much as
possible.
This study focuses on:
1. Traffic operating conditions.
2. The engineering design of the streets in the region.
3. Proposing ideas and solutions to existing and expected problems.
The methodology that has been conducted in this study is based on previous studies in
this area, as well as using techniques, methods, and references adopted locally and
internationally. Our team made field visits to the considered area to report the state of the
street, and collect field data on the traffic operating conditions to be used in the analysis
phase. An appropriate design and management plan has been developed. The analysis and
designs were based on American Association of State Highway and Transportation Officials
(AASHTO), Highway Capacity Manual, and local specifications and standards. Finally, the
completed work has been offered into a report with the necessary design plans, tables, figures
and proposed solutions.
Results of the study are provided in this project include traffic conditions, and
geometric designs need to be revised and redesigned in order to improve traffic conditions
and reduce congestion level. It also includes improving traffic safety conditions for the study
area. The results of this study will be useful for future studies as well. The final output will
form a transportation management plan for the study area along with plans and ideas on
improving the existing conditions in order to provide the best possible outcomes and
solutions for forecasted problems