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Developing Trip Generation Rates For Hospitals In Amman

Submitted2014-11-04
Last Update2014-11-04
TitleDeveloping Trip Generation Rates For Hospitals In Amman
Author(s)Author #1
Author title:
Name: Mohammad Naser
Org: Assistant Professor, Department of Civil Engineering, Faculty of Engineering and Technology, The University of Jordan.
Country:
Email: test@test.test

Author #2
Author title:
Name: Sa´┐Żad Abu Qdais
Org: Professor, Department of Civil Engineering, Faculty of Engineering, Jordan University for Science and Technology
Country:
Email:

Author #3
Author title:
Name: Hossam Faris
Org: Assistant Professor, Business Information Technology Department, King Abdulla II School for Information Technology, The University of Jordan
Country:
Email:

Other Author(s)
Contact AuthorAuthor #1
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KeywordsTrip generation, Traffic impact assessment, Transportation planning, Urban transportation modeling system, Hospitals
AbstractTraffic Impact Assessment (TIA) for proposed developments often relies on trip rates obtained from historical studies. One of the most commonly used references for estimating trip rates for different proposed land uses is the Institute of Transportation Engineers´┐Ż (ITE) trip generation manual. There are many issues related to the accuracy levels associated with using ITS trip generation rates within the U.S. and for sites in other countries. This study focused on developing trip generation rates for hospitals in the city of Amman, where twenty one hospitals were surveyed during average weekdays and two categories of data were collected for each hospital; various traffic volume counts and specific descriptive information about the hospital including its area, number of beds and number of available parking stalls. This study showed that trip generation models developed in the ITE trip generation manual will not produce accurate estimates that could be used for proposed hospital sites. Several methods were used to develop hospital trip generation models, including single variable regression, multivariate regression and MLP algorithms. The data analysis showed that the number of patient beds and the gross floor area were the main factors affecting the number of hospital vehicle trip generation.
Paperview paper 2878.pdf (212KB)

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