Case Studies
Oct 8, 2022

Experimental Design for Measuring Operational Performance of Truck Parking Terminal Using Simulation Technique

Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8, Issue 4

Abstract

The paper presents the performance analysis of a well-designed truck parking terminal, which is planned for regulating truck traffic over a commercial port. The designed truck parking terminal is modeled using microscopic traffic simulation, which is validated based on the movement of vehicles to the parking bays. After validation, various scenarios were created to evaluate parking terminal performance by varying the parking volumes and number of operational parking bays. The operational efficiency of the parking terminal for design scenarios was evaluated using parking performance measures that included parking load, average parking duration, parking turnover, and load-to-capacity ratio (parking index). For the design peak load of 4,200  vehicles/day with a uniform arrival rate, the operational efficiency was found to be about 73%. Interestingly, it was observed that with an increase in the number of operational parking bays, the parking efficiency decreased for the given volume level. Considering this phenomenon, a methodology was developed to identify the optimum number of parking bays under varying demand-supply scenarios. The developed methodology can help identify the optimum number of parking bays for existing and future (expansion) conditions. Furthermore, this study highlights the importance of using simulation in evaluating operational and design aspects of transportation facilities, where the need for repeated empirical observations is eliminated. As such, this study should be of interest to traffic engineers and practitioners interested in the efficient operation of parking terminals.

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Data Availability Statement

Some data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request:
Simulation model.
Data generated from simulation runs.

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Go to ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8Issue 4December 2022

History

Received: May 3, 2022
Accepted: Jul 31, 2022
Published online: Oct 8, 2022
Published in print: Dec 1, 2022
Discussion open until: Mar 8, 2023

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Postdoctoral Researcher, Civiele Techniek en Geowetenschappen, Delft Univ. of Technology, Stevinweg 1, Delft 2628 CN, Netherlands (corresponding author). ORCID: https://orcid.org/0000-0002-3561-5676. Email: [email protected]; [email protected]
Shriniwas Arkatkar [email protected]
Associate Professor, Dept. of Civil Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat 395007, India. Email: [email protected]
Said Easa, M.ASCE [email protected]
Professor, Dept. of Civil Engineering, Ryerson Univ., 341 Church St.,Toronto, ON, Canada M5B 2M2. Email: [email protected]
Gaurang Joshi [email protected]
Professor, Dept. of Civil Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat 395007, India. Email: [email protected]

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