Technical Papers
Apr 17, 2020

Modeling and Evaluating the Impact of City Block Size on Traffic Performance

Publication: Journal of Urban Planning and Development
Volume 146, Issue 3

Abstract

This paper investigates how block size influences traffic by dividing the travel distance, time, and number of turning maneuvers into two parts: the one that happens inside the block, and the one outside. We develop analytical formulations that yield representative values of the three aforementioned indicators under low-demand scenarios. A VISSIM simulation with a dynamic traffic assignment is used to verify such values, study the traffic behavior for high-demand scenarios, and evaluate the traffic performance, network capacity, and resiliency. The results indicate that traffic inside the block plays a more important role on the overall performance in networks with larger block size and/or short trips. In addition, smaller block-size networks yield shorter travel distance and better travel accessibility, as well as higher network capacity; whereas larger block-size networks have shorter travel time and smaller number of turnings under low-demand levels. In the congested situation, the larger block-size networks show relatively better performance as they take longer to become congested and gridlocked.

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Acknowledgments

This work was partially supported by the NYUAD Center for Interacting Urban Networks (CITIES), funded by Tamkeen under the NYUAD Research Institute Award CG001 and by the Swiss Re Institute under the Quantum Cities™ initiative.

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Go to Journal of Urban Planning and Development
Journal of Urban Planning and Development
Volume 146Issue 3September 2020

History

Received: Mar 11, 2019
Accepted: Nov 27, 2019
Published online: Apr 17, 2020
Published in print: Sep 1, 2020
Discussion open until: Sep 17, 2020

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Authors

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Ph.D. Candidate, School of Transportation and Logistics, Southwest Jiaotong Univ., Chengdu 610031, China (corresponding author). ORCID: https://orcid.org/0000-0003-1988-5999. Email: [email protected]
Associate Professor, Division of Engineering, New York Univ. Abu Dhabi 129188. ORCID: https://orcid.org/0000-0001-5701-0523. Email: monica[email protected]

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