Technical Papers
Nov 3, 2023

Cycle-Length Optimization of Isolated Signalized Intersection with Mixed-Traffic Condition

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 150, Issue 1

Abstract

For signalized intersections with mixed traffic conditions, pedestrians and bicyclists (P&Bs) affect the vehicle saturation flow rate (SFR), which further influences the cycle length. However, existing studies always consider the effect of P&Bs on vehicle SFR as a constant, which is actually time-variant according to the P&Bs crossing state. Thus, it is necessary to consider this characteristic when determining the cycle length. This study developed a cycle-length model that considers the time-variant effect of P&Bs. The vehicle SFR is first modified using the adjustment factor method. By substituting the modified vehicle SFR into Webster’s delay formula, the numerical solutions of the optimal cycle were derived by considering the minimum vehicle delay as the target. Thereafter, using linear regression of the optimal and minimum cycles, the model was simplified, and an analytical solution of the optimal cycle was derived. The average deviation caused by simplification was 1.95%. The optimality of the model was validated by simulation, with significant reduction in vehicle delay compared with the traditional highway capacity manual (HCM) method.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author by request.

Acknowledgments

This study was supported by the National Natural Science Foundation of China (52131204 and 52272336) and the Fundamental Research Funds for the Central Universities (2022-5-YB-05 and 22120220580).

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Published In

Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 150Issue 1January 2024

History

Received: Dec 26, 2022
Accepted: Aug 31, 2023
Published online: Nov 3, 2023
Published in print: Jan 1, 2024
Discussion open until: Apr 3, 2024

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Authors

Affiliations

Graduate Student, Key Laboratory of Road and Traffic Engineering of the Ministry of Education, College of Transportation Engineering, Tongji Univ., Shanghai 201804, China. ORCID: https://orcid.org/0000-0001-8535-4972. Email: [email protected]
Professor, Key Laboratory of Road and Traffic Engineering of the Ministry of Education, College of Transportation Engineering, Tongji Univ., Shanghai 201804, China (corresponding author). ORCID: https://orcid.org/0000-0002-9403-3174. Email: [email protected]
Professor and Director, Dept. of Traffic Engineering, Univ. of Shanghai for Science and Technology, 516 Jungong Rd., Shanghai 200093, China. ORCID: https://orcid.org/0000-0003-0741-4911. Email: [email protected]

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Cited by

  • Estimation of vehicle control delay using artificial intelligence techniques for heterogeneous traffic conditions, Expert Systems with Applications, 10.1016/j.eswa.2024.123206, 246, (123206), (2024).

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