Title: A novel analytical model for estimating vehicle delay at isolated signalised intersections

Authors: Feng Qiao; Huixin Liu; Dan Luo; Haochen Sun; Yinong Chen

Addresses: School of Information and Control Engineering, Shenyang Institute of Technology, Fushun, 113122, China; Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang, 100168, China ' School of Information and Control Engineering, Shenyang Institute of Technology, Fushun, 113122, China ' School of Information and Control Engineering, Shenyang Institute of Technology, Fushun, 113122, China ' School of Information Engineering, Henan University of Science and Technology, Luoyang, 471000, Henan, China ' School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ 85287-8809, USA

Abstract: This paper proposes a novel analytical model to estimate the average vehicle delay at signalised intersections under saturated or oversaturated conditions based on the investigation and analysis of the existing methods to deal with the problems arising in the process of acceleration, deceleration, and the transmissibility of the cycle-by-cycle average vehicle delay. The proposed model employs and combines the operating and queuing characteristics of vehicles to produce the analytic formula. To verify the effectiveness of the proposed model, simulation experiments are conducted, and the error rates and the correlation coefficients are investigated, which confirm that the proposed model possesses certain significant advantages over the existing models in saturated and oversaturated conditions. The results of research work show that the proposed model can provide transportation engineers or professionals with an effective tool for analysing, timing and managing the saturated or oversaturated signalised intersections.

Keywords: signalised intersection; analytical model; vehicle delay; saturated condition; oversaturated condition; operating characteristics.

DOI: 10.1504/IJSPM.2022.130286

International Journal of Simulation and Process Modelling, 2022 Vol.19 No.1/2, pp.71 - 85

Received: 02 Apr 2021
Accepted: 22 Jan 2022
Published online: 17 Apr 2023 *

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