Title: Research on travel time prediction of expressway in peak period based on Greenberg model

Authors: Yan Xing; Yuqing Hao

Addresses: School of Transportation Engineering, Shenyang Jianzhu University, Shenyang 100168, China ' School of Transportation Engineering, Shenyang Jianzhu University, Shenyang 100168, China

Abstract: Expressway travel time is an important parameter to describe the traffic status, which can accurately reflect the efficiency of expressway traffic. To further simplify the complexity of the travel time prediction method, and improve the prediction accuracy, in this paper, the travel time prediction of the expressway is divided into three cases for discussion. First of all, based on the Greenberg model, under the premise of a comprehensive analysis of the section flow, traffic density, and other factors, to establish different sections under the peak period expressway vehicle travel time prediction model. Finally, the model is verified by taking the expressway around the city as an example. The results shows that the prediction results are always within 10% of the actual measurement error, which shows that compared with the measured data, the error of the model proposed is small, the prediction accuracy is high, within the acceptable range.

Keywords: travel time prediction; entrance/exit ramps; Greenberg model; peak period expressway.

DOI: 10.1504/IJSPM.2022.130284

International Journal of Simulation and Process Modelling, 2022 Vol.19 No.1/2, pp.54 - 61

Received: 13 Apr 2021
Accepted: 04 Jan 2022
Published online: 17 Apr 2023 *

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