Citation

Imran W, Khan ZH, Khan D, Ghani U, Bashir T. Transp. Res. Interdiscip. Persp. 2024; 25: e101108.

Copyright

(Copyright © 2024, Elsevier Publishing)

DOI

10.1016/j.trip.2024.101108

PMID

unavailable

Abstract

The macroscopic continuum traffic flow models are being investigated to predict and ameliorate traffic more efficiently. These models are beneficial implementation tools to comprehend and complement the shortfalls in traffic evolution. Despite the significant enhancements in devising the traffic dynamics, the practical utilization of these macroscopic models is not being fully explored. In this study, the Non-Homogeneous Stimulus-Response Model (NHSRM) (Imran et al., 2023) is investigated for its application in forecasting traffic flow on a curvy highway during various weather conditions. The weather impact, in the specific, dry, light rainfall, moderate rainfall, and heavy rainfall on the travel time, velocity, and density spatiotemporal evolution on a curvy highway is analyzed. The flow during different weather conditions is investigated over two curved roads with 120 m, and 500 m radii. As evident from the results, significant velocity breakdowns during heavy rainfall impact the upstream traffic which contributes to congestion development. The average velocity of traffic depletes significantly, and the congestion formation upstream is significant. While the travel time of particular highway segments elevates sharply during heavy rainfall. A comprehensive understanding of the insights, and the criticality associated with the parameters of the model, in particular, on the choice of the maximum velocity of the highway has been presented for NHSRM.

Keywords

Adverse weather conditions; Curvy highways; Macroscopic continuum model; Non-Homogeneous-Stimulus-Response model; Traffic dynamics; Traffic forecasting