https://doi.org/10.1140/epjb/s10051-025-00902-9
Regular Article - Statistical and Nonlinear Physics
The role of predictive effect in lattice model incorporating traffic jerk effect
Department of Mathematics, University Institute of Sciences, Chandigarh University, 140413, Mohali, Punjab, India
Received:
26
July
2024
Accepted:
13
March
2025
Published online:
1
April
2025
In traffic networks, the intricate traffic congestion is the result of the abrupt deceleration and acceleration of non-motor vehicles that react by observing downstream situations. Furthermore, as information technology (IT) continues to grow and evolve, drivers can now obtain a precise assessment of the present status of real-time traffic on a prior basis. The traffic congestion that occurs due to traffic jerks may be minimized with the use of prior information (known as the predictive effect). To assess the impact of the predictive effect and traffic jerk effect on homogeneous vehicular flow, an extended lattice hydrodynamic model is proposed. Linear and nonlinear stability analysis is used to investigate the proposed model theoretically. The approach of reductive perturbation is used to derive the modified Korteweg–de Vries (mKdV) equation. Density waves in the structure of kink–antikink soliton waves around the critical point are formed. Further, numerical simulations are carried out to validate the theoretical predictions, confirming that incorporating the predictive effect into a traffic system may decrease traffic congestion more efficiently.
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© The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
