Original scientific paper
https://doi.org/10.7307/ptt.v38i5.1223
Coordinated Optimisation Model of Ramp Merging Sequences and Trajectories in Mixed Traffic
Weijing Zhu
; Guangxi Science and Technology Information Network Centre, Nanning, China
Sining Yu
; School of Architecture and Transportation Engineering, Guilin University of Electronic Technology, Guilin, China
Tao Wang
; Guangxi Key Laboratory of Intelligent Transportation System, Nanning Research Institute, Guilin University of Electronic Technology, Nanning, China
Chaoqiang Tian
; School of Architecture and Transportation Engineering, Guilin University of Electronic Technology, Guilin, China
Xiongcai Gan
; School of Architecture and Transportation Engineering, Guilin University of Electronic Technology, Guilin, China
Xiaoqin Zhou
; Guangxi Transport Vocational and Technical College, Nanning, China
*
* Corresponding author.
Abstract
The long-term coexistence of connected and automated vehicles (CAVs) and human-driven vehicles (HDVs) in mixed traffic flows will continue to significantly impact merg-ing behaviours and operational efficiency in freeway on-ramp merging areas. To improve merging efficiency at freeway on-ramps, this paper proposes a cooperative merging model for mixed traffic. First, the merging points for ramp vehicles are determined based on vehi-cle interaction characteristics in the merging area. Then, for the dynamic decision-making problem of merging sequences, considering the differences in cooperative merging be-tween CAVs and HDVs, the optimal merging sequence for both single-vehicle and multi-vehicle platoon merging is determined by minimising the global deviation between the actual travel time and the expected minimum travel time. Finally, according to the prede-termined merging sequence, a bidirectional speed guidance strategy based on virtual vehi-cle mapping is designed for both mainline and ramp vehicles to achieve cooperative opti-misation of the merging sequence and vehicle trajectories, enabling the smooth merging of ramp vehicles into the mainline. Simulations verify that the proposed method performs better than FIFO and effectively improves merging efficiency under different CAV penetra-tion rates. Particularly in low-to-medium penetration scenarios, it achieves a 25% delay optimisation rate and 22% reduction in travel time, with the optimisation effect improving to varying degrees as penetration rates increase. This establishes a foundation for traffic analysis and cooperative control in freeway on-ramp merging areas under mixed traffic en-vironments.
Keywords
connected and automated vehicles; ramp merging area; vehicle cooperative control meth-ods; mixed traffic
Hrčak ID:
347511
URI
Publication date:
27.5.2026.
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