<p>Virtual coupling (VC) has attracted increasing research attention as a train control concept for rail systems, enabling trains to operate at very short separations using cooperative, relative distance-based control. This paper reviews how VC affects railway operations across three interconnected layers: operation control, transport organization and system-level performance evaluation. At the control layer, we synthesize research on separation and collision avoidance models, trajectory planning, formation and cooperative control, and uncertainty-aware control methods, covering both model predictive control-based designs and alternative control strategies that address parametric uncertainty, heterogeneous braking, delays and cyber-attacks. At the planning layer, we survey line planning, timetabling, rolling stock circulation, train constitution and rescheduling models that embed VC-enabled headway relaxation, dynamic (de)coupling and platoon composition as decision variables, linking VC to passenger-oriented capacity allocation and disruption management. At the evaluation layer, we review signaling system safety assessment, capacity and headway analysis, and energy and environmental studies that quantify VC impacts under realistic signaling, infrastructure, and disturbance conditions. A thematic–methodological mapping highlights the prevalence of optimization and model predictive control, the limited integration between control and passenger-oriented planning, and the currently limited body of evidence for high-speed and heavy-haul applications. The review identifies consistent modeling patterns, critical gaps, and implementation challenges, and proposes a realistic research roadmap for treating VC as an operational and service innovation rather than a purely signaling upgrade.</p>

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A Comprehensive Review of Virtually Coupled Train Systems

  • Qi Zhang,
  • Yuqi Liao,
  • Yuzhou Ji

摘要

Virtual coupling (VC) has attracted increasing research attention as a train control concept for rail systems, enabling trains to operate at very short separations using cooperative, relative distance-based control. This paper reviews how VC affects railway operations across three interconnected layers: operation control, transport organization and system-level performance evaluation. At the control layer, we synthesize research on separation and collision avoidance models, trajectory planning, formation and cooperative control, and uncertainty-aware control methods, covering both model predictive control-based designs and alternative control strategies that address parametric uncertainty, heterogeneous braking, delays and cyber-attacks. At the planning layer, we survey line planning, timetabling, rolling stock circulation, train constitution and rescheduling models that embed VC-enabled headway relaxation, dynamic (de)coupling and platoon composition as decision variables, linking VC to passenger-oriented capacity allocation and disruption management. At the evaluation layer, we review signaling system safety assessment, capacity and headway analysis, and energy and environmental studies that quantify VC impacts under realistic signaling, infrastructure, and disturbance conditions. A thematic–methodological mapping highlights the prevalence of optimization and model predictive control, the limited integration between control and passenger-oriented planning, and the currently limited body of evidence for high-speed and heavy-haul applications. The review identifies consistent modeling patterns, critical gaps, and implementation challenges, and proposes a realistic research roadmap for treating VC as an operational and service innovation rather than a purely signaling upgrade.