Structured-Corridor Safety-State Avoidance for Unmanned Ground Support Equipment at Aircraft Stands

Aircraft stands impose asymmetric spatial and procedural constraints that cannot be represented by geometric free space alone. This study proposes a Structured Operation Corridor for unmanned ground support equipment (SOC-UGSE), which converts existing stand markings, aircraft-side boundaries, and operating rules into machine-interpretable corridor constraints and corridor-specific actions. The framework distinguishes a detour-permitted Longitudinal Transfer Corridor (LTC-UGSE) from a no-detour Lateral Service-Approach Corridor (LSAC-UGSE), and maps object class, motion state, distance, corridor occupancy, and available clearance to Normal, Warning, or Stop responses. Standard vision, ranging, LiDAR, and temporal-processing modules are used only to instantiate these decision variables. On a controlled 1:10-scale platform, the implemented perception chain achieved an overall corridor-perception success of 83.9%, while frame-level agreement with rule-derived reference states reached 90.95%. Across 63 independent interaction sequences, sequence-level success was 95.2%, with no complete missed-stop event or prohibited boundary crossing. In a separate balanced comparison of 150 sequences, SOC-UGSE achieved the highest overall scenario-response compliance of 94.7%, outperforming distance-only stopping and corridor-free obstacle avoidance by reducing unnecessary stops and prohibited actions, respectively. These results support the structured-corridor rule-execution concept under controlled scaled-platform conditions, rather than full-scale operational safety or deployment readiness.

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Publication Details

Journal
Aerospace
Published
2026-09-09
DOI
https://doi.org/10.3390/aerospace13090820
Primary Topic
Air Traffic Management and Optimization
Type
article
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article

Structured-Corridor Safety-State Avoidance for Unmanned Ground Support Equipment at Aircraft Stands

Hongbin Liu, Zhiqiang Zhang, Liang Zeng, Ke Tang et al.
Aerospace
Air Traffic Management and Optimization
article

Structured-Corridor Safety-State Avoidance for Unmanned Ground Support Equipment at Aircraft Stands

Hongbin Liu, Zhiqiang Zhang, Liang Zeng, Ke Tang, Mengyuan Lu, Di Zhu, Xinping Zhu
article en

Abstract

Aircraft stands impose asymmetric spatial and procedural constraints that cannot be represented by geometric free space alone. This study proposes a Structured Operation Corridor for unmanned ground support equipment (SOC-UGSE), which converts existing stand markings, aircraft-side boundaries, and operating rules into machine-interpretable corridor constraints and corridor-specific actions. The framework distinguishes a detour-permitted Longitudinal Transfer Corridor (LTC-UGSE) from a no-detour Lateral Service-Approach Corridor (LSAC-UGSE), and maps object class, motion state, distance, corridor occupancy, and available clearance to Normal, Warning, or Stop responses. Standard vision, ranging, LiDAR, and temporal-processing modules are used only to instantiate these decision variables. On a controlled 1:10-scale platform, the implemented perception chain achieved an overall corridor-perception success of 83.9%, while frame-level agreement with rule-derived reference states reached 90.95%. Across 63 independent interaction sequences, sequence-level success was 95.2%, with no complete missed-stop event or prohibited boundary crossing. In a separate balanced comparison of 150 sequences, SOC-UGSE achieved the highest overall scenario-response compliance of 94.7%, outperforming distance-only stopping and corridor-free obstacle avoidance by reducing unnecessary stops and prohibited actions, respectively. These results support the structured-corridor rule-execution concept under controlled scaled-platform conditions, rather than full-scale operational safety or deployment readiness.

AerospaceVol. 13(9)
Manchester Airport (GB), Civil Aviation Flight University of China (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 7%
Air Traffic Management and Optimization
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