349 enabling rapid identification of critical interactions and consistent tracking of risk conditions across operational zones, enabling safety teams to focus on interactions that may require operational attention according to site-defined prioritization criteria. Overall, Stage 2 provides an interpretable and auditable mechanism for contextual interpretation and prioritization of CAS interaction alerts under real operational constraints. 3.3. Risk Severity Aggregation and Propagation Analysis (Stage 3) Stage 3 performs an aggregated analysis of collision risk by integrating interaction severity indicators derived from CAS alerts, spatial distribution, and temporal recurrence to identify accumulatedrisk zones (hotspots). It transitions from individual event assessment to a macro-level characterization of operational risk. The step-based methodology is illustrated in Figure 3. The analysis uses georeferenced CAS alerts together with outputs from previous stages: (i) functional zone per event (Stage 1), (ii) estimated collision risk severity (Stage 2), and (iii) recurrence of interaction alerts as a measure of exposure. Figure 3 – Step-based methodology for spatial risk aggregation and propagation analysis in Stage 3. Step 1. Spatial discretization. The mine is discretized using a structured spatial partition designed to provide homogeneous and scalable analysis units across the operation. Each spatial unit represents an elementary analysis cell and serves as a node within the spatial risk model. Step 2. Aggregated risk assessment. Each spatial unit is assigned a normalized risk indicator that integrates the severity of alerts and their recurrence within the unit. This aggregation, defined using expert criteria from mine safety and CAS domains, captures both the intensity and persistence of risk at each location. Step 3. Spatial risk propagation modeling. To incorporate spatial dependencies beyond isolated events, the operation is represented through a spatial dependency model that accounts for interactions between neighboring units. This modeling approach captures proximity effects, operational continuity, and spatial relationships, which are characteristic of mining environments where risk conditions may extend across adjacent areas with similar operational characteristics. Step 4. Identification of operational hotspots. The output is an aggregated risk map highlighting hotspots associated with accumulated collision risk. This systemic perspective enables identification of critical zones from both operational and safety standpoints. Results are presented through a batch-based historical dashboard, allowing selection of analysis windows and exploration of spatial risk evolution. This supports retrospective evaluation and the definition of preventive measures such as speed adjustments, signage, traffic flow modifications, or targeted operational controls. Conceptually, Stage 3 operates as a mine safety digital shadow, focused on historical hotspot visualization while establishing the foundation for a digital twin with predictive and simulation-based safety
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