## 5 Results and Discussion
### Spatial Interaction Between HDT Behaviors and Clustered Freight Zones
#### 5.4.5. Fence-Sided Truck (FT)  
Figure 13 shows a systematic analysis of the trip patterns of FTs. As general-purpose vehicles tailored for SME cargo transport, FTs exhibit a spatial distribution characterized by a concentration in small-merchant clusters alongside flexible adaptation to multi-scenario transportation needs. A Sankey diagram analysis reveals that Cluster 2 (46.98%) and Cluster 4 (26.03%) account for over 73% of FT trips, with Cluster 1 (19.73%) primarily serving small-and-medium-sized manufacturing enterprises that are hub-adjacent. This pattern aligns closely with FTs' functional attributes: their open side-fenced design facilitates the loading/unloading of irregular cargo (e.g., building materials, furniture, and steel), making them ideal for multi-batch, small-volume, non-standardized transport demands. This precisely matches the small industrial agglomeration function of Cluster 2 and the commercial-industrial mixed zone role of Cluster 4.  
The spatial heatmap analysis shows FTs frequently operate in comprehensive markets and industrial clusters such as Malu Logistics Industrial Park, Baoshan Steel Processing Zone, Minhang Manufacturing Cluster, and Zhujing Building Materials Wholesale Market. These nodes share the characteristics of having a prominent SME presence and regional cargo distribution. For example, FTs in Baoshan Steel Processing Zone handle the short-haul transport of processed steel to construction sites, while those in GM Jinqiao support the supply chains between component manufacturing and OEM assembly, exemplifying the synergy between regional production networks and flexible transport tools. The high ID entropy in these areas indicates that transport demand is predominantly met by individual drivers or small logistics firms, consistent with SMEs' reliance on market-driven capacity, a reflection of the fragmented demand and diverse market participants.  
Figure 12: Systematic analysis of trip patterns of dump trucks. The upper two subplots depict heatmaps of trip ends and trips, respectively. The Sankey diagram in the lower-left corner illustrates the proportions of DT trips across clustered functional zones, while the ID entropy heatmap in the lower-right corner visualizes entropy values in grid cells with high trip volumes.  
The concentration metrics (\(HHI_{E}\) = 0.33 and \(HHI_{R}\) = 0.04), both below medium levels, reveal a dispersed agglomeration pattern: while trips cluster in Clusters 2 and 4, they lack the hub dominance seen in tractor trucks, instead forming a dispersion pattern across multiple SME clusters. This reflects their broad coverage of peripheral markets, exacerbated by the scattered nature of transported goods (steel, furniture, and hardware) and their application in diverse scenarios. In contrast to STs' industrial node radiation and DTs' infrastructure-logistics linkage, FTs' agglomeration in industrial support zones, integrated logistics parks, and comprehensive markets highlights their role as connective tissues between core industrial clusters and peripheral suppliers. They provide both short-haul component delivery for large manufacturers (e.g., GM, Cluster 2) and end-user transport for supporting merchants (e.g., furniture market-to-residence delivery, Cluster 4), serving as critical intermediaries between scaled production and the fragmented demand in urban freight networks.  
In summary, FTs' spatial interaction model is a joint product of SME demand, vehicle versatility, and regional functional gradients. The high penetration in Cluster 2 stems from the need for flexible industrial support transport, the activity in Cluster 4 reflects diverse commercial delivery scenarios, and the moderate concentration metrics embody multi-stakeholder participation and multi-cargo adaptability.