Facility connectivity plays a pioneering role in the Belt and Road Initiative proposed by General Secretary Xi Jinping in 2013. Xinjiang, as the core area of the Silk Road Economic Belt bordering eight Eurasian countries, plays a crucial role in cross-border transportation and humanistic exchanges and is the focus of the national connectivity initiative. While the current analysis on regional accessibility has become more diversified, analyses on long-distance cross-border corridors are still relatively rare. Therefore, this paper takes the Xinjiang Uygur Autonomous Region (XUAR) of China as the main study area extending westward to the five Central Asian countries. Modified accessibility accounting methods and gravity models are used to analyze the current status of accessibility and the strength of economic ties between Xinjiang and the five Central Asian countries. The results showed that the distance decay effect of transportation accessibility between Xinjiang and the five Central Asian countries is obvious; the constraints of “natural geography + transportation economy” affect the accessibility level from each state in Xinjiang to the five Central Asian countries and shows a trend of strength in the north and weakness in the south. From the optimization of the regional planning road network in a reverse projection, G3033 and other highways and the construction of the Yi-A railroad will improve the status quo of “east-west access but not north-south access” in Xinjiang. The “corridor effect” and spatial polarization characteristics of economic connection intensity from Xinjiang to the five Central Asian countries are significant. This study has important theoretical and practical significance for the construction of cross-border corridors.

Sustainable urban freight logistics requires routing decisions that jointly account for operating cost, vehicle technology, low-emission-zone (LEZ) access, terrain-sensitive energy use, and battery feasibility. This study develops a policy–terrain-coupled mixed-fleet routing framework integrating LEZ exposure, system-level carbon settlement, terrain-sensitive energy consumption, electric-vehicle (EV) battery feasibility, and route-level EV/internal-combustion-engine vehicle reassignment within a unified daily total operational cost (DTOC) evaluator. An adaptive large-neighborhood search (ALNS) procedure reconstructs feasible routes, while vehicle type is re-evaluated through counterfactual comparison of the complete system objective. The main experiments use 60 enhanced Gehring–Homberger benchmark-derived scenarios and 20 independent seeds, supplemented by ablation, carbon-price, EV-fixed-cost, heuristic-weight, convergence, and customer-scale scalability analyses. The ALNS-based framework achieves the lowest mean DTOC among the tested procedures, albeit with higher runtime. Policy and terrain information alter modeled fleet composition, with topology-dependent cost effects. Lower EV fixed costs consistently increase EV share, whereas carbon-price effects vary across network structures. All runs in the additional 200–1000-customer tests were feasible, although runtime increased with problem size. London- and Madrid-informed cases are treated as archetypes rather than as real-world validation cases. These results provide a basis for scenario screening and comparative planning of policy–terrain interactions before city-specific calibration and deployment.