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Abstract

Transportation agencies have adopted context-based classification systems that classify roadways based on the surrounding environment and user types. This offers a more comprehensive and multimodal perspective than traditional functional classification. While the Kentucky Transportation Cabinet (KYTC) has begun using project-level context classification, the agency will benefit from introducing network-level context classification. This will improve guidance, enhance project prioritization, and support the development of projects that better address the needs of all users. Responding to this need, Kentucky Transportation Center (KTC) researchers, in conjunction with KYTC staff, created a GIS-based model to build a context classification network that covers all state-maintained roadways and locally maintained roadways with functional classifications of collector or arterial. The model utilizes readily available data, including building density, building area density, intersection density, and existing urban and rural functional classifications. After KYTC reviewed the initial context classifications, the full context classification network was updated based on their feedback. The Cabinet should regularly update the network to account for land use changes, redrawn urban area boundaries, and modified functional classifications. Because the context classification network has many applications for transportation planning, design, operations, and maintenance, it should be shared widely so that KYTC staff and external stakeholders can access it.

Report Date

6-2026

Report Number

KTC-26-28

Digital Object Identifier

https://doi.org/10.13023/ktc.rr.2026.28

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