Abstract
In transportation networks, access management is the systematic approach to control the location, spacing, design, and operation of residential and commercial access points, where a main goal is to preserve the safety and capacity of the system. The literature describes how access management programs can help in saving billions of dollars by reducing the number of crashes and improving road capacity. However, it is common for transportation agencies to have limited resources, including budgets, equipment, time, human resources, and others, and thus they need a framework to prioritize their access management needs among hundreds of thousands of access points. While current prioritization frameworks in the transportation literature have several limitations, this research develops a prioritization framework that combines data-driven quantitative analysis with modeling and expertise of transportation professionals to prioritize access management projects that focus on safety improvement. This will be accomplished by identifying a set of site-specific (quantitative and qualitative) factors that represent engineering characteristics of locations where access points are located and have an impact on the safety of road users. Next, these factors are used to develop a classification criterion to classify each access point into two categories (in terms of safety): critical and noncritical. "the results of this analysis are then demonstrated spatially using innovative straight-line diagrams, where the main goal is to allow decision makers to easily identify and prioritize anomalous access points. To demonstrate the developed framework, it was applied to thousands of access points located on four major U.S. highway. The results of this demonstration should assist decision makers to prioritize these access points based on a safety improvement perspective.