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To help mitigate road congestion caused by the unrelenting growth of trafficdemand, many transportation authorities have implemented managed lane policies,which restrict certain freeway lanes to certain types of vehicles. It wasoriginally thought that managed lanes would improve the use of existinginfrastructure through demand-management behaviors like carpooling, butimplementations have often been characterized by unpredicted phenomena that aresometimes detrimental to system performance. The development of traffic modelsthat can capture these sorts of behaviors is a key step for helping managedlanes deliver on their promised gains. Towards this goal, this paper presentsan approach for solving for driver behavior of entering and exiting managedlanes at the macroscopic (i.e., fluid approximation of traffic) scale. Ourmethod is inspired by recent work in extending a dynamic-system-based modelingframework from traffic behaviors on individual roads, to models at junctions,and can be considered a further extension of this dynamic-system paradigm tothe route/lane choice problem. Unlike traditional route choice models that areoften based on discrete-choice methods and often rely on computing andcomparing drivers' estimated travel times from taking different routes, ourmethod is agnostic to the particular choice of physical traffic model and issuited specifically towards making decisions at these interfaces using onlylocal information. These features make it a natural drop-in component to extendexisting dynamic traffic modeling methods.

A Dynamic-System-Based Approach to Modeling Driver Movements Across General-Purpose/Managed Lane Interfaces