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To help mitigate road congestion caused by the unrelenting growth of trafficdemand, many transit authorities have implemented managed lane policies.Managed lanes typically run parallel to a freeway's standard, general-purpose(GP) lanes, but are restricted to certain types of vehicles. It was originallythought that managed lanes would improve the use of existing infrastructurethrough incentivization of demand-management behaviors like carpooling, butimplementations have often been characterized by unpredicted phenomena that isoften to detrimental system performance.  This paper presents several macroscopic traffic modeling tools we have usedfor study of freeways equipped with managed lanes, or "managed lane-freewaynetworks." The proposed framework is based on the widely-used first-orderkinematic wave theory. In this model, the GP and the managed lanes are modeledas parallel links connected by nodes, where certain type of traffic may switchbetween GP and managed lane links. Two types of managed lane topologies areconsidered: full-access, where vehicles can switch between the GP and themanaged lanes anywhere; and separated, where such switching is allowed only atcertain locations called gates.  We also describe methods to incorporate in three phenomena into our modelthat are particular to managed lane-freeway networks. The inertia effectreflects drivers' inclination to stay in their lane as long as possible andswitch only if this would obviously improve their travel condition. Thefriction effect reflects the empirically-observed driver fear of moving fast ina managed lane while traffic in the adjacent GP lanes moves slowly due tocongestion. The smoothing effect describes how managed lanes can increasethroughput at bottlenecks by reducing lane changes. We present simple modelsfor each of these phenomena that fit within the general macroscopic theory.

Macroscopic Modeling, Calibration, and Simulation of Managed Lane-Freeway Networks, Part I: Topological and Phenomenological Modeling