  Connected autonomous vehicles (CAV) technologies are about to be in the
market in the near future. This requires transportation facilities ready to
operate in a mixed traffic environment where a portion of vehicles are CAVs and
the remaining are manual vehicles. Since CAVs are able to run with less spacing
and headway compared with manual vehicles or mixed traffic, allocating a number
of freeway lanes exclusive to CAVs may improve the overall performance of
freeways. In this paper, we propose an analytical managed lane model to
evaluate the freeway flow in mixed traffic and to determine the optimal number
of lanes to be allocated to CAVs. The proposed model is investigated in two
different operation environments: single-lane and managed lane environments. We
further define three different CAV technology scenarios: neutral, conservative,
and aggressive. In the single-lane problem, the influence of CAV penetration
rates on mixed traffic capacity is examined in each scenario. In the managed
lanes problem, we propose a method to determine the optimal number of dedicated
lanes for CAVs under different settings. A number of numerical examples with
different geometries and demand levels are investigated for all three
scenarios. A sensitivity analysis on the penetration rates is conducted. The
results show that more aggressive CAV technologies need less specific allocated
lanes because they can follow the vehicles with less time and space headways.
