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

Freeway Lane Management Approach in Mixed Traffic Environment with Connected Autonomous Vehicles