The use of connected autonomous vehicles (CAVs) can help reduce gaps between vehicles. However, smaller gaps may cause challenges for on-ramp vehicles merging into the freeway. This study introduces several strategies that allow on-ramp vehicles to merge safely and efficiently to the mainline by providing adequate merging gaps or resolving merging conflicts in a mixed traffic environment. Eight methods are proposed to facilitate merging. These strategies are simulated in a mixed traffic environment and with different traffic characteristics, including different proportions of CAVs. The results indicate that operational performance is affected by CAV penetration rate and traffic management strategy. For relatively low freeway traffic volume, or 100% CAV penetration rate, traffic operations under the do-nothing option performs almost as well as the best traffic management strategy. However, at lower CAV penetration rates and high freeway traffic volumes, the proposed strategies are more viable than the do-nothing option.

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The connected autonomous vehicle (CAV) is the most significant breakthrough in the automobile industry since the wide adoption of automobiles as a mode of transportation. These vehicles can respond faster, drive more precisely within their lane, and keep gaps shorter than driver-operated vehicles (DVs). Therefore, they can improve traffic operations and reduce collisions resulting from human errors. However, shorter gaps on the freeway right lane (FRL) can create difficulty for on-ramp vehicles to merge onto the freeway. In addition, there is a transition period from all DVs to all CAVs. As a result, there would be a mixed traffic environment including DVs and CAVs, which might necessitate different merging management strategies.This study proposes eight possible solutions to address the merging problems by providing acceptable gaps or resolving the conflicts between merging and mainline vehicles in a mixed traffic environment. These strategies are then evaluated based on different measures to determine which merging solution is most effective for each traffic condition. Average travel times and the capacity drop are used as traffic performance measures, while safety measures include the percentage of vehicles with low merging speed (VLMS) and probability of non-compliance (PNC) of merging manoeuvre.The behaviour of CAVs and performance merging strategies are modelled using Vissim v2020, internal programing, and a MATLAB program. The simulation results indicate that when the CAV penetration rate is between 0% and 100%, most proposed strategies outperform the base condition of do-nothing. The traffic performance changes depending on the CAV penetration rate and the type of traffic management strategy.iiiThe results of the safety measure for most strategies based on the VLMS index indicate that at low traffic volumes, increasing CAV penetration rate reduces VLMS, thereby improving safety. At high traffic volume, some strategies such as dissolving platoons and ramp metering show better performance. For the PNC measure, most strategies have lower PNC and better expected safety performance than the base strategy.Furthermore, increasing the CAV penetration rate reduces PNC. Finally, a regression analysis between PNC and the existing collision database demonstrated a correlation between PNC and collision frequency.