Mitigating traffic oscillation through control of connected automated vehicles: A cellular automata simulation

Abstract

With the advent and advancement of connected and automated vehicle technologies, it is now possible to control connected and automated vehicles (CAVs) in mixed traffic flows to reduce traffic oscillations and enhance traffic flow performance. Recently, a control strategy for autonomous vehicles (AVs) named “The Follower Stopper controller” (FS) has been proposed. However, the existing studies for the FS strategy only considered the situation that all CAVs execute the FS strategy individually. And the impact on the mixed traffic flow when CAVs in the mixed traffic flow execute FS strategies as platoons is not investigated. To address this limitation, this paper proposes a control strategy for CAVs that considers the driving behavior of CAVs platoons based on the FS strategy, which allows CAVs to execute the FS strategy as a platoon. Then, a cellular automaton model of mixed traffic flow is developed based on the proposed strategy. Finally, a numerical simulation is conducted to analyze the impacts of the proposed strategy on traffic efficiency, traffic congestion, traffic oscillation, vehicle fuel consumption, and pollutant emissions under different penetration rates (PRs) of CAVs and traffic densities. Moreover, a comparative analysis with the FS strategy was conducted to verify the effectiveness and superiority of the proposed strategy. The result shows that (1) the proposed strategy can effectively mitigate traffic oscillations and reduce congestion. The improvement effect of the proposed control strategy on the mixed traffic flow is significantly affected by the penetration rate of CAVs as well as the traffic density. (2) Compared with the FS strategy, the proposed strategy has better performance in improving traffic efficiency, alleviating traffic oscillations, relieving congestion, and reducing fuel consumption and pollutant emissions under different traffic conditions. (3) The effectiveness of the FS strategy in improving the performance of mixed traffic flow is greatly limited by traffic density. There is a significant marginal utility of the FS strategy in improving traffic flow performance under high traffic density. However, the proposed strategy overcomes the limitations imposed by high traffic densities. The proposed strategy is highly adaptable to diverse traffic densities and can continuously enhance traffic flow performance as the penetration rate of CAVs rises.