Optimal design of differentiated credit charging links in mixed-autonomy transportation networks

In this paper, we investigate a novel driveway management strategy, namely deploying au-tonomous vehicle/credit charging links in mixed-autonomy transportation networks. Such links are freely accessible for (connected) autonomous vehicles, while charging credits for human-driven vehicles. We formulate the mixed traffic equilibrium as a variational in-equality problem, based on which a bi-level programming model is proposed to simultane-ously determine the optimal location as well as the credit charge of these links. Then a ge-netic algorithm is applied to solve the bi-level problem, within which a gradient projection method is used to solve the lower-level problem. Numerical results reveal that deployment of such links further improves the network performance compared with the case where only a tradable credit scheme is implemented. We also find that different strategies are employed to deploy the differentiated charging links under different scenarios, which pro-vides useful insight for the practical implementation. Moreover, we investigate the credit trading market and find that connected autonomous vehicle users are more likely to be the beneficiary in the proposed scheme. In this regard, the proposed scheme also has the potential to propel the market penetration of connected autonomous vehicles. (c) 2022 Elsevier Inc. All rights reserved.