Electric cars (ECs) play a vital role in reducing carbon emissions and improving sustainable development. Due to the lack of public charging facilities, the application of private ECs is limited. Motivated by the sharing economy, this is the first study to investigate the idea of sharing electric bus (EB) charging stations to alleviate the plight of private EC owners. However, existing EB charging strategies do not cater to the sharing and hinder the implementation of the policy. Therefore, this paper proposed a general mathematic mixed-integer non-linear programming model to coordinate the optimal charging strategy and sharing operation to meet the external and internal goals of bus systems, namely, maximizing charging station availability and satisfying the EB charging demand. Harnessing real-world bus operating data, the proposed model effectively generates multiple charging strategies. The results show that some hybrid strategies can achieve a similar sharing availability period as the public-oriented strategy with lower costs. In addition, sensitivity analysis indicates that increasing battery capacity can extend the sharing availability period while increasing charging power has only a minor impact. Overall, the proposed model obtains desired charging scheduling and provides concrete suggestions to promote the sustainable development of ECs and EBs.

Connected and Autonomous Vehicles (CAVs) are expected to reshape future transportation systems. During the long transition period, in which CAVs and human-driven vehicles (HVs) coexist, deploying CAV-dedicated lanes offers a promising approach to enhancing overall efficiency, but raises concerns about distributional fairness. This study develops a system-level evaluation framework that integrates bi-level network capacity optimization with practical planning constraints to determine optimal lane-deployment strategies. The bi-level model aims to maximize network reserve capacity at the upper level, while it captures mixed-traffic flow distribution under the lower-level user equilibrium (UE) principle. Both levels are constrained by CAV market penetration (MPR), social equity, and budget bound considerations. To ensure computational tractability, nonlinear relationships are linearized through Piecewise Linear Approximation (PLA), converting the original Mixed-Integer Nonlinear Programming (MINLP) model into a Mixed-Integer Linear Programming (MILP) formulation solvable by standard optimization solvers. Numerical experiments on the Sioux Falls network demonstrate that increasing MPR and dedicated lane deployment can substantially improve network capacity by up to 36% compared with the baseline, with diminishing marginal benefits as deployment scale excesses. Incorporating equity constraints further reduce the HV–CAV cost gap, promoting fairer outcomes without significant efficiency loss. These findings offer quantitative evidence on the efficiency–equity trade-offs in CAV-dedicated lanes planning and provide practical implications for policymakers in developing sustainable strategies.

During the early stages of autonomous vehicle (AV) adoption, traditional human-driven vehicles (HVs) and AVs will share urban roads—potentially diminishing the capacity benefits of AVs; thus, dedicated infrastructure strategies, such as AV-exclusive lanes and AV/Toll (AVT) lanes, have been proposed in the literature. While these approaches enhance overall travel efficiency in mixed traffic networks, they often neglect social equity concerns. In particular, the benefits of dedicated infrastructure are largely felt by AV users, while HV users experience a disproportionate increase in equilibrium travel time, negatively impacting social equity. This study optimizes AVT lane toll rates to balance efficiency and equity, ensuring a fair distribution of transportation impacts across user groups. New measurement formulas are introduced to quantify spatial and social equity based on disparities in generalized equilibrium travel costs across different origin–destination pairs and travel modes after an AVT tolling scheme. An equitable AVT tolling model, grounded in fuzzy utility theory, is developed, and a numerical example demonstrates its effectiveness in addressing spatial and social equity concerns in AVT lane tolling contexts.