Efficient and environmentally friendly operation of intermittent dedicated lanes for connected autonomous vehicles in mixed traffic environments

Abstract

The emergence of connected autonomous vehicles (CAVs) provides a possibility to develop an efficient and sustainable mobility option. To foster the adoption of CAVs, the dedicated CAV lanes have been widely discussed in terms of optimal planning and allocating infrastructures for CAVs. Meanwhile, a sensible operation manner of dedicated lanes is also crucial to reap the maximum benefits. In this paper, we propose a novel idea, i.e., the intermittent dedicated CAV lanes (IDCLs), which dynamically provide a separate right-of-way for human-driven vehicles (HVs) to maximize traffic efficiency and minimize environmental costs. To this end, we first tailor two multi-class queuing models as fundamental tools to evaluate the traffic state. A traffic emission model is proposed based on the proposed queuing models. Then, a queuing-based bi-objective optimization model, which aims to maximize the traffic throughput and minimize the green tax simultaneously, is developed for the optimal operation of IDCL. Subsequently, the non-dominated sorting genetic algorithm-II (NSGA-II) is employed to find the Pareto optimal solutions. Finally, numerical experiments are conducted under different market penetration rates (MPRs) of CAVs and various traffic intensities. The results reported in this paper help policymakers and authorities draw insights into the IDCL policy.