Lane management for asymmetric mixed traffic flow on bidirectional multi-lane roadways

Abstract

To manage the bidirectional asymmetric mixed traffic flow with connected and automated vehicles (CAVs) and human-driven vehicles, the study proposes a lane management (LM) model based on the joint policy of CAV dedicated lanes (CDLs), CAV reversible lanes (CRLs), and CAV access strategies (CASs) for non-managed lanes. An analytical model is developed to determine the optimal numbers of CDLs and CRLs and the optimal CASs that maximize overall mixed traffic throughputs, considering four parameters under aggressive, moderate, and conservative CAV technology scenarios. The results show that the LM policy can significantly improve overall throughputs compared with the benchmark policy by deploying optimal CDLs, CRLs, and/or CASs under the three scenarios. Moreover, for the LM policy, the overall throughput gradually rises, except for the asymptotical increments with the CAV penetration rate under the conservative scenario and the asymptotical reductions with the directional imbalance percent of traffic demand under the three scenarios.