An autonomous vehicle exclusive lane design problem under the mixed autonomy traffic environment: Model formulation and large-scale algorithm design - Wang, Ting; Li, Yao; Jia, Bin; Long, Jiancheng (Transportation research. Part E, Logistics and transportation review, 2024)
•Propose a bi-level autonomous vehicle (AV) exclusive lane design problem.•Describe the mixed routing equilibrium travel behavior of mixed traffic flows, where AVs can alter their equilibrium principle between user equilibrium and system optimum during a trip.•Treat the SO principle of AVs as an independent subproblem and formulate the mixed routing equilibrium problem as a variational inequality (VI) based model.•Develop a heuristic nested algorithm to solve the VI-based model in large-scale scenarios.•Illustrate the algorithm performances and model properties. With the development of self-driving, urban network will face a hybrid stage where both connected autonomous vehicles (CAVs) and human-driven vehicles (HDVs) coexist. Due to the ability of CAVs to share information and coordinate in real-time, the design of autonomous vehicle (AV)-exclusive lanes has received much attention as it is expected to improve traffic flow characteristics. This study proposes an AV-exclusive lane design problem (ALDP) for the road network. The ALDP is formulated as a bi-level programming model. The upper-level model deploys the optimal design of AV-exclusive lanes to reduce the total comprehensive cost. The lower-level problem describes the mixed routing equilibrium (MRE) travel behavior of CAVs and HDVs. Specifically, CAVs and HDVs follow the user equilibrium principle in general lanes, and CAVs on the exclusive lanes are controlled by the system to adopt the system optimum principle. To deal with large-scale scenarios, a heuristic nested algorithm is developed for solving the lower-level MRE traffic assignment problem. Two acceleration strategies, namely the technology-based strategy and the sensitivity analysis-based strategy, are developed to speed up the solution process. Besides, a kriging surrogate-based optimization algorithm is designed to solve the bi-level ALDP. Numerical experiments demonstrate that the nested algorithm achieves high-precision solution with fast computational speed when solving the MRE problem in real-world traffic networks. Additionally, the implementation of the AV-exclusive lanes design scheme significantly improves the overall performance of the network in terms of total system travel time. This study provides new insights into future hybrid phase facility construction and management strategies.