Cooperative decision-making for mixed traffic: A ramp merging example. (November 2020)

• Record Type: Journal Article
• Authors: Sun, Zhanbo; Huang, Tianyu; Zhang, Peitong
• Is Part Of: Transportation research. Volume 120(2020)
• Publication Date: 2020-11
• Subjects: Connected Automated Vehicles (CAVs) -- Cooperative decision-making for mixed traffic (CDMMT) -- Ramp merging -- Bi-level optimization -- Dynamic programming; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2020.102764
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: We studies cooperative decision-making for mixed traffic at ramp-merging sections. Cooperative and non-cooperative microscopic decisions are explicitly considered. The problem is solved using a bi-level dynamic programming-based approach. The proposed CDMMT Ramp Merging method guarantees system-efficient results. Abstract: The rapid conceptual development and commercialization of connected automated vehicle (CAV) has led to the problem of mixed traffic, i.e., traffic mixed with CAVs and conventional human-operated vehicles (HVs). The paper studies cooperative decision-making for mixed traffic (CDMMT). Using discrete optimization, a CDMMT mechanism is developed to facilitate ramp merging, and to properly capture the cooperative and non-cooperative behaviors in mixed traffic. The CDMMT mechanism can be described as a bi-level optimization program in which state-constrained optimal control-based trajectory design problems are imbedded in a sequencing problem. A bi-level dynamic programming-based solution approach is developed to efficiently solve the problem. The proposed modeling mechanism and solution approach are generic to deterministic decisions and can guarantee system-efficient solutions. A micro-simulation environment is built for model validation and analysis of mixed traffic. The results show that compared to the scenario with 100% HVs, ramp-merging can be smoother in mixed traffic environment. At high CAV penetration, the section throughput increases about 18%. With the proposed CDMMT mechanism, traffic throughput can be further increased by 10–15%. The proposed methods form the basis of traffic analysis and cooperative control at ramp-merging sections under mixed traffic environment.