@article{ref1,
title="Cooperative decision-making for mixed traffic: a ramp merging example",
journal="Transportation research part C: emerging technologies",
year="2020",
author="Sun, Zhanbo and Huang, Tianyu and Zhang, Peitong",
volume="120",
number="",
pages="e102764-e102764",
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.<p /> <p>Language: en</p>",
language="en",
issn="0968-090X",
doi="10.1016/j.trc.2020.102764",
url="http://dx.doi.org/10.1016/j.trc.2020.102764"
}