A Universal Cooperative Decision-Making Framework for Connected Autonomous Vehicles With Generic Road Topologies

Cooperative decision-making of Connected Autonomous Vehicles (CAVs) presents a longstanding challenge due to its inherent nonlinearity, non-convexity, and discrete characteristics, compounded by the diverse road topologies encountered in real-world traffic scenarios. The majority of current methodol...

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Vydané v:	IEEE transactions on vehicular technology Ročník 74; číslo 4; s. 5414 - 5429
Hlavní autori:	Huang, Zhenmin, Liu, Wenru, Shen, Shaojie, Ma, Jun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.04.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Autonomous driving Autonomous vehicles connected autonomous vehicles (CAVs) Convexity cooperative decision-making Decision making Games Graph theory Graphical representations Integer programming Linear programming Merging Mixed integer Mixed integer linear programming mixed-integer linear programming (MILP) multi-agent systems non-convex optimization Optimization Roads Roads & highways Topology Trajectory Trajectory planning
ISSN:	0018-9545, 1939-9359
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