A Framework for Self-Enforced Optimal Interaction Between Connected Vehicles

被引：6

作者：

Stryszowski, Marcin ^{[1
]}

Longo, Stefano ^{[1
]}

D'Alessandro, Dario ^{[2
]}

Velenis, Efstathios ^{[1
]}

Forostovsky, Gregory ^{[3
]}

Manfredi, Sabato ^{[2
]}

机构：

[1] Cranfield Univ, Adv Vehicle Engn Ctr, Cranfield MK43 0AP, Beds, England

[2] Univ Naples Federico II, Dept Elect Engn & Informat Technol DIETI, I-80138 Naples, Italy

[3] Arrival Ltd, London W1G 0EG, England

来源：

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | 2021年 / 22卷 / 10期

基金：

英国工程与自然科学研究理事会;

关键词：

Mechanical power transmission; Games; Aerodynamics; Game theory; Cost function; Connected vehicles; Connected cars; game theory platooning; negotiation; overtake; V2V; TRANSPORTATION; COMMUNICATION; OPTIMIZATION;

D O I：

10.1109/TITS.2020.2988150

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

This paper proposes a decision-making framework for Connected Autonomous Vehicle interactions. It provides and justifies algorithms for strategic selection of control references for cruising, platooning and overtaking. The algorithm is based on the trade-off between energy consumption and time. The consequent cooperation opportunities originating from agent heterogeneity are captured by a game-theoretic cooperative-competitive solution concept to provide a computationally feasible, self-enforced, cooperative traffic management framework.

引用

页码：6152 / 6161

页数：10

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