NDLI: Manoeuvre prediction and planning for automated and connected vehicles based on interaction and gaming awareness under uncertainty

Content Provider	IET Digital Library
Author	Hu, Manjiang Xie, Guotao Gao, Hongbo Cao, Dongpu Li, Keqiang
Abstract	The complex and mixed traffic environment makes it a challenge for the widespread use of automated and connected vehicles (ACVs). It is necessary for these systems to have a better understanding of the traffic environment including interaction and gaming between multiple vehicles. In this study, a manoeuvre prediction and planning framework is proposed on the basis of game theories for complex and mixed traffic scenarios via vehicle-to-everything communication. In this framework, the interaction and gaming between multiple vehicles are considered by employing the extensive form game theories. In the payoff function, the risk assessment model based on trajectory prediction under uncertainty is employed to assess collision risks. Driving efficiency and preference are also combined in the payoff function. Uncertainty elements, including estimation and prediction, are considered to predict and plan by using Nash equilibrium of the extensive form game theory in mixed and behavioural strategies. Finally, this framework is applied and proved in different lane-change scenarios. The results show that this framework could predict other vehicles’ driving manoeuvres and plan manoeuvres for ego vehicles by considering interaction and gaming between multiple vehicles, which helps ACVs understand the environment better and make the cooperative manoeuvre planning in complex traffic scenarios.
Starting Page	933
Ending Page	941
Page Count	9
ISSN	1751956X
Volume Number	13
e-ISSN	17519578
Issue Number	Issue 6, Jun (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-its/13/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-its.2018.5353
Journal	IET Intelligent Transport Systems
Publisher Date	2018-12-03
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	ACVs Automated Connected Vehicle Automated Vehicle Behavioural Strategy Collision Avoidance Complex Traffic Environment Complex Traffic Scenarios Ego Vehicle Estimation Extensive Form Game Theory Game Theories Game Theory Gaming Awareness Manoeuvre Planning Manoeuvre Prediction Mixed Strategy Mixed Traffic Environment Mixed Traffic Scenario Multiple Vehicle Payoff Function Planning Framework Risk Assessment Model Risk Management Road Traffic Road Vehicle Spatial Variables Control Telecommunication Traffic Traffic Engineering Computing Traffic Environment Including Interaction Trajectory Prediction Uncertainty Element Vehicle-to-everything Communication
Content Type	Text
Resource Type	Article
Subject	Law Transportation Environmental Science Mechanical Engineering

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