An Integrated Framework of Decision Making and Motion Planning for Autonomous Vehicles Considering Social Behaviors

Hang, Peng; Lv, Chen; Huang, Chao; Cai, Jiacheng; Hu, Zhongxu

doi:10.1109/tvt.2020.3040398

Cited by 132 publications

(68 citation statements)

References 42 publications

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“…The vehicle kinematic model is usually used to address the motion planning and control of vehicles at low-speed conditions, e.g., automatic parking control [65]. For motion control at high-speed conditions, the vehicle dynamic model is preferred [66].…”

Section: Vehicle Kinematic Modelmentioning

confidence: 99%

Towards Autonomous Driving: Review and Perspectives on Configuration and Control of Four-Wheel Independent Drive/Steering Electric Vehicles

Hang

Chen

2021

Actuators

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In this paper, the related studies of chassis configurations and control systems for four-wheel independent drive/steering electric vehicles (4WID-4WIS EV) are reviewed and discussed. Firstly, some prototypes and integrated X-by-wire modules of 4WID-4WIS EV are introduced, and the chassis configuration of 4WID-4WIS EV is analyzed. Then, common control models of 4WID-4WIS EV, i.e., the dynamic model, kinematic model, and path tracking model, are summarized. Furthermore, the control frameworks, strategies, and algorithms of 4WID-4WIS EV are introduced and discussed, including the handling of stability control, rollover prevention control, path tracking control and active fault-tolerate control. Finally, with a view towards autonomous driving, some challenges, and perspectives for 4WID-4WIS EV are discussed.

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Section: Vehicle Kinematic Modelmentioning

confidence: 99%

Towards Autonomous Driving: Review and Perspectives on Configuration and Control of Four-Wheel Independent Drive/Steering Electric Vehicles

Hang

Chen

2021

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“…In [88], a human-like decision making framework for autonomous vehicles is proposed, where the potential field method and MPC are used to plan the collision-avoidance path and provide predicted motion states for the human-like decision making module. An integrated framework to deal with the decision making and motion planning is presented in [89] for lanechange maneuvers, while considering social behaviors of surrounding traffic participants. In [90,91], an integrated decision-making and motion planning module is proposed in an MPC framework which incorporates the lane selection and a potential field in the objective function to improve comfortability.…”

Section: Motion Planning By Mpc For a Single Agvmentioning

confidence: 99%

Model predictive control for autonomous ground vehicles: a review

Hirche

Huang

et al. 2021

Auton. Intell. Syst.

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This paper reviews model predictive control (MPC) and its wide applications to both single and multiple autonomous ground vehicles (AGVs). On one hand, MPC is a well-established optimal control method, which uses the predicted future information to optimize the control actions while explicitly considering constraints. On the other hand, AGVs are able to make forecasts and adapt their decisions in uncertain environments. Therefore, because of the nature of MPC and the requirements of AGVs, it is intuitive to apply MPC algorithms to AGVs. AGVs are interesting not only for considering them alone, which requires centralized control approaches, but also as groups of AGVs that interact and communicate with each other and have their own controller onboard. This calls for distributed control solutions. First, a short introduction into the basic theoretical background of centralized and distributed MPC is given. Then, it comprehensively reviews MPC applications for both single and multiple AGVs. Finally, the paper highlights existing issues and future research directions, which will promote the development of MPC schemes with high performance in AGVs.

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“…But their decisions and actions are correlated, i.e. one's decision is made based on the constraints imposed by surrounding ones, and its behavior will also affect others in surround Yu et al, 2018;Hang et al, 2020a) . Besides, as a human has limited perception capability, the information one can obtain from the surrounding environment is limited (Dingus et al, 2016;Li and Busso, 2016;Kuo et al, 2019;.…”

Section: Introductionmentioning

confidence: 99%

Human-like Interactive Behavior Generation for Autonomous Vehicles: A Bayesian Game-theoretic Approach with Turing Test

Zhang¹,

Hang²,

Huang³

et al. 2021

Preprint

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Interacting with surrounding road users is a key feature of vehicles and is critical for intelligence testing of autonomous vehicles. The Existing interaction modalities in autonomous vehicle simulation and testing are not sufficiently smart and can hardly reflect human-like behaviors in real world driving scenarios. To further improve the technology, in this work we present a novel hierarchical game-theoretical framework to represent naturalistic multi-modal interactions among road users in simulation and testing, which is then validated by the Turing test. Given that human drivers have no access to the complete information of the surrounding road users, the Bayesian game theory is utilized to model the decision-making process. Then, a probing behavior is generated by the proposed game theoretic model, and is further applied to control the vehicle via Markov chain. To validate the feasibility and effectiveness, the proposed method is tested through a series of experiments and compared with existing approaches. In addition, Turing tests are conducted to quantify the human-likeness of the proposed algorithm. The experiment results show that the proposed Bayesian game theoretic framework can effectively generate representative scenes of human-like decision-making during autonomous vehicle interactions, demonstrating its feasibility and effectiveness. Corresponding author(s) Email: lyuchen@ntu.edu.sg

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An Integrated Framework of Decision Making and Motion Planning for Autonomous Vehicles Considering Social Behaviors

Cited by 132 publications

References 42 publications

Towards Autonomous Driving: Review and Perspectives on Configuration and Control of Four-Wheel Independent Drive/Steering Electric Vehicles

Towards Autonomous Driving: Review and Perspectives on Configuration and Control of Four-Wheel Independent Drive/Steering Electric Vehicles

Model predictive control for autonomous ground vehicles: a review

Human-like Interactive Behavior Generation for Autonomous Vehicles: A Bayesian Game-theoretic Approach with Turing Test

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