Wei, C orcid.org/0000-0002-4565-509X, Romano, R orcid.org/0000-0002-2132-4077, Merat, N orcid.org/0000-0003-4140-9948 et al. (5 more authors) (2019) Risk-based autonomous vehicle motion control with considering human driver’s behaviour. Transportation Research Part C: Emerging Technologies, 107. pp. 1-14. ISSN 0968-090X
Abstract
The selected motions of autonomous vehicles (AVs) are subject to the constraints from the surrounding traffic environment, infrastructure and the vehicle’s dynamic capabilities. Normally, the motion control of the vehicle is composed of trajectory planning and trajectory following according to the surrounding risk factors, the vehicles’ capabilities as well as tyre/road interaction situations. However, pure trajectory following with a unique path may make the motion control of the vehicle be too careful and cautious with a large amount of steering effort. To follow a planned trajectory, the AVs with the traditional path-following control algorithms will correct their states even if the vehicles have only a slight deviation from the desired path or the vehicle detects static infrastructure like roadside trees. In this case, the safety of the AVs can be guaranteed to some degree, but the comfort and sense of hazards for the drivers are ignored, and sometimes the AVs have unusual motion behaviours which may not be acceptable to other road users. To solve this problem, this study aims to develop a safety corridor-based vehicle motion control approach by investigating human-driven vehicle behaviour and the vehicle’s dynamic capabilities. The safety corridor is derived by the manoeuvring action feedback of actual drivers as collected in a driving simulator when presented with surrounding risk elements and enables the AVs to have safe trajectories within it. A corridor-based Nonlinear Model Predictive Control (NMPC) has been developed which controls the vehicle state to achieve a smooth and comfortable trajectory while applying trajectory constraints using the safety corridor. The safety corridor and motion controller are assessed using four typical scenarios to show that the vehicle has a human-like or human-oriented behaviour which is expected to be more acceptable for both drivers and other road users.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Elsevier Ltd. This is an author produced version of a paper published in Transportation Research Part C: Emerging Technologies. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Risk-based corridor; Autonomous vehicles; Model predictive control; Trajectory; Human-like |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Safety and Technology (Leeds) |
Funding Information: | Funder Grant number Innovate UK fka Technology Strategy Board (TSB) 84063-528134 |
Depositing User: | Symplectic Publications |
Date Deposited: | 10 Sep 2019 13:00 |
Last Modified: | 05 May 2021 16:07 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.trc.2019.08.003 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:150669 |