Look-Ahead Driving Schemes for Efficient Control of Automated Vehicles on Urban Roads
Recently developed efficient driving schemes usually solve a predictive optimization problem or determining the vehicle control input, and at the expense of high computational cost, they improve the overall traffic flows and individual driving performances on urban roads. This paper presents a more practical technique for automated vehicles’ predictive driving by extending the existing adaptive cruise control (ACC) scheme with a look-ahead functionality. Such a look-ahead driving scheme (LDS) predicts the states of the preceding vehicle at an adaptive look-ahead time step and, with negligible computation costs, computes the vehicle control input more circumspectly for efficient driving in urban traffic. The proposed LDS is evaluated in typical urban traffic at the signalized intersections by observing the intersection utilization, flowing characteristics, and individual vehicles’ fuel efficiency. Furthermore, the authors also evaluate the influences of the LDS-vehicles’ penetration rates on overall traffic performances at various traffic volumes.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/00189545
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Supplemental Notes:
- Copyright © 2022, IEEE.
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Authors:
- Kamal, Md Abdus Samad
- Hashikura, Kotaro
- Hayakawa, Tomohisa
- Yamada, Kou
- Imura, Jun-ichi
- Publication Date: 2022-2
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 1280-1292
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Serial:
- IEEE Transactions on Vehicular Technology
- Volume: 71
- Issue Number: 2
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 0018-9545
- Serial URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=25
Subject/Index Terms
- TRT Terms: Advanced vehicle control systems; Autonomous intelligent cruise control; Intelligent vehicles; Predictive models; Signalized intersections; Urban highways
- Subject Areas: Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01837089
- Record Type: Publication
- Files: TRIS
- Created Date: Feb 25 2022 8:58AM