Traffic Signal Timing and Trajectory Optimization in a Mixed Autonomy Traffic Stream
This study introduces a methodology for cooperative signal timing and trajectory optimization at intersections with a mix of connected automated vehicles (CAVs) and human-driven vehicles (HVs). The authors represent joint signal timing and trajectory control as a mixed-integer non-linear program, which is computationally complex. The developed methodology provides a balance between computational efficiency and solution quality by (a) linearizing the nonlinear constraints and reformulating the problem with a tight convex hull of the mixed-integer solutions and (b) decomposing the intersection-level program into several lane-level programs. Hence, a unique controller jointly optimizes the trajectories of CAVs on a lane and the signal timing parameters associated with that lane. This setting will allow finding near-optimal solutions with small duality gaps for complex intersections with different demand levels. Case study results show that the proposed methodology finds solutions efficiently with at most 0.1% duality gap. The authors compared the developed methodology with an existing signal timing and trajectory control approach and found 13% to 41% reduction in average travel time and 1% to 31% reduction in fuel consumption under different scenarios.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
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Supplemental Notes:
- Copyright © 2022, IEEE.
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Authors:
- Tajalli, Mehrdad
- Hajbabaie, Ali
- Publication Date: 2022-7
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 6525-6538
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Serial:
- IEEE Transactions on Intelligent Transportation Systems
- Volume: 23
- Issue Number: 7
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 1524-9050
- Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Connected vehicles; Optimization; Traffic signal timing; Vehicle mix; Vehicle trajectories
- Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting;
Filing Info
- Accession Number: 01855180
- Record Type: Publication
- Files: TRIS
- Created Date: Aug 22 2022 9:35AM