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Transportation Research Part C Emerging Technologies
Article . 2019 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2019
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
DBLP
Article . 2020
Data sources: DBLP
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Pay to change lanes: A cooperative lane-changing strategy for connected/automated driving

Authors: Dianchao Lin; Li Li; Saif Eddin Jabari;

Pay to change lanes: A cooperative lane-changing strategy for connected/automated driving

Abstract

This paper proposes a cooperative lane changing strategy using a transferable utility games framework. This allows vehicles to engage in transactions where gaps in traffic are created in exchange for monetary compensation. The proposed approach is best suited to discretionary lane change maneuvers. We formulate gains in travel time, referred to as time differences, that result from achieving higher speeds. These time differences, coupled with value of time, are used to formulate a utility function, where utility is transferable. We also allow for games between connected vehicles that do not involve transfer of utility. We apply Nash bargaining theory to solve the latter. A cellular automaton is developed and utilized to perform simulation experiments that explore the impact of such transactions on traffic conditions (travel-time savings, resulting speed-density relations and shock wave formation) and the benefit to vehicles. The results show that lane changing with transferable utility between drivers can help achieve win-win results, improve both individual and social benefits without resulting in any adverse effects on traffic characteristics in general and, in fact, result in slight improvement at traffic densities outside of free-flow and (bumper-to-bumper) jammed traffic.

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Keywords

FOS: Computer and information sciences, Computer Science - Computer Science and Game Theory, Optimization and Control (math.OC), FOS: Mathematics, Mathematics - Optimization and Control, Computer Science and Game Theory (cs.GT)

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    78
    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
78
Top 1%
Top 10%
Top 1%
Green
bronze