Skip to main content
archive
Search Submit Donate Log in
Press Enter to search · Advanced search

Computer Science > Robotics

arXiv:2211.08636 (cs)
[Submitted on 16 Nov 2022]

Title:Cooperative Energy and Time-Optimal Lane Change Maneuvers with Minimal Highway Traffic Disruption

Authors:Andres S. Chavez Armijos, Anni Li, Christos G. Cassandras, Yasir K. Al-Nadawi, Hidekazu Araki, Behdad Chalaki, Ehsan Moradi-Pari, Hossein Nourkhiz Mahjoub, Vaishnav Tadiparthi
View a PDF of the paper titled Cooperative Energy and Time-Optimal Lane Change Maneuvers with Minimal Highway Traffic Disruption, by Andres S. Chavez Armijos and 8 other authors
View PDF HTML (experimental)
Abstract:We derive optimal control policies for a Connected Automated Vehicle (CAV) and cooperating neighboring CAVs to carry out a lane change maneuver consisting of a longitudinal phase where the CAV properly positions itself relative to the cooperating neighbors and a lateral phase where it safely changes lanes. In contrast to prior work on this problem, where the CAV "selfishly" only seeks to minimize its maneuver time, we seek to ensure that the fast-lane traffic flow is minimally disrupted (through a properly defined metric). Additionally, when performing lane-changing maneuvers, we optimally select the cooperating vehicles from a set of feasible neighboring vehicles and experimentally show that the highway throughput is improved compared to the baseline case of human-driven vehicles changing lanes with no cooperation. When feasible solutions do not exist for a given maximal allowable disruption, we include a time relaxation method trading off a longer maneuver time with reduced disruption. Our analysis is also extended to multiple sequential maneuvers. Simulation results show the effectiveness of our controllers in terms of safety guarantees and up to 16% and 90% average throughput and maneuver time improvement respectively when compared to maneuvers with no cooperation.
Comments: arXiv admin note: substantial text overlap with arXiv:2203.17102
Subjects: Robotics (cs.RO); Systems and Control (eess.SY)
Cite as: arXiv:2211.08636 [cs.RO]
  (or arXiv:2211.08636v1 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2211.08636
arXiv-issued DOI via DataCite

Submission history

From: Andres S. Chavez Armijos [view email]
[v1] Wed, 16 Nov 2022 03:10:21 UTC (1,926 KB)
Full-text links:

Access Paper:

    View a PDF of the paper titled Cooperative Energy and Time-Optimal Lane Change Maneuvers with Minimal Highway Traffic Disruption, by Andres S. Chavez Armijos and 8 other authors
  • View PDF
  • HTML (experimental)
  • TeX Source
license icon view license

Current browse context:

cs.RO
< prev   |   next >
new | recent | 2022-11
Change to browse by:
cs
cs.SY
eess
eess.SY

References & Citations

  • NASA ADS
  • Google Scholar
  • Semantic Scholar
Loading...

BibTeX formatted citation

Data provided by:

Bookmark

BibSonomy Reddit

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
  • Author
  • Venue
  • Institution
  • Topic

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
We gratefully acknowledge support from our major funders, member institutions, , and all contributors.
About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab)
Major funding support from
Simons Foundation Simons Foundation International Schmidt Sciences