Optimizing Departures of Automated Vehicles From Highways While Maintaining Mainline Capacity
Abstract
Automated vehicles have the potential to revolutionize our nation's transportation systems as they promise to dramatically reduce congestion, accidents, and fuel usage. Namely, as it becomes possible to precisely exert control on and coordinate the movement and placement of vehicles along a stretch of highway, the separation distance between vehicles can be reduced, thus increasing flow and minimizing congestion. Precise and coordinated vehicle controls and placements also improve predictability, resulting in fewer instances of sudden braking, which reduce fuel usage and accidents. Most existing research has focused on the steady-state behaviors and operations of automated vehicles, such as platooning, and assumes complete knowledge of the system, e.g., the number of vehicles and their destinations and/or neglects dynamic or transition operations such as exiting a highway and lane changing. Uncoordinated lane-changing and exiting behaviors by automated vehicles can significantly reduce the flow of traffic as vehicles will require larger separations, are forced to slow down, or worse, collide. In this paper, we present a collision-free runtime approach to efficiently organize the departures of automated vehicles from a highway environment while maintaining highway capacity in extremely dynamic conditions. To maximize the number of safe departures, the key ideas are to: 1) determine when, and where to, an exiting vehicle should lane change in order to make a successful exit given current traffic conditions as provided by connected vehicle technology and 2) execute the actual lane-change operations using a reservation-based approach. Simulation results show that, by coordinating vehicles' behaviors, traffic flow can be improved by up to five times of today's typical flow while ensuring a 100% exit success rate in a collision-free manner.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
An Analysis of Possible Energy Impacts of Automated Vehicles
Brown, A., Gonder, J., & Repac, B. (2014) · Lecture Notes in Mobility · doi:10.1007/978-3-319-05990-7_13 · Cited by 217 · see citing works
Flagged first, then by citations
Research works printed but not linked: 39
- 10.1109/ITSC.2010.5625197 · DOI
- 10.1061/(ASCE)0733-947X(2002)128:2(182) · DOI
- 10.1109/LCN.2008.4664253 · DOI
- 10.1287/trsc.29.2.118 · DOI
- 10.1109/RAMECH.2004.1438017 · DOI
- 10.1109/TITS.2007.908721 · DOI
- 10.1016/j.trd.2014.11.006 · DOI
- berry, 2010, The Effects of Driving Style and Vehicle Performance on the Realworld Fuel Consumption of US Light-duty Vehicles
- 10.1109/ITSC.2012.6338779 · DOI
- 10.1016/j.comcom.2007.12.008 · DOI
- 10.1016/j.trb.2005.04.003 · DOI
- board, 2010, Highway Capacity Manual
- 10.1061/(ASCE)TE.1943-5436.0000165 · DOI
- 10.1109/TITS.2008.928265 · DOI
- 10.1177/095965180121500402 · DOI
- 10.1088/0305-4470/33/48/103 · DOI
- greenshields, 0, A study of traffic capacity, Highw Res Board Proc Annu Meet, 448
- 10.1016/S0968-090X(96)00011-3 · DOI
- 10.1016/S0005-1098(97)00050-2 · DOI
- chee, 1994, Vehicle lane change maneuver in automated highway systems
- 10.1109/TITS.2003.811644 · DOI
- 10.1109/TITS.2014.2356932 · DOI
- 10.1016/j.tra.2015.04.003 · DOI · Paper page
- 10.1007/s12239-008-0043-4 · DOI
- tsao, 1994, Capacity of automated highway systems Effect of platooning and barriers
- 10.1142/S0219843611002319 · DOI
- subramanian, 2005, Motor vehicle traffic crashes as a leading cause of death in the U S 2002—A demographic perspective
- 10.1016/j.trc.2004.09.001 · DOI
- horowitz, 2004, An efficient lane change maneuver for platoons of vehicles in an automated highway system
- 10.1257/aer.101.6.2616 · DOI
- 10.1016/j.trb.2009.12.014 · DOI
- schrank, 2012, TTI's 2012 Urban Mobility Report
- 10.1109/87.852914 · DOI
- 10.1109/ACC.1995.533804 · DOI
- moriarty, 1998, Distributed learning of lane-selection strategies for traffic management
- 10.1016/S0968-090X(96)00012-5 · DOI
- 10.1109/25.618201 · DOI
- 10.1109/IVS.2007.4290284 · DOI
- 10.1016/S0968-090X(99)00006-6 · DOI
Cited by
Sorted by citations
Faisal, A., Yigitcanlar, T., Kamruzzaman, M., & Currie, G. (2019) · Journal of Transport and Land Use · doi:10.5198/jtlu.2019.1405 · Cited by 427 · see citing works
- Authors
- Meissner, E., Chantem, T., & Heaslip, K.
- Affiliations
- Utah State University (US)
- Virginia Tech (US)
- Venue
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2016-12
- Volume
- 17
- Issue
- 12
- Pages
- 3498-3511
- ISSN
- 1524-9050 (ISSN-L)
- 1558-0016
- OpenAlex
- W2413042152
- Cited by
- 11
- References
- 1
- Citations by year
- 2023: 1 · 2021: 3 · 2020: 2 · 2019: 4 · 2018: 1
- FWCI
- 1.40
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Intelligent Transportation Systems (publishedVersion)
- Funders
- National Science Foundation (1545091, 1544601)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Social Sciences › Transportation › Transportation and Mobility Innovations
- Physical Sciences › Engineering › Civil and Structural Engineering › Road Transport and Highway Systems
- Keywords
- autonomous vehicles, lane changing, road capacity, traffic flow, connected vehicles, traffic congestion
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review