Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments
•Experiments on a circular track with 20+ vehicles show stop-and-go waves emerge.•Control of an autonomous vehicle can dampen stop-and-go waves in field experiments.•Control of one autonomous vehicle reduces total traffic fuel consumption.•Mobile traffic control is possible when a small fraction of...
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| Published in | Transportation research. Part C, Emerging technologies Vol. 89; pp. 205 - 221 |
|---|---|
| Main Authors | , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.04.2018
Elsevier |
| Subjects | |
| Online Access | Get full text |
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| Abstract | •Experiments on a circular track with 20+ vehicles show stop-and-go waves emerge.•Control of an autonomous vehicle can dampen stop-and-go waves in field experiments.•Control of one autonomous vehicle reduces total traffic fuel consumption.•Mobile traffic control is possible when a small fraction of vehicles are automated.
Traffic waves are phenomena that emerge when the vehicular density exceeds a critical threshold. Considering the presence of increasingly automated vehicles in the traffic stream, a number of research activities have focused on the influence of automated vehicles on the bulk traffic flow. In the present article, we demonstrate experimentally that intelligent control of an autonomous vehicle is able to dampen stop-and-go waves that can arise even in the absence of geometric or lane changing triggers. Precisely, our experiments on a circular track with more than 20 vehicles show that traffic waves emerge consistently, and that they can be dampened by controlling the velocity of a single vehicle in the flow. We compare metrics for velocity, braking events, and fuel economy across experiments. These experimental findings suggest a paradigm shift in traffic management: flow control will be possible via a few mobile actuators (less than 5%) long before a majority of vehicles have autonomous capabilities. |
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| AbstractList | Traffic waves are phenomena that emerge when the vehicular density exceeds a critical threshold. Considering the presence of increasingly automated vehicles in the traffic stream, a number of research activities have focused on the influence of automated vehicles on the bulk traffic flow. In the present article, we demonstrate experimentally that intelligent control of an autonomous vehicle is able to dampen stop-and-go waves that can arise even in the absence of geometric or lane changing triggers. Precisely, our experiments on a circular track with more than 20 vehicles show that traffic waves emerge consistently, and that they can be dampened by controlling the velocity of a single vehicle in the flow. We compare metrics for velocity, braking events, and fuel economy across experiments. These experimental findings suggest a paradigm shift in traffic management: flow control will be possible via a few mobile actuators (less than 5%) long before a majority of vehicles have autonomous capabilities. •Experiments on a circular track with 20+ vehicles show stop-and-go waves emerge.•Control of an autonomous vehicle can dampen stop-and-go waves in field experiments.•Control of one autonomous vehicle reduces total traffic fuel consumption.•Mobile traffic control is possible when a small fraction of vehicles are automated. Traffic waves are phenomena that emerge when the vehicular density exceeds a critical threshold. Considering the presence of increasingly automated vehicles in the traffic stream, a number of research activities have focused on the influence of automated vehicles on the bulk traffic flow. In the present article, we demonstrate experimentally that intelligent control of an autonomous vehicle is able to dampen stop-and-go waves that can arise even in the absence of geometric or lane changing triggers. Precisely, our experiments on a circular track with more than 20 vehicles show that traffic waves emerge consistently, and that they can be dampened by controlling the velocity of a single vehicle in the flow. We compare metrics for velocity, braking events, and fuel economy across experiments. These experimental findings suggest a paradigm shift in traffic management: flow control will be possible via a few mobile actuators (less than 5%) long before a majority of vehicles have autonomous capabilities. |
| Author | Hamilton, Nathaniel Bunting, Matt Work, Daniel B. Seibold, Benjamin Delle Monache, Maria Laura Bhadani, Rahul Haulcy, R’mani Stern, Raphael E. Piccoli, Benedetto Sprinkle, Jonathan Churchill, Miles Pohlmann, Hannah Wu, Fangyu Cui, Shumo |
| Author_xml | – sequence: 1 givenname: Raphael E. surname: Stern fullname: Stern, Raphael E. organization: Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 N. Mathews Ave, Urbana, IL 61801, USA – sequence: 2 givenname: Shumo surname: Cui fullname: Cui, Shumo organization: Department of Mathematics, Temple University, 1805 North Broad Street, Philadelphia, PA 19122, USA – sequence: 3 givenname: Maria Laura surname: Delle Monache fullname: Delle Monache, Maria Laura organization: Inria, University Grenoble Alpes, CNRS, GIPSA-lab, F-38000 Grenoble, France – sequence: 4 givenname: Rahul surname: Bhadani fullname: Bhadani, Rahul organization: Electrical and Computer Engineering, University of Arizona, Tucson, AZ 85721-0104, USA – sequence: 5 givenname: Matt surname: Bunting fullname: Bunting, Matt organization: Electrical and Computer Engineering, University of Arizona, Tucson, AZ 85721-0104, USA – sequence: 6 givenname: Miles surname: Churchill fullname: Churchill, Miles organization: Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 N. Mathews Ave, Urbana, IL 61801, USA – sequence: 7 givenname: Nathaniel surname: Hamilton fullname: Hamilton, Nathaniel organization: Lipscomb University, 1 University Park Drive, Nashville, TN 37204, USA – sequence: 8 givenname: R’mani surname: Haulcy fullname: Haulcy, R’mani organization: Yale University, New Haven, CT 06520, USA – sequence: 9 givenname: Hannah surname: Pohlmann fullname: Pohlmann, Hannah organization: Pennsylvania State University, University Park, PA 16801, USA – sequence: 10 givenname: Fangyu surname: Wu fullname: Wu, Fangyu organization: Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 N. Mathews Ave, Urbana, IL 61801, USA – sequence: 11 givenname: Benedetto surname: Piccoli fullname: Piccoli, Benedetto organization: Department of Mathematical Sciences, Rutgers University – Camden, 311 N. 5th St, Camden, NJ 08102, USA – sequence: 12 givenname: Benjamin surname: Seibold fullname: Seibold, Benjamin organization: Department of Mathematics, Temple University, 1805 North Broad Street, Philadelphia, PA 19122, USA – sequence: 13 givenname: Jonathan surname: Sprinkle fullname: Sprinkle, Jonathan organization: Electrical and Computer Engineering, University of Arizona, Tucson, AZ 85721-0104, USA – sequence: 14 givenname: Daniel B. surname: Work fullname: Work, Daniel B. email: dan.work@vanderbilt.edu organization: Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 N. Mathews Ave, Urbana, IL 61801, USA |
| BackLink | https://inria.hal.science/hal-01614638$$DView record in HAL |
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| Snippet | •Experiments on a circular track with 20+ vehicles show stop-and-go waves emerge.•Control of an autonomous vehicle can dampen stop-and-go waves in field... Traffic waves are phenomena that emerge when the vehicular density exceeds a critical threshold. Considering the presence of increasingly automated vehicles in... |
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| SubjectTerms | Autonomous vehicles Computer Science Systems and Control Traffic control Traffic waves |
| Title | Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments |
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