The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments
Open accessAbstract
Abstract 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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Cites
Consensus and Cooperation in Networked Multi-Agent Systems
Olfati-Saber, R., Fax, J. A., & Murray, R. M. (2007) · Proceedings of the IEEE · doi:10.1109/jproc.2006.887293 · Cited by 10,522 · cited 1×
“The control of complex multi-agent systems has impact beyond vehicular traffic flow, including coordinated robots [69], social networks [70], animal swarming [71, 72], and many other applications.”
BackgroundWhitham, G. B., & Fowler, R. G. (1975) · Physics Today · doi:10.1063/1.3069011 · Cited by 8,179
Whiteman, K. J. (1975) · Physics Bulletin · doi:10.1088/0031-9112/26/11/028 · Cited by 7,064
A cellular automaton model for freeway traffic
Nagel, K., & Schreckenberg, M. (1992) · Journal de Physique I · doi:10.1051/jp1:1992277 · Cited by 3,838
Traffic and related self-driven many-particle systems
Helbing, D. (2001) · Reviews of Modern Physics · doi:10.1103/revmodphys.73.1067 · Cited by 3,245
Dynamical model of traffic congestion and numerical simulation
Bando, M., Hasebe, K., Nakayama, A., Shibata, A., & Sugiyama, Y. (1995) · Physical Review E · doi:10.1103/physreve.51.1035 · Cited by 3,013
Graph Theoretic Methods in Multiagent Networks
Mesbahi, M., & Egerstedt, M. (2010) · Princeton University Press eBooks · doi:10.1515/9781400835355 · Cited by 2,897 · cited 1×
“The control of complex multi-agent systems has impact beyond vehicular traffic flow, including coordinated robots [69], social networks [70], animal swarming [71, 72], and many other applications.”
BackgroundStatistical physics of vehicular traffic and some related systems
Chowdhury, D. (2000) · Physics Reports · doi:10.1016/s0370-1573(99)00117-9 · Cited by 2,298
Feedback systems: an introduction for scientists and engineers
(2008) · Choice Reviews Online · doi:10.5860/choice.46-2107 · Cited by 1,968
Statistical Physics of Vehicular Traffic and Some Related Systems
Chowdhury, D., Santen, L., & Schadschneider, A. (2000) · Cited by 1,823
Cited by
Energy saving potentials of connected and automated vehicles
Vahidi, A., & Sciarretta, A. (2018) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2018.09.001 · Cited by 537
Taiebat, M., Brown, A. L., Safford, H. R., Qu, S., & Xu, M. (2018) · Environmental Science & Technology · doi:10.1021/acs.est.8b00127 · Cited by 334
Evaluating the impact of connected and autonomous vehicles on traffic safety
Ye, L., & Yamamoto, T. (2019) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/j.physa.2019.04.245 · Cited by 296
Wang, J., Zhang, L., Huang, Y., Zhao, J., & Bella, F. (2020) · Journal of Advanced Transportation · doi:10.1155/2020/8867757 · Cited by 261
Gueriau, M., & Dusparic, I. (2020) · 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc45102.2020.9294174 · Cited by 133
Metadata
- Authors
- Stern, R. E., Cui, S., Delle Monache, M. L., Bhadani, R., Bunting, M., Churchill, M., Hamilton, N., Haulcy, R., Pohlmann, H., Wu, F., Piccoli, B., Seibold, B., Sprinkle, J., & Work, D. B.
- Venue
- Transportation Research Part C: Emerging Technologies
- Publisher
- Elsevier BV
- Published
- 2018-04
- Volume
- 89
- Pages
- 205-221
- ISSN
- 0968-090X (ISSN-L)
- OpenAlex
- W2611350544
- Cited by
- 800
- References
- 59
- FWCI
- 44.99
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Stern, R. E., Cui, S., Delle Monache, M. L., Bhadani, R., Bunting, M., Churchill, M., Hamilton, N., Haulcy, R., Pohlmann, H., Wu, F., Piccoli, B., Seibold, B., Sprinkle, J., & Work, D. B. (2018). Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments. Transportation Research Part C: Emerging Technologies. https://doi.org/10.1016/j.trc.2018.02.005
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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