The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Effect of adaptive cruise control systems on traffic flow
Abstract
The flow of traffic composed of vehicles that are equipped with adaptive cruise control (ACC) is studied using simulations. The ACC vehicles are modeled by a linear dynamical equation that has string stability. In platoons of all ACC vehicles, perturbations due to changes in the lead vehicle's velocity do not cause jams. Simulations of merging flows near an onramp show that if the total incoming rate does not exceed the capacity of the single outgoing lane, free flow is maintained. With larger incoming flows, a state closely related to the synchronized flow phase found in manually driven vehicular traffic has been observed. This state, however, should not be considered congested because the flow is maximal for the density. Traffic composed of random sequences of ACC vehicles and manual vehicles has also been studied. At high speeds (approximately 30 m/s ) jamming occurs for concentrations of ACC vehicles of 10% or less. At 20% no jams are formed. The formation of jams is sensitive to the sequence of vehicles (ACC or manual). At lower speeds (approximately 15 m/s ), no critical concentration for complete jam suppression is found. Rather, the average velocity in the pseudojam region increases with increasing ACC concentration. Mixing 50% ACC vehicles randomly with manually driven vehicles on the primary lane in onramp simulations shows only modestly reduced travel times and larger flow rates.
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Cites
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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., et al. (2018) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2018.02.005 · Cited by 800
Adaptive Cruise Control Design for Active Congestion Avoidance
Kesting, A., Treiber, M., Schönhof, M., & Helbing, D. (2008) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2007.12.004 · Cited by 610
Dynamics of connected vehicle systems with delayed acceleration feedback
Ge, J. I., & Orosz, G. (2014) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2014.04.014 · Cited by 454
Cooperative Adaptive Cruise Control: A Reinforcement Learning Approach
Desjardins, C., & Chaib-draa, B. (2011) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2011.2157145 · Cited by 344
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
Metadata
- Authors
- Davis, L. C.
- Venue
- Physical Review E
- Publisher
- American Physical Society (APS)
- Published
- 2004-06-04
- Volume
- 69
- Issue
- 6
- Pages
- 066110-066110
- ISSN
- 1539-3755 (ISSN-L)
- 1550-2376
- OpenAlex
- W2147021187
- Cited by
- 284
- References
- 14
- FWCI
- 13.56
- Type
- journal article
- Language
- en
- Open access
- closed
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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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