TY - GEN
T1 - Stabilizing traffic flow via a single autonomous vehicle
T2 - 28th IEEE Intelligent Vehicles Symposium, IV 2017
AU - Cui, Shumo
AU - Seibold, Benjamin
AU - Stern, Raphael
AU - Work, Daniel B.
N1 - Funding Information:
This material is based upon work supported by the National Science Foundation under Grants No. CNS-1446690 and CNS-1446702
Funding Information:
*This material is based upon work supported by the National Science Foundation under Grants No. CNS–1446690 and CNS–1446702.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/28
Y1 - 2017/7/28
N2 - In certain flow regimes, the ideal uniform vehicle flow on the road is unstable, and stop-And-go traffic develops. The instability that leads to this less fuel-efficient unsteady flow results from the collective behavior of all human drivers. This work studies under which circumstances the presence of a single autonomous vehicle (AV) can locally stabilize the flow, without changing the way the humans drive. If possible, this can enable traffic flow control via very few AVs serving as mobile actuators. First, the analysis of car-following models reveals that in idealized conditions (no system noise), the flow can in fact be made linearly stable by means of a low fraction of control vehicles. Second, we highlight the fundamental limitations of this sparse control when considering models with noise.
AB - In certain flow regimes, the ideal uniform vehicle flow on the road is unstable, and stop-And-go traffic develops. The instability that leads to this less fuel-efficient unsteady flow results from the collective behavior of all human drivers. This work studies under which circumstances the presence of a single autonomous vehicle (AV) can locally stabilize the flow, without changing the way the humans drive. If possible, this can enable traffic flow control via very few AVs serving as mobile actuators. First, the analysis of car-following models reveals that in idealized conditions (no system noise), the flow can in fact be made linearly stable by means of a low fraction of control vehicles. Second, we highlight the fundamental limitations of this sparse control when considering models with noise.
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U2 - 10.1109/IVS.2017.7995897
DO - 10.1109/IVS.2017.7995897
M3 - Conference contribution
AN - SCOPUS:85028033645
T3 - IEEE Intelligent Vehicles Symposium, Proceedings
SP - 1336
EP - 1341
BT - IV 2017 - 28th IEEE Intelligent Vehicles Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 11 June 2017 through 14 June 2017
ER -