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Using advanced adaptive cruise control systems to reduce congestion at sags : An evaluation based on microscopic traffic simulation. / Goñi-Ros, Bernat; Schakel, Wouter J.; Papacharalampous, Alexandros E.; Wang, Meng; Knoop, Victor L.; Sakata, Ichiro; van Arem, Bart; Hoogendoorn, Serge P.

In: Transportation Research Part C: Emerging Technologies, Vol. 102, 2019, p. 411-426.

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@article{a738f885102e4811855ea4fd679ae75e,
title = "Using advanced adaptive cruise control systems to reduce congestion at sags: An evaluation based on microscopic traffic simulation",
abstract = "Sags are roadway sections along which the gradient increases gradually in the direction of traffic. Sags are generally bottlenecks in freeway networks. Previous research suggests that traffic management measures using advanced Adaptive Cruise Control (ACC) systems could reduce congestion on freeways, but little is known about their potential effectiveness at sags. This article evaluates the effectiveness of a basic ACC system (B-ACC) and two advanced ACC systems – Traffic State-Adaptive ACC (TSA-ACC) and Cooperative ACC (C-ACC) – in mitigating congestion at sags. TSA-ACC adapts the ACC parameters to the macroscopic traffic state estimated by the vehicle itself. C-ACC uses information of other vehicles in the surroundings to adjust its accelerations. Results are obtained using microscopic traffic simulations with different penetration rates. They show that, under high-demand conditions, congestion decreases with increasing percentage of vehicles equipped with B-ACC. With high penetration rates (75{\%} and above), traffic no longer becomes congested at the sag. Moreover, the results show that TSA-ACC and C-ACC reduce congestion more than B-ACC, mainly because they increase the queue discharge capacity of the sag. The two advanced ACC systems prevent the formation of congestion at the sag at lower penetration rates than B-ACC. TSA-ACC is the most effective system. C-ACC is only more effective than B-ACC in scenarios with 20{\%} penetration rate or higher; below that, connectivity between equipped vehicles is too low. Our findings show the potential of using advanced ACC systems to mitigate congestion at sags and indicate some challenges of this traffic management approach.",
keywords = "Adaptive Cruise Control, Freeway capacity, Microscopic traffic simulation, Sag vertical curve, Traffic management",
author = "Bernat Go{\~n}i-Ros and Schakel, {Wouter J.} and Papacharalampous, {Alexandros E.} and Meng Wang and Knoop, {Victor L.} and Ichiro Sakata and {van Arem}, Bart and Hoogendoorn, {Serge P.}",
note = "Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.",
year = "2019",
doi = "10.1016/j.trc.2019.02.021",
language = "English",
volume = "102",
pages = "411--426",
journal = "Transportation Research. Part C: Emerging Technologies",
issn = "0968-090X",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Using advanced adaptive cruise control systems to reduce congestion at sags

T2 - Transportation Research. Part C: Emerging Technologies

AU - Goñi-Ros, Bernat

AU - Schakel, Wouter J.

AU - Papacharalampous, Alexandros E.

AU - Wang, Meng

AU - Knoop, Victor L.

AU - Sakata, Ichiro

AU - van Arem, Bart

AU - Hoogendoorn, Serge P.

N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2019

Y1 - 2019

N2 - Sags are roadway sections along which the gradient increases gradually in the direction of traffic. Sags are generally bottlenecks in freeway networks. Previous research suggests that traffic management measures using advanced Adaptive Cruise Control (ACC) systems could reduce congestion on freeways, but little is known about their potential effectiveness at sags. This article evaluates the effectiveness of a basic ACC system (B-ACC) and two advanced ACC systems – Traffic State-Adaptive ACC (TSA-ACC) and Cooperative ACC (C-ACC) – in mitigating congestion at sags. TSA-ACC adapts the ACC parameters to the macroscopic traffic state estimated by the vehicle itself. C-ACC uses information of other vehicles in the surroundings to adjust its accelerations. Results are obtained using microscopic traffic simulations with different penetration rates. They show that, under high-demand conditions, congestion decreases with increasing percentage of vehicles equipped with B-ACC. With high penetration rates (75% and above), traffic no longer becomes congested at the sag. Moreover, the results show that TSA-ACC and C-ACC reduce congestion more than B-ACC, mainly because they increase the queue discharge capacity of the sag. The two advanced ACC systems prevent the formation of congestion at the sag at lower penetration rates than B-ACC. TSA-ACC is the most effective system. C-ACC is only more effective than B-ACC in scenarios with 20% penetration rate or higher; below that, connectivity between equipped vehicles is too low. Our findings show the potential of using advanced ACC systems to mitigate congestion at sags and indicate some challenges of this traffic management approach.

AB - Sags are roadway sections along which the gradient increases gradually in the direction of traffic. Sags are generally bottlenecks in freeway networks. Previous research suggests that traffic management measures using advanced Adaptive Cruise Control (ACC) systems could reduce congestion on freeways, but little is known about their potential effectiveness at sags. This article evaluates the effectiveness of a basic ACC system (B-ACC) and two advanced ACC systems – Traffic State-Adaptive ACC (TSA-ACC) and Cooperative ACC (C-ACC) – in mitigating congestion at sags. TSA-ACC adapts the ACC parameters to the macroscopic traffic state estimated by the vehicle itself. C-ACC uses information of other vehicles in the surroundings to adjust its accelerations. Results are obtained using microscopic traffic simulations with different penetration rates. They show that, under high-demand conditions, congestion decreases with increasing percentage of vehicles equipped with B-ACC. With high penetration rates (75% and above), traffic no longer becomes congested at the sag. Moreover, the results show that TSA-ACC and C-ACC reduce congestion more than B-ACC, mainly because they increase the queue discharge capacity of the sag. The two advanced ACC systems prevent the formation of congestion at the sag at lower penetration rates than B-ACC. TSA-ACC is the most effective system. C-ACC is only more effective than B-ACC in scenarios with 20% penetration rate or higher; below that, connectivity between equipped vehicles is too low. Our findings show the potential of using advanced ACC systems to mitigate congestion at sags and indicate some challenges of this traffic management approach.

KW - Adaptive Cruise Control

KW - Freeway capacity

KW - Microscopic traffic simulation

KW - Sag vertical curve

KW - Traffic management

UR - http://www.scopus.com/inward/record.url?scp=85063372818&partnerID=8YFLogxK

U2 - 10.1016/j.trc.2019.02.021

DO - 10.1016/j.trc.2019.02.021

M3 - Article

VL - 102

SP - 411

EP - 426

JO - Transportation Research. Part C: Emerging Technologies

JF - Transportation Research. Part C: Emerging Technologies

SN - 0968-090X

ER -

ID: 52794517