TY - JOUR
T1 - A multi-class model-based control scheme for reducing congestion and emissions in freeway networks by combining ramp metering and route guidance
AU - Pasquale, C.
AU - Sacone, S
AU - Siri, S
AU - De Schutter, B.
PY - 2017
Y1 - 2017
N2 - The paper proposes a multi-class control scheme for freeway traffic networks. This control scheme combines two control strategies, i.e. ramp metering and route guidance, in order to reduce the total time spent and the total emissions in a balanced way. In particular, the ramp metering and route guidance controllers are feedback predictive controllers, i.e. they compute the control actions not only on the basis of the measured system state, but also on the basis of the prediction of the system evolution, in terms of traffic conditions and traffic emissions. Another important feature of the controllers is that they have a multi-class nature: different classes of vehicles are considered and specific control actions are computed for each class. Since the controllers are based on a set of parameters that need to be tuned, the overall control framework also includes a module to properly determine the gains of the controllers. The simulation analysis reported in the paper shows the effectiveness of the proposed control framework and, in particular, the possibility of implementing control policies that are specific for each vehicle type.
AB - The paper proposes a multi-class control scheme for freeway traffic networks. This control scheme combines two control strategies, i.e. ramp metering and route guidance, in order to reduce the total time spent and the total emissions in a balanced way. In particular, the ramp metering and route guidance controllers are feedback predictive controllers, i.e. they compute the control actions not only on the basis of the measured system state, but also on the basis of the prediction of the system evolution, in terms of traffic conditions and traffic emissions. Another important feature of the controllers is that they have a multi-class nature: different classes of vehicles are considered and specific control actions are computed for each class. Since the controllers are based on a set of parameters that need to be tuned, the overall control framework also includes a module to properly determine the gains of the controllers. The simulation analysis reported in the paper shows the effectiveness of the proposed control framework and, in particular, the possibility of implementing control policies that are specific for each vehicle type.
KW - Freeway networks
KW - Integrated control
KW - Predictive feedback controller
KW - Ramp metering
KW - Route guidance
KW - Traffic emissions
UR - http://www.scopus.com/inward/record.url?scp=85019551623&partnerID=8YFLogxK
U2 - 10.1016/j.trc.2017.04.007
DO - 10.1016/j.trc.2017.04.007
M3 - Article
AN - SCOPUS:85019551623
SN - 0968-090X
VL - 80
SP - 384
EP - 408
JO - Transportation Research. Part C: Emerging Technologies
JF - Transportation Research. Part C: Emerging Technologies
ER -