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A multi-class model-based control scheme for reducing congestion and emissions in freeway networks by combining ramp metering and route guidance
- Publication Year :
- 2017
- Publisher :
- Elsevier Ltd, 2017.
-
Abstract
- 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.
- Subjects :
- Scheme (programming language)
0209 industrial biotechnology
Engineering
Freeway networks
Traffic emissions
Control (management)
Transportation
02 engineering and technology
Integrated control
Predictive feedback controller
Ramp metering
Route guidance
Set (abstract data type)
020901 industrial engineering & automation
Control theory
0502 economics and business
Metering mode
Civil and Structural Engineering
computer.programming_language
050210 logistics & transportation
Class (computer programming)
business.industry
05 social sciences
Control engineering
Computer Science Applications
Model predictive control
Traffic congestion
Automotive Engineering
State (computer science)
business
computer
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....da307d1608ff04752abdd81ca7a74765