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Freeway Traffic Control in Presence of Capacity Drop
- Source :
- IEEE Transactions on Intelligent Transportation Systems. 22:1497-1516
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- Capacity drop at congested freeway bottlenecks is well known with a lot of field observations. This paper studies coordinated ramp metering (RM) and mainstream traffic flow control (MTFC) as well as their integration (RM+MTFC) for freeway traffic, with particular attention to effects of capacity drop on the performance of traffic control measures. Via mathematical analysis and comprehensive simulation studies under an optimal control framework, the work has revealed a capacity-drop-related mechanism that MTFC and ramp metering are based on to take effects, and obtained a number of important conclusions: (1) applications of any control measure (RM, MTFC, or RM+MTFC) in freeways are justified by the existence of capacity drop in field; (2) an appropriate usage of the control measures can effectively prevent the activation of potential bottlenecks on freeways and hence avoid capacity drop; (3) any control measure is beneficial for a large majority of the driver population in a freeway network if it can manage to increase the accumulated total network exit flow; (4) it is a common misconception that ramp metering would simply transfer traffic loads from the freeway mainstream to on-ramps. The work has also highlighted the strengths, weaknesses, and applicability of ramp metering and MTFC.
- Subjects :
- 050210 logistics & transportation
education.field_of_study
Traffic flow control
Computer science
Mechanical Engineering
Freeway traffic control
Feedback control
05 social sciences
Population
Optimal control
Automotive engineering
Computer Science Applications
Control measure
0502 economics and business
Automotive Engineering
Drop (telecommunication)
Metering mode
education
Subjects
Details
- ISSN :
- 15580016 and 15249050
- Volume :
- 22
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Intelligent Transportation Systems
- Accession number :
- edsair.doi...........350f23bb050f1c650524004f3a718480