Development of Coordinated Ramp-Metering Based on Multi-objective Nonlinear Optimization Functions: Traffic and Safety

Haj-Salem, Habib; Farhi, Nadir; Lebacque, Jean Patrique; Bhouri, Neïla

doi:10.1007/978-3-319-57105-8_16

“…The linking of crash occurrence with occupancy could potentially provide a basis for multi-objective traffic control that aims to maximise safety as well as improving efficiency (Haj-Salem, Farhi, Lebacque & Bhouri, 2016).…”

Section: Methodsmentioning

confidence: 99%

Untitled

2020

JRS

0

View full text Add to dashboard Cite

The Australasian College of Road Safety (ACRS) and Austroads invite you to attend the largest road safety-dedicated conference in the Southern Hemisphere. The 2020 Australasian Road Safety Conference (ARSC2020) will be held in Melbourne at the Melbourne Convention & Exhibition Centre from Wednesday 16 September to Friday 18 September 2020.ARSC2020 will showcase the region's outstanding researchers, practitioners, policy-makers and industry spanning the range of road safety issues identified in the United Nations Decade of Action for Road Safety: Road Safety Management, Infrastructure, Safe Vehicles, User Behaviour, and Post-Crash Care.ARSC2020 will bring with it a special focus on engaging all levels of government and community, from the city to the bush, to move "Towards Zero -A Fresh Approach". The comprehensive 3-day scientific program will showcase the latest research; education and policing programs; policies and management strategies; and technological developments in the field, together with national and international keynote speakers, oral and poster presentations, workshops and interactive symposia. WHO SHOULD ATTEND?ARSC2020 is expected to attract 500-700 delegates including researchers, policing and enforcement agencies, practitioners, policymakers, industry representatives, educators, and students working in the fields of behavioural science, education and training, emergency services, engineering and technology, health and rehabilitation, policing, justice and law enforcement, local, state and federal government, traffic management, and vehicle safety.

show abstract

“…In addition to the traffic performance, other research took the safety factors into account. [13] integrated a risk model to the system and designed a multi-objective nonlinear optimization for the coordination of RM. [14] also derived a risk indicator from safety-density relation to be utilized with standard traffic performance indicator, total travel time spent in a horizon-based nonlinear optimal control problem.…”

Section: Introductionmentioning

confidence: 99%

A Feedback Linearization Approach for Coordinated Traffic Flow Management in Highway Systems

Chavoshi¹,

Kouvelas²

2022

Preprint

0

View full text Add to dashboard Cite

This paper aims to develop a traffic control approach that provides an optimal real-time solution for large-scale highway networks. The traffic flow model’s nonlinearity is the main reason for the complex optimization problems that consequently require high computational effort. Feedback linearization is a well-known approach in nonlinear systems control. It can provide an exact linear representation of the original nonlinear system. Thus, it facilitates further steps in the controller design. This research combines the feedback linearization method and linear MPC to simultaneously guarantee optimal performance and real-time feasibility. While developing feedback linearization for METANET model, we discovered a pattern that describes the expansion of the control signals (ramp metering and variable speed limits) and disturbances effects through the highway networks. Utilizing this pattern, we design a generic feedback linearization control law for METANET model. The control law provides the key connection between the linearized and original model. Finally, we complete the methodology by employing a linear MPC to regulate the linearized model. The performance of the designed method is evaluated by conducting comprehensive simulation studies, including a large-scale network. The simulation results are promising. Eventually, comparing the developed methodology with an equivalent nonlinear MPC verifies a substantial improvement in computational costs.

show abstract

“…In addition to the traffic performance, other research took the safety factors into account. [13] integrated a risk model to the system and designed a multi-objective nonlinear optimization for the coordination of RM. [14] also derived a risk indicator from safety-density relation to be utilized with standard traffic performance indicator, total travel time spent in a horizon-based nonlinear optimal control problem.…”

Section: Introductionmentioning

confidence: 99%

A Feedback Linearization Approach for Coordinated Traffic Flow Management in Highway Systems

Chavoshi¹,

Kouvelas²

2022

Preprint

0

View full text Add to dashboard Cite

This paper aims to develop a traffic control approach that provides an optimal real-time solution for large-scale highway networks. The traffic flow model’s nonlinearity is the main reason for the complex optimization problems that consequently require high computational effort. Feedback linearization is a well-known approach in nonlinear systems control. It can provide an exact linear representation of the original nonlinear system. Thus, it facilitates further steps in the controller design. This research combines the feedback linearization method and linear MPC to simultaneously guarantee optimal performance and real-time feasibility. While developing feedback linearization for METANET model, we discovered a pattern that describes the expansion of the control signals (ramp metering and variable speed limits) and disturbances effects through the highway networks. Utilizing this pattern, we design a generic feedback linearization control law for METANET model. The control law provides the key connection between the linearized and original model. Finally, we complete the methodology by employing a linear MPC to regulate the linearized model. The performance of the designed method is evaluated by conducting comprehensive simulation studies, including a large-scale network. The simulation results are promising. Eventually, comparing the developed methodology with an equivalent nonlinear MPC verifies a substantial improvement in computational costs.

show abstract

Development of Coordinated Ramp-Metering Based on Multi-objective Nonlinear Optimization Functions: Traffic and Safety

Cited by 7 publications

References 7 publications

Untitled

Untitled

A Feedback Linearization Approach for Coordinated Traffic Flow Management in Highway Systems

A Feedback Linearization Approach for Coordinated Traffic Flow Management in Highway Systems

Contact Info

Product

Resources

About