Convex optimization for energy-efficient traffic control

Zu, Yue; Dai, Ran; Dong, Jing

doi:10.1109/cdc.2016.7799310

Cited by 4 publications

(2 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(2) By incorporating simplified solutions in model constraints, an energy-efficient traffic control problem is formulated as CQOP and embedded in a real-time traffic management scheme to efficiently search for optimal commands. (3) Beyond the theoretical development 80 in earlier work (Yue Zu and Dong, 2016), we implement CQOP in VISSIM based on microscopic traffic simulation environment and real-world collected data. By constructing a Component Object Model (COM) interface, the MATLAB generated control commands are connected with VISSIM simulation environments.…”

Section: Introductionmentioning

confidence: 99%

Real-time energy-efficient traffic control via convex optimization

Liu

Dai

et al. 2018

Transportation Research Part C: Emerging Technologies

Self Cite

View full text Add to dashboard Cite

This article proposes a macroscopic traffic control strategy to reduce fuel consumption of vehicles on highways. By implementing Greenshields fundamental diagram, the solution to Moskowitz equations is expressed as linear functions with respect to vehicle inflow and outflow, which leads to generation of a linear traffic flow model. In addition, we build a quadratic cost function in terms of vehicle volume to estimate fuel consumption rate based on COPERT model. A convex quadratic optimization problem is then formulated to generate energy-efficient traffic control decisions in real-time. Simulation results demonstrate significant reduction of fuel consumption on testing highway sections under peak traffic demands of busy hours. AbstractThis article proposes a macroscopic traffic control strategy to reduce fuel consumption of vehicles on highways. By implementing Greenshields fundamental diagram, the solution to Moskowitz equations is expressed as linear functions with respect to vehicle inflow and outflow, which leads to generation of a linear traffic flow model. In addition, we build a quadratic cost function in terms of vehicle volume to estimate fuel consumption rate based on COPERT model. A convex quadratic optimization problem is then formulated to generate energyefficient traffic control decisions in real-time. Simulation results demonstrate significant reduction of fuel consumption on testing highway sections under peak traffic demands of busy hours. based method in a MPC framework. However, although macroscopic traffic flow model, e.g. FASTLANE and METANET, have been adopted in energy-efficient traffic management, it is time consuming to find a convergent solution when a highly nonlinear traffic flow model is considered (Zegeye, 2011). Speed intervals have been used to obtain an approximate solution without solving highly 50 nonlinear dynamics, which results in accumulative errors over time (Dai et al., 2015).This work focuses on managing one type of highway infrastructure, dynamic speed limit signs, to control traffic flow speeds in order to reduce total fuel consumption during a specific time period. We adopt Lighthill-Whitham-Richard 55 (LWR) macroscopic traffic flow model, introduced by Ligthill and Whitham in the 1950's (Lighthill and Whitham, 1955), and COPERT fuel consumption esti-where J f and J t are fuel consumption estimated by COPERT and TTT of all vehicles, respectively. J f,norm and J t,norm denote two nominal values which are used for normalization. They can be obtained by estimating the fuel consumption and TTT in uncontrolled scenario. Weighting factor θ is introduced as an empirical parameter. The newly constructed multi-objective optimization 240 problem is still a CQOP and can be solved using the convex optimization solver

show abstract

Section: Introductionmentioning

confidence: 99%

Real-time energy-efficient traffic control via convex optimization

Liu

Dai

et al. 2018

Transportation Research Part C: Emerging Technologies

Self Cite

View full text Add to dashboard Cite

show abstract

“…Optimal control methods for a traffic network based on viability framework are proposed in [34], [35], where they demonstrate how the new method has reduced the computational complexity. The framework has also been used to develop a convex optimization approach to reduce the fuel consumption in [38]. Also a recent work [43] considered a H-J PDE with viscous term that allowed them to perform a feedback linearisation, which enabled tracking a desired timedependent state on some fixed space point.…”

mentioning

confidence: 99%

Boundary Control Design for Traffic With Nonlinear Dynamics

Tumash

Wit

Monache

2022

IEEE Trans. Automat. Contr.

View full text Add to dashboard Cite

We address a problem of boundary control for a nonlinear scalar conservation law. Namely, this paper is devoted to the boundary control of an LWR PDE with triangular flux function evolving along a single road. The target state is a time-and space-dependent trajectory. The boundary control law is constructed using the analytical solution of the Hamilton-Jacobi equation, which is an integral form of the LWR PDE. We design a feedback controller and illustrate its performance on a numerical example using the Godunov scheme. Index Terms-boundary control problem, Hamilton-Jacobi formulation, LWR model, partial differential equations, traffic control. I. INTRODUCTION A. Motivation and Literature Review C ONSERVATION laws are a very important topic to study nowadays, since a significant part of physical systems is based on the principle of the conservation of some quantity, for example, mass or energy. Urban and highway traffic behaviour is modeled via conservation laws with the principle of preserving the number of cars. The first work describing the behaviour of traffic on a macroscopic scale was proposed by Lighthill, Whitham [2], and, independently, Richards [3] in the fifties (LWR model). The LWR model is a first-order model based on the conservation of mass equation. Despite the appearance of more sophisticated first order [14], [16], [17] or even higher order models capable of covering more realistic traffic behaviour [13], [18], the LWR model remains the most used one to study traffic behaviour due to its simplicity. Mathematically, the LWR model is a hyperbolic scalar conservation law with a nonlinear concave flux function, which represents an empirical relation between flow and density, see [25] for a detailed review.Traffic congestion represents a considerable issue worldwide that negatively impacts traffic mobility, especially in large urban areas, which makes traffic management an important Manuscript

show abstract

Distributed traffic control for reduced fuel consumption and travel time in transportation networks

Dai

Dong

2015

2015 European Control Conference (ECC)

Self Cite

View full text Add to dashboard Cite

This paper proposes a distributed framework for optimal control of vehicles in transportation networks. The objective is to reduce the balanced fuel consumption and travel time through hybrid control on speed limit and ramp metering rate. The dual decomposition theory associated with the subgradient method is then applied in order to decompose the optimal control problem into a series of suboptimal problems and then solve them individually via networked road infrastructures (RIs). Coordination among connected RIs is followed in each iteration to update the individual controls. An example is demonstrated to verify the reduction in terms of fuel consumption and travel time using the proposed approach.

show abstract

Convex optimization for energy-efficient traffic control

Cited by 4 publications

References 19 publications

Real-time energy-efficient traffic control via convex optimization

Real-time energy-efficient traffic control via convex optimization

Boundary Control Design for Traffic With Nonlinear Dynamics

Distributed traffic control for reduced fuel consumption and travel time in transportation networks

Contact Info

Product

Resources

About