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