Alfréd András Csikós

Modeling and optimal control of travel times and traffic emission on freeways

Abstract In this paper a modeling method and a control approach is proposed for minimising both travel times and traffic emission on freeways. A simulation-based investigation among emission models is performed to determine the model to be engaged for a model-based control. The chosen model is imposed on a second-order macroscopic traffic model. A constrained LQ control is proposed for optimization. An emission-optimal control and a multicriteria (travel time and emission) optimization are compared to conventional, solely travel-time optimal control. Simulations prove that ramp metering can be used to reduce both emission and travel times on motorways.

Freeway shockwave control using ramp metering and variable speed limits

In this work a novel controller design method is suggested for motorway shockwave management using ramp metering and variable speed limit (VSL) control. The proposed controller has a feedforward-feedback control structure that is designed for a motorway arterial model. For the feedback design the nonlinear model predictive control is used. The feedforward control is utilized to enhance the operability of the control system to high disturbances. Two different controllers are designed: while controller A uses continuous VSL signs, VSL input values of controller B is chosen from a discrete set. For the latter, a two-step optimization is used to decrease oscillations. The designed controllers are tested in a case study, in which a total traffic breakdown situation is modeled. In the uncontrolled case, the initial perturbation leads to a traffic jam with zero traffic speed, whereas the proposed control design is capable of preventing the congestion.

Traffic speed prediction method for urban networks — an ANN approach

The paper proposes a traffic speed prediction algorithm for urban road traffic networks. The motivation of the prediction is to provide short time forecast in order to support ITS (Intelligent Transport System) functionalities, such as traveler information systems, route guidance (navigation) systems, as well as adaptive traffic control systems. A potential and efficient solution to this problem is the application of a soft computing method. Namely, an artificial neural network (ANN) is used for the forecast by involving the measured speed patterns. The ANN is trained by using data produced by Vissim (a microscopic road traffic simulator) simulations. The proposed algorithm is developed and analyzed on a real-word test network (part of downtown in Budapest).

A simple dynamic model for the dispersion of motorway traffic emission

In this work a modeling approach is introduced for the dispersion of motorway traffic emissions. The process model is developed for a distributed parameter system, and is derived based on the conservation law within the balance volumes between the road and the rural area, specified by the wind direction. Parallel to the wind, plug flow is considered, and for the absorption of pollution a simplified version of the Gaussian plume model is used. For the boundary conditions of the model, the output of the macroscopic emission model, introduced in [Csikós et al. (2012)] is substituted. A sensitivity analysis is performed on the proposed model which justifies the preconception on the future control system structure.

Design of platoon velocity based on multi-criteria optimization

Abstract The paper focuses on the design of the velocity of a platoon based on fuel consumption, road slopes, emissions and traveling time. Since the performance specifications are in contradiction, the design task leads to a multi-criteria optimization procedure. Moreover, the differences between the dynamics of the vehicles in the platoon should be taken into consideration. The goal of this paper is to develop an optimization method for the velocity of the platoon which creates a balance between the different performance factors. The design of the platoon control is based on the robust ℋ ∞ control theory. The method is illustrated through simulation examples, which show that a balance between energy saving, the minimization of traveling time and emission can be obtained.

Macroscopic modeling and control of emission in urban road traffic networks

AbstractThis work suggests a framework for modeling the traffic emissions in urban road traffic networks that are described by the Network Fundamental Diagram (NFD) concept. Traffic emission is formalized in finite spatiotemporal windows as a function of aggregated traffic variables, i.e. Total Travel Distances (TTDs) in the network and network average speed. The framework is extended for the size of an urban network during a signal cycle – the size of a window in which the network aggregated parameters are modeled in the NFD concept. Simulations have been carried out for model accuracy analysis, using the microscopic Versit + Micro model as reference. By applying the macroscopic emission model function and the traffic modeling relationships, the control objective for pollution reduction has also been formalized. Basically, multi-criteria control design has been introduced for two criteria: maximization of the TTD and minimization of traffic emissions within the network.

Road inclinations and emissions in platoon control via multi-criteria optimization

A well-organized platoon control may have advantages in terms of increasing highway capacity and decreasing fuel consumption and emissions. The paper proposes the design of the velocity of platoon. In the velocity design several factors must be taken into consideration such as fuel consumption, road inclinations, emissions and traveling time. Since the vehicles in a heterogeneous platoon have different dynamic abilities, emission parameters, and fuel characteristics, the design task leads to a multi-criteria optimization problem. The design of the platoon control is based on the robust H∞ control method. The method is illustrated through simulation examples.

Motorway control system for the reduction of pollutant concentrations in local rural areas

In this work a control system is developed for the limitation of pollutant concentrations of rural areas near motorways. The controlled system is based on the second-order macroscopic model description of the freeway traffic, extended by an emission dispersion model, introduced in [1]. The control of the system is realized by ramp metering, optimized by the nonlinear model predictive control method. Simulation results show a good performance during changing disturbances.

Multicriteria Cruise Control Design Considering Geographic and Traffic Conditions

The paper presents the design of cruise control systems considering road and traffic information during the design of speed trajectories. Several factors are considered such as road inclinations, traffic lights, preceding vehicles, speed limits, engine emissions and travel times. The purpose of speed design is to reduce longitudinal energy, fuel consumption and engine emissions without a significant increase in travel time. The signals obtained from the road and traffic are handled jointly with the dynamic equations of the vehicle and built into the control design of reference speed. A robust H∞ control is designed to achieve the speed of the cruise control, guaranteeing the robustness of the system against disturbances and uncertainties.

Multicriteria ramp metering control considering environmental and traffic aspects

Abstract In this paper a multicriteria ramp metering control is designed considering three criteria: traffic performance and the local– and global effects of traffic emission. For real-time emission modeling a macroscopic modeling framework is proposed using an average-speed emission model. Based on the proposed model function cost functions regarding the global and local effects of traffic emission are stated. Traffic control is realized via ramp metering and the control input is optimized by using the NMPC technique. The closed-loop simulation of the designed control is carried out in VISSIM microscopic simulator.