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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2005.02.032 Byline: Vaya Dinopoulou, Christina Diakaki, Markos Papageorgiou Keywords: Traffic control; Optimal control; Urban traffic control Abstract: Despite the long-lasting research and developments in the field of urban traffic control systems, the continuously increasing mobility requirements urge for solutions that will release urban areas from the serious congestion problems and their consequences. From the control point of view, this may be translated into the employment of traffic-responsive systems that respond automatically to the prevailing traffic conditions. This is the aim of the signal control strategy TUC, whose basic philosophy, design methodology, characteristics and application results under both simulated and field conditions are presented in this paper. Based on a store-and-forward type of mathematical modelling and using well-known methodological tools from Automatic Control Theory, the TUC strategy addresses in a simple but efficient way, as demonstrated from the applications so far, the problem of co-ordinated, traffic-responsive signal control in large-scale urban networks. Author Affiliation: Dynamic Systems and Simulation Laboratory, Technical University of Crete, Greece

The methods used for designing the motorway network traffic control strategies and the available control measures in terms of design, operating features, ramp metering, route guidance and link control are discussed. An advanced coordinated ramp metering control, based on large-scale optimisation that is applied to the Amsterdam ring-road is presented to support the discussion.

An optimal control algorithm used to solve integrated dynamic flow optimization problems based on feasible direction search and the reduced gradient is ideal in large scale discrete time optimal control problems. The method was used in computing for the integrated optimal flow control in single destination traffic networks. This approach is a feasible alternative to other optimization methods and can be adapted to divergent applications such as communication networks where similar problems are commonplace.

A discrete-time stochastic optimal control problem was recently proposed to address the GLOSA (Green Light Optimal Speed Advisory) problem in cases where the next signal switching time is decided in real time and is therefore uncertain in advance. The corresponding numerical solution via SDP (Stochastic Dynamic Programming) calls for substantial computation time, which excludes problem solution in the vehicle's on-board computer in real time. In this context, the present paper concentrates on the challenge of developing numerical algorithms to solve efficiently the stochastic GLOSA problem. As a first attempt to overcome the computation time bottleneck, a modified version of Dynamic Programming, known as Discrete Differential Dynamic Programming (DDDP) was recently employed for the numerical solution of the stochastic optimal control problem and was demonstrated to achieve results equivalent to those obtained with the ordinary SDP algorithm, albeit with significantly reduced computation times. After an outline of the DDDP approach, the present work considers a second modified version of Dynamic Programming, known as Differential Dynamic Programming (DDP). For the stochastic GLOSA problem, it is demonstrated that DDP achieves quasi-instantaneous (extremely fast) solutions in terms of CPU times, which allows for the proposed approach to be readily executable online, in an MPC (Model Predictive Control) framework, in the vehicle's on-board computer. The novel numerical approach is tested and demonstrated by use of realistic examples and is compared to the SDP and DDDP solutions. It should be noted that DDP does not require discretization of variables, hence the obtained solutions may be slightly superior to the standard SDP solutions. [ABSTRACT FROM AUTHOR]

The paper provides results for the stabilization of a spatially uniform equilibrium profile for a scalar conservation law that arises in the study of traffic dynamics under variable speed limit control. Two different control problems are studied: the problem with free speed limits at the inlet and the problem with no speed limits at the inlet. Explicit formulas are provided for respective feedback laws that guarantee stabilization of the desired equilibrium profile. For the first problem, global asymptotic stabilization is achieved; while for the second problem, regional exponential stabilization is achieved. Moreover, the solutions for the corresponding closed-loop systems are guaranteed to be classical solutions, i.e., there are no shocks. The obtained results are illustrated by means of a numerical example. [ABSTRACT FROM AUTHOR]

Proposed or emerging vehicle automation and communication systems (VACS) may contribute to the mitigation of motorway traffic congestion on the basis of appropriate traffic control strategies. In this context, this paper presents a novel first-order multi-lane macroscopic traffic flow model for motorways which is mainly intended for use within a related optimal control problem formulation. The model’s starting point is close to the well-known CTM (cell-transmission model), which is modified and extended to consider additional aspects of the traffic dynamics, such as lane changing and the capacity drop, via appropriate procedures for computing lateral and longitudinal flows. The model has been derived with a view to combine realistic traffic flow description with a simple (linear or piecewise linear) mathematical form, which can be exploited for efficient optimal control problem formulations, as described in a companion (Part II) paper. Although the model has been primarily derived for use in future traffic conditions including VACS, it may also be used for conventional traffic flow representation. In fact, the accuracy of the proposed modelling approach is demonstrated through calibration and validation procedures using real data from an urban motorway located in Melbourne, Australia. [ABSTRACT FROM AUTHOR]

Integrated motorway traffic flow control considering the use of Vehicle Automation and Communication Systems (VACS) is considered in this paper. VACS may act both as sensors (providing information on traffic conditions) and as actuators, permitting the deployment of ramp metering, variable speed limits, and lane changing control. The integrated traffic control problem is addressed through the formulation of a linearly constrained optimal control problem based on the first-order multi-lane model for motorways introduced and validated in a companion paper (Part I). A case study illustrating the potential improvements achievable using this approach is presented. [ABSTRACT FROM AUTHOR]

During the last decade, there has been an enormous interdisciplinary effort by the automobile industry and numerous research institutions worldwide towards the development, testing and employment of a variety of Vehicle Automation and Communication Systems (VACS) with the main aims to improve road safety and driver convenience. Some VACS, however, have a direct impact on road efficiency as well and could therefore be exploited to relieve road networks from the significant congestion problems and their negative consequences for travel times, safety, fuel consumption, the environment and the quality of life in general. In other words, some of the available VACS could also be used as novel or innovative sensors, actuators and tools towards a new era of traffic management. This paper provides an overview of proposed and available VACS and discusses their perspectives from the motorway traffic management point of view. Classifications of the different systems in this respect are also provided, while SWOT (Strengths–Weaknesses–Opportunities–Threats) analyses are used to identify specific exploitation ways. Current trends and future perspectives of VACS within a motorway traffic management context are finally summarised. [ABSTRACT FROM AUTHOR]

A path-planning algorithm for connected and non-connected automated road vehicles on multilane motorways is derived from the opportune formulation of an optimal control problem. In this framework, the objective function to be minimized contains appropriate respective terms to reflect: the goals of vehicle advancement; passenger comfort; and avoidance of collisions with other vehicles and of road departures. Connectivity implies, within the present work, that connected vehicles can exchange with each other (V2V) real-time information about their last generated short-term path. For the numerical solution of the optimal control problem, an efficient feasible direction algorithm (FDA) is used. To ensure high-quality local minima, a simplified Dynamic Programming (DP) algorithm is also conceived to deliver the initial guess trajectory for the start of the FDA iterations. Thanks to very low computation times, the approach is readily executable within a model predictive control (MPC) framework. The proposed MPC-based approach is embedded within the Aimsun microsimulation platform, which enables the evaluation of a plethora of realistic vehicle driving and advancement scenarios under different vehicles mixes. Results obtained on a multilane motorway stretch indicate higher efficiency of the optimally controlled vehicles in driving closer to their desired speed, compared to ordinary manually driven vehicles. Increased penetration rates of automated vehicles are found to increase the efficiency of the overall traffic flow, benefiting manual vehicles as well. Moreover, connected controlled vehicles appear to be more efficient in achieving their desired speed, compared also to the corresponding non-connected controlled vehicles, due to the improved real-time information and short-term prediction achieved via V2V communication. [ABSTRACT FROM AUTHOR]

Highlights: [•] Network fundamental diagrams, based on a reduced amount of measurements, are derived. [•] Reduced NFDs exhibit a critical range of traffic states equivalent to the complete NFD. [•] Efficient feedback-based gating is possible by applying few real-time measurements. [•] Delay and mean speed improved by 30% in cases with complete and reduced measurements. [ABSTRACT FROM AUTHOR]

Abstract: Real-data testing results of a real-time nonlinear freeway traffic state estimator are presented with a particular focus on its adaptive features. The pursued general approach to the real-time adaptive estimation of complete traffic state in freeway stretches or networks is based on stochastic nonlinear macroscopic traffic flow modeling and extended Kalman filtering. One major innovative aspect of the estimator is the real-time joint estimation of traffic flow variables (flows, mean speeds, and densities) and some important model parameters (free speed, critical density, and capacity), which leads to four significant features of the traffic state estimator: (i) avoidance of prior model calibration; (ii) automatic adaptation to changing external conditions (e.g. weather and lighting conditions, traffic composition, control measures); (iii) enabling of incident alarms; (iv) enabling of detector fault alarms. The purpose of the reported real-data testing is, first, to demonstrate feature (i) by investigating some basic properties of the estimator and, second, to explore some adaptive capabilities of the estimator that enable features (ii)–(iv). The achieved testing results are quite satisfactory and promising for further work and field applications. [Copyright &y& Elsevier]

Abstract: This paper reports on real data testing of a real-time freeway traffic state estimator, with a particular focus on its adaptive capabilities. The pursued general approach to the real-time adaptive estimation of complete traffic state in freeway stretches or networks is based on stochastic macroscopic traffic flow modeling and extended Kalman filtering. One major innovative feature of the traffic state estimator is the online joint estimation of important model parameters (free speed, critical density, and capacity) and traffic flow variables (flows, mean speeds, and densities), which leads to three significant advantages of the estimator: (1) avoidance of prior model calibration; (2) automatic adaptation to changing external conditions (e.g. weather and lighting conditions, traffic composition, control measures); (3) enabling of incident alarms. These three advantages are demonstrated via suitable real data testing. The achieved testing results are satisfactory and promising for subsequent applications. [Copyright &y& Elsevier]

Abstract: The number of vehicles included in a metered motorway ramp or an urban signalized link at any time is valuable information for real-time control. A Kalman-Filter is employed to produce reliable estimates of this quantity based on real-time measurements of flow and occupancy provided by (at least) three loop detectors. The resulting vehicle-count estimator is tested via microscopic simulation for a variety of metered ramp scenarios and traffic conditions. Several related fundamental issues are addressed: the effects of loop density, update period, downstream signal cycle, vehicle length and link length. The simulation investigations indicate a robust estimation performance with low calibration effort needed, which facilitates easy applicability of the method. [Copyright &y& Elsevier]

Abstract: The relationships between instantaneous space-variables and (easily measurable) local time-variables in largely homogeneous and stationary traffic flow, as typically encountered in uninterrupted traffic conditions, are briefly reviewed. An elaborate analysis and microscopic simulation investigation is conducted with respect to the same relationships at signalized links with inherently strong traffic flow variations triggered by traffic signal switchings. A number of influencing factors when estimating space-variables from measured local time-variables is analysed and illustrated in detail. [Copyright &y& Elsevier]

Abstract: The paper presents a unified macroscopic model-based approach to real-time freeway network traffic surveillance as well as a software tool RENAISSANCE that has been recently developed to implement this approach for field applications. RENAISSANCE is designed on the basis of stochastic macroscopic freeway network traffic flow modeling, extended Kalman filtering, and a number of traffic surveillance algorithms. Fed with a limited amount of real-time traffic measurements, RENAISSANCE enables a number of freeway network traffic surveillance tasks, including traffic state estimation and short-term traffic state prediction, travel time estimation and prediction, queue tail/head/length estimation and prediction, and incident alarm. The traffic state estimation and prediction lay the operating foundation of RENAISSANCE since RENAISSANCE bases the other traffic surveillance tasks on its traffic state estimation or prediction results. The paper first introduces the utilized stochastic macroscopic freeway network traffic flow model and a real-time traffic measurement model, upon which the complete dynamic system model of RENAISSANCE is established with special attention to the handling of some important model parameters. The algorithms for the various traffic surveillance tasks addressed are described along with the functional architecture of the tool. A simulation test was conducted via application of RENAISSANCE to a hypothetical freeway network example with a sparse detector configuration, and the testing results are presented in some detail. Final conclusions and future work are outlined. [Copyright &y& Elsevier]

A general approach to the real-time estimation of the complete traffic state in freeway stretches is developed based on the extended Kalman filter. First, a general stochastic macroscopic traffic flow model of freeway stretches is presented, while some simple formulae are proposed to model real-time traffic measurements. Second, the macroscopic traffic flow model along with the measurement model is organized in a compact state-space form, based on which a traffic state estimator is designed by use of the extended-Kalman-filtering method. While constructing the traffic state estimator, special attention is paid to the handling of the boundary conditions and unknown parameters of the macroscopic traffic flow model. A number of simulations are conducted to test the designed traffic state estimator under various traffic situations in a freeway stretch with on/off-ramps and a long inter-detector distance. Some key issues are carefully investigated, including tracking capability of the traffic state estimator, comparison of various estimation schemes, evaluation of different detector configurations, significance of the on-line model parameter estimation, sensitivity of the traffic state estimator to the initial values of the estimated model parameters and to the related standard deviation values, and dynamic tracking of time-varying model parameters. The achieved simulation results are very promising for the subsequent development and testing work that is briefly outlined. [Copyright &y& Elsevier]

Abstract: The Advanced Motorway Optimal Control (AMOC) strategy for optimal freeway network-wide ramp metering is applied to the ring-road of Amsterdam, The Netherlands, in the aim of investigating some important and interesting problems arising in ubiquitous ramp metering systems. A number of suitably chosen scenarios along with a thorough analysis, interpretation, and suitable visualization of the obtained results provide a basis for the better understanding of some complex interrelationships of competing performance criteria. More precisely, the strategy’s efficiency and equity properties as well as their trade-off are studied and their partially competitive behaviour is discussed. This trade-off is implicitly addressed by the AMOC strategy through consideration of the available ramp storage space and may be used as a tool to establish a desired policy of the system’s efficiency versus equity. [Copyright &y& Elsevier]

An extension of the feedback local ramp metering strategy ALINEA is proposed that allows the automatic tracking of the critical occupancy to help maximize the mainstream flow. The developed AD-ALINEA strategy may be valuable whenever the critical occupancy cannot be estimated beforehand or is subject to real-time change due to changing environmental conditions or traffic composition (e.g. trucks). An upstream-measurement based version of the adaptive strategy (AU-ALINEA) is also developed. Both strategies are successfully tested in a stochastic macroscopic simulation environment under various scenarios. [Copyright &y& Elsevier]

The paper presents the design approach, the objectives, the development, the advantages, and some application results of the traffic-responsive urban control (TUC) strategy. Based on a store-and-forward modelling of the urban network traffic and using the linear-quadratic regulator theory, the design of TUC leads to a multivariable regulator for traffic-responsive co-ordinated network-wide signal control that is particularly suitable also for saturated traffic conditions. Simulation investigations demonstrate the efficiency of the proposed approach. Results of TUC''s first field implementation and evaluation are also presented. Finally, summarising conclusions are drawn and future work is outlined. [Copyright &y& Elsevier]

Presents information on the work performed within the European DRIVE II Project European Urban Corridor Control (EUROCOR) in relation to modelling and integrated controls of the M8 Eastbound Corridor in Glasgow. Description of the M8 Eastbound Corridor; Details on the application of METACOR to the M8 Eastbound Corridor.

Presents a unified approach to the design of integrated control strategies for traffic corridors of arbitrary topology including both motorways and signal-controlled urban roads. Approach based on suitable application of the store-and-forward modeling philosophy that leads to the formulation of linear optimal-control problem involving a number of possible control actions.

This study develops and proposes a unifying control scheme to address the ramp and mainline metering problems arising in freeways. A distinguishing novelty of the proposed approach is that it can inherently be applied both at local and coordinated levels. The proposed strategy is based on a recently developed nonlinear adaptive control scheme, consisting of a nominal feedback law in conjunction with a nonlinear observer, which aims to estimate some unknown system variables. The present study provides insights into and demonstrates the properties and the performance of the proposed methodology, which is tested for realistic traffic scenarios using a macroscopic traffic flow simulator as a surrogate for potential field application. Comparison tests have been performed with other control strategies proposed in the literature and employed already in the field. [ABSTRACT FROM AUTHOR]

Highlights • New macroscopic model for Variable Speed Limits (VSLs). • Calibration and validation of the most well-known macroscopic models for VSLs. • The capacity of a freeway is reduced if a Variable Speed Limit is decreased. • When densities are increased, the VSL-induced speeds start to decrease substantially. Abstract The goals of this paper are to analyze the effects of Variable Speed Limits (VSLs) on freeway traffic flow, to propose a new macroscopic model for VSL, and to compare, calibrate and validate the most well known macroscopic models for VSL using real data from a stretch of the A12 freeway in The Netherlands. Firstly, a new macroscopic model for VSLs is presented, combining characteristics of previously proposed models, in order to have the capability of modeling different capacities, critical densities, and levels of compliance for segments affected by speed limits. Subsequently, the effects of VSLs on the fundamental diagram of traffic flow are studied concluding that, at least for the considered stretch of the A12 freeway, the capacity of the freeway segment is decreased (and the critical density is increased) when the speed limit is reduced from 120 to 90 km/h. Furthermore, analyzing a wider range of VSLs, it is shown that the VSL-induced fundamental diagram is not triangular and that the speed limit compliance can be very low if enforcement measures are not applied. Finally, the proposed model is compared analytically, numerically, and graphically with the two most well-known macroscopic models for VSLs. The analysis and the simulation results show that the proposed model delivers more accurate predictions in cases where the compliance is low and/or the capacity is reduced by the use of VSLs. [ABSTRACT FROM AUTHOR]

Real-time estimation of the traffic state in urban signalized links is valuable information for modern traffic control and management. In recent years, with the development of in-vehicle and communication technologies, connected vehicle data has been increasingly used in literature and practice. In this work, a novel data fusion approach is proposed for the high-resolution (second-by-second) estimation of queue length, vehicle accumulation, and outflow in urban signalized links. Required data includes input flow from a fixed detector at the upstream end of the link as well as location and speed of the connected vehicles. A probability-based approach is derived to compensate the error associated with low penetration rates while estimating the queue tail location, which renders the proposed methodology more robust to varying penetration rates of connected vehicles. A well-defined nonlinear function based on traffic flow theory is developed to attain the number of vehicles inside the queue based on queue tail location and average speed of connected vehicles. The overall scheme is thoroughly tested and demonstrated in a realistic microscopic simulation environment for three types of links with different penetration rates of connected vehicles. In order to test the efficiency of the proposed methodology in case that data are available at higher sampling times, the estimation procedure is also demonstrated for different time resolutions. The results demonstrate the efficiency and accuracy of the approach for high-resolution estimation, even in the presence of measurement noise. [ABSTRACT FROM AUTHOR]

A model-based traffic state estimation approach is developed for per-lane density estimation as well as on-ramp and off-ramp flows estimation for highways in presence of connected vehicles. Three are the basic ingredients of the developed estimation scheme: (1) a data-driven version of the conservation-of-vehicles equation (in its time- and space-discretized form); (2) the utilization of position and speed information from connected vehicles’ reports, as well as total flow measurements obtained from a minimum number (sufficient for the observability of the model) of fixed detectors, such as, for example, at the main entry and exit of a given highway stretch; and (3) the employment of a standard Kalman filter. Furthermore, necessary and sufficient conditions for the (strong) structural observability of the introduced model are established (properties, which are rarely studied in the literature on traffic estimation), which yield the fixed detectors requirements needed for the proper operation of the developed estimation scheme. The performance of the estimation scheme is evaluated for various penetration rates of connected vehicles utilizing real microscopic traffic data collected within the Next Generation SIMulation (NGSIM) program. It is shown that the estimation performance is satisfactory, in terms of a suitable metric, even for low penetration rates of connected vehicles. The sensitivity of the estimation performance to variations of the model parameters (two in total) is also quantified, and it is shown that, overall, the estimation scheme is little sensitive to the model parameters. [ABSTRACT FROM AUTHOR]

Due to the noticeable environmental and economical problems caused by traffic congestion and by the emissions produced by traffic, analysis and control of traffic is essential. One of the various traffic analysis approaches is the model-based approach, where a mathematical model of the traffic system is developed/used based on the governing physical rules of the system. In this paper, we propose a framework to interface and integrate macroscopic flow models and microscopic emission models. As a result, a new mesoscopic integrated flow-emission model is obtained that provides a balanced trade-off between high accuracy and low computation time. The proposed approach considers an aggregated behavior for different groups of vehicles (mesoscopic) instead of considering the behavior of individual vehicles (microscopic) or the entire group of vehicles (macroscopic). A case study is done to evaluate the proposed framework, considering the performance of the resulting mesoscopic integrated flow-emission model. The traffic simulation software SUMO combined with the microscopic emission model VT-micro is used as the comparison platform. The results of the case study prove that the proposed approach provides excellent results with high accuracy levels. In addition, the mesoscopic nature of the integrated flow-emission model guarantees a low CPU time, which makes the proposed framework suitable for real-time model-based applications. [ABSTRACT FROM AUTHOR]

One of the main triggers of traffic congestion on highways is vehicle merging at on-ramps. The development of automated procedures for cooperative vehicle merging is aimed to ensure safety and alleviate congestion problems. In this work, a longitudinal trajectory planning methodology is presented, developed to assist the merging of vehicles on highways; it achieves safe and traffic-efficient merging, while minimizing the engine effort and passenger discomfort through the minimization of acceleration and its first and second derivatives during the merging maneuver. The problem is formulated as a finite-horizon optimal control problem and is solved analytically. This enables the solution to be stored on-board, saving computational time and rendering the methodology suitable for practical applications. The tunable weights, used for taking into account the different optimization criteria, may serve as parameters to match the individual driver’s preferences. The proposed methodology is first developed for a pair of cooperating vehicles, a merging one and its putative leader. Moreover, an alternative solution procedure via a time-variant Linear-Quadratic Regulator approach is also presented. A Model Predictive Control (MPC) scheme is utilized to compensate possible disturbances in the trajectories of the cooperating vehicles, whereby the analytical optimal solution is applied repeatedly in real time, using updated measurements, until the merging procedure is actually finalized. Subsequently, the methodology is generalized for a set of vehicles inside the merging area. Various numerical simulations illustrate the validity and applicability of the method. [ABSTRACT FROM AUTHOR]

In this paper, we design decentralized control strategies for the two-dimensional movement of autonomous vehicles on lane-free roads. The behavior of the autonomous vehicles resembles that of self-driven particles that individually produce their driving force and steering, while interacting with each other, giving rise to an emerging particle traffic flow. The bicycle kinematic model is used to model the dynamics of the vehicles, and each vehicle determines its control input based only on its own state and on the relative displacement vector from other (adjacent) vehicles and the boundary of the road. The resulting control system is nonlinear and evolves on a specific open set. Therefore, the feedback design is challenging and is accomplished by means of a control Lyapunov function methodology. Potential functions and Barbălat's lemma are employed to prove the following properties, which are ensured by the proposed nonlinear controller: (i) the vehicles do not collide with each other or with the boundary of the road; (ii) the speeds of all vehicles are always positive, i.e., no vehicle moves backwards at any time; (iii) the speed of all vehicles remain below a given speed limit; (iv) all vehicle speeds converge to a given longitudinal speed set-point; and (v) the accelerations, lateral speeds, and orientations of all vehicles tend to zero. The efficiency of the proposed 2-D cruise controllers is illustrated by means of numerical examples. [ABSTRACT FROM AUTHOR]

A widespread deployment of vehicle automation and communication systems (VACS) is expected in the next years. This may lead to improvements in traffic management efficiency because of the novel possibilities of using VACS both as sensors and as actuators, as well as of a variety of new communications channels (vehicle-to-vehicles, vehicle-to-infrastructure) and related opportunities. To achieve this traffic flow efficiency, appropriate studies, developing potential control strategies to exploit the VACS availability, are essential. This paper describes a hierarchical model predictive control framework that can be used for the coordinated and integrated control of a motorway system, considering that an amount of vehicles are equipped with specific VACS. The concept employs and exploits the synergistic (integrated) action of a number of old and new control measures, including ramp metering, vehicle speed control, and lane changing control at a macroscopic level. The effectiveness and the computational feasibility of the proposed approach are demonstrated via microscopic simulation for a variety of penetration rates of equipped vehicles. [ABSTRACT FROM AUTHOR]

The well-known feedback ramp metering algorithm ALINEA can be applied for local ramp metering or included as a key component in a coordinated ramp metering system. ALINEA uses real-time occupancy measurements from the ramp flow merging area that may be at most a few hundred meters downstream of the metered on-ramp nose. In many practical cases, however, bottlenecks with smaller capacities than the merging area may exist further downstream, which suggests using measurements from those downstream bottlenecks. Recent theoretical and simulation studies indicate that ALINEA may lead to poorly damped closed-loop behavior in this case, but PI-ALINEA, a suitable Proportional-Integral (PI) extension of ALINEA, can lead to satisfactory control performance. This paper addresses the same local ramp-metering problem in the presence of far-downstream bottlenecks, with a particular focus on the employment of PI-ALINEA to tackle three distinct cases of bottleneck that may often be encountered in practice: (1) an uphill case; (2) a lane-drop case; and (3) an un-controlled downstream on-ramp case. Extensive simulation studies are conducted on the basis of a macroscopic traffic flow model to show that ALINEA is not capable of carrying out ramp metering in these bottleneck cases, while PI-ALINEA operates satisfactorily in all cases. A field application example of PI-ALINEA is also reported with regard to a real case of far downstream bottlenecks. With its control parameters appropriately tuned beforehand, PI-ALINEA is found to be universally applicable, with little fine-tuning required for field applications. [ABSTRACT FROM AUTHOR]

Ramp metering (RM) is the most direct and efficient tool for the motorway traffic flow management. However, because of the usually short length of the on-ramps, RM is typically deactivated to avoid interference of the created ramp queue with adjacent street traffic. By the integration of local RM with mainstream traffic flow control (MTFC) enabled via variable speed limits (VSL), control operation upstream of active bottlenecks could be continued even if the on-ramp is full or if the RM lower bound has been reached. Such integration is proposed via the extension of an existing local cascade feedback controller for MTFC-VSL by use of a split-range-like scheme that allows different control periods for RM and MTFC-VSL. The new integrated controller remains simple yet efficient and suitable for field implementation. The controller is evaluated in simulation for a real motorway infrastructure (a ring-road) fed with real (measured) demands and compared to stand-alone RM or MTFC-VSL, both with feedback and optimal control results. The controller’s performance is shown to meet the specifications and to approach the optimal control results for the investigated scenario. [ABSTRACT FROM AUTHOR]

Abstract: The continuously increasing daily traffic congestions on motorway networks around the world call for innovative control measures that would drastically improve the current traffic conditions. Mainstream traffic flow control (MTFC) is proposed as a novel and efficient motorway traffic management tool, and its possible implementation and principal impact on traffic flow efficiency is analysed. Variable speed limits, suitably operated and enforced, is considered as one (out of several possible) way(s) for MTFC realisation, either as a stand-alone measure or in combination with ramp metering. A previously developed, computationally efficient software tool for optimal integrated motorway network traffic control including MTFC is applied to a large-scale motorway ring-road. It is demonstrated via several investigated control scenarios that traffic flow can be substantially improved via MTFC with or without integration with coordinated ramp metering actions. [Copyright &y& Elsevier]

Lane-free vehicle movement has been recently proposed for connected automated vehicles (CAV) due to various potential advantages. One such advantage stems from the fact that incremental changes of the road width in lane-free traffic lead to corresponding incremental changes of the traffic flow capacity. Based on this property, the concept of internal boundary control was recently introduced to flexibly share the total road width and capacity among the two traffic directions of a highway in real-time, in response to the prevailing traffic conditions, so as to maximize the cross-road (both directions) infrastructure utilization. Feedback-based Linear–Quadratic regulators with or without Integral action (LQI and LQ regulators) are appropriately developed in this paper to efficiently address the internal boundary control problem. Simulation investigations, involving a realistic highway stretch and different demand scenarios, demonstrate that the proposed simple regulators are robust and similarly efficient as an open-loop nonlinear constrained optimal control solution, while circumventing the need for accurate modelling and external demand prediction. [ABSTRACT FROM AUTHOR]

• Presenting optimal internal boundary control for lane-free automated vehicle traffic. • Converting CTM nonlinear model to linear model and inclusion in the constraints of a QP (Quadratic Programming) problem. • Employing QP to solve the internal boundary control problem. • Considering capacity drop in order to cover accurate behavior of traffic. A recently proposed paradigm for vehicular traffic in the era of CAV (connected and automated vehicles), called TrafficFluid, involves lane-free vehicle movement. Lane-free traffic implies that incremental road widening (narrowing) leads to corresponding incremental increase (decrease) of capacity; and this opens the way for consideration of real-time internal boundary control on highways and arterials, in order to flexibly share the total (both directions) road width and capacity among the two directions in dependence of the bi-directional demand and traffic conditions, so as to maximize the total (two directions) flow efficiency. The problem is formulated as a convex QP (Quadratic Programming) problem that may be solved efficiently, and representative case studies shed light on and demonstrate the features, capabilities and potential of the novel control action. [ABSTRACT FROM AUTHOR]

• Microscopic implementation of the Internal Boundary Control in lane-free environments. • Enhancing LQR Performance in Internal Boundary Control by Incorporating Feedforward Extension. • Design of appropriate vehicle movement strategy for lane-free environments. • Internal Boundary Control-induced extensions of the lane-free microscopic simulator TrafficFluid-Sim. The recently introduced TrafficFluid concept proposes that automated vehicles drive lane-free, thus enabling capacity sharing between the two opposite road directions via real-time Internal Boundary Control (IBC). This novel traffic control measure was demonstrated, using macroscopic traffic flow models, to deliver unprecedented improvements of traffic flow efficiency. The present study completes and validates the IBC concept in a much more realistic way via microscopic simulation and active internal boundary moving, using the SUMO-based TrafficFluid-Sim simulation tool. To effectuate IBC, a Linear Quadratic Regulator (LQR), which is a feedback control scheme, is employed. In addition, to enhance the performance of the LQR controller, a feedforward term, accounting for external disturbances, i.e. entering flow and on-ramp flows, is also designed, leading to an augmented LQR-FF control scheme. The LQR and LQR-FF controllers are tested and compared in the created realistic environment, demonstrating how IBC may operate in practice to combat traffic congestion on highways. [ABSTRACT FROM AUTHOR]