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This deliverable is created in the starting phase for INFRAMIX and presents the INFRAMIX co-simulation environment to be used validating the proposed use cases before entering the field test. The main goal is to simulate realistic traffic... more
This deliverable is created in the starting phase for INFRAMIX and presents the INFRAMIX co-simulation environment to be used validating the proposed use cases before entering the field test. The main goal is to simulate realistic traffic on the test sites, the detailed behaviour of either automated vehicles or vehicles with human drivers, and the communication among vehicles, infrastructure, and traffic management services. Furthermore, the presented simulation framework is prepared to work in hybrid testing scenarios, where real vehicles and real road situations interact with the co-simulation and vice versa.
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Max pressure (MP) is a distributed strategy for adaptive urban traffic signal control. Real-time queue estimation for road links is indispensable for MP-based traffic control. All works conducted so far on MP traffic signal control... more
Max pressure (MP) is a distributed strategy for adaptive urban traffic signal control. Real-time queue estimation for road links is indispensable for MP-based traffic control. All works conducted so far on MP traffic signal control assumed that accurate information of vehicle queues was directly available in real time. This paper studies joint queue estimation and MP control for signalized urban networks with connected vehicles. For the sake of practical significance, the cases of link queue estimation and lane-wise queue estimation were both considered as input to the MP traffic signal control. A congested 3*3 network was emulated using AIMSUN to evaluate the performance of the developed queue estimation and MP traffic signal control algorithms, with study results reported.
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Max pressure (MP) is a distributed strategy for adaptive urban traffic signal control. Real-time queue estimation for road links is indispensable for MP-based traffic control. All works conducted so far on MP traffic signal control... more
Max pressure (MP) is a distributed strategy for adaptive urban traffic signal control. Real-time queue estimation for road links is indispensable for MP-based traffic control. All works conducted so far on MP traffic signal control assumed that accurate information of vehicle queues was directly available in real time. This paper studies joint queue estimation and MP control for signalized urban networks with connected vehicles. For the sake of practical significance, the cases of link queue estimation and lane-wise queue estimation were both considered as input to the MP traffic signal control. A congested 3*3 network was emulated using AIMSUN to evaluate the performance of the developed queue estimation and MP traffic signal control algorithms, with study results reported.
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During the last decade, there has been a significant effort to develop a variety of Vehicle Automation and Communication Systems (VACS). These are expected to revolutionise the features and capabilities of individual vehicles within the... more
During the last decade, there has been a significant effort to develop a variety of Vehicle Automation and Communication Systems (VACS). These are expected to revolutionise the features and capabilities of individual vehicles within the next decades. The introduction of VACS brings along the (sometimes ignored) necessity and continuously growing opportunities for accordingly adapted or utterly new Traffic Management (TM) actions and strategies. This calls for a new era of freeway TM research and practice, which is indispensable in order to accompany, complement and exploit the evolving VACS deployment. Specifically, the development of new traffic flow modelling and control approaches should become a priority in the years to come.
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This paper addresses the problem of collaborative multi-agent autonomous driving of connected and automated vehicles (CAVs) in lane-free highway scenarios. We eliminate the lane-changing task, i.e., CAVs may be located in any arbitrary... more
This paper addresses the problem of collaborative multi-agent autonomous driving of connected and automated vehicles (CAVs) in lane-free highway scenarios. We eliminate the lane-changing task, i.e., CAVs may be located in any arbitrary lateral position within the road boundaries, hence allowing for better utilization of the available road capacity. As a consequence, vehicles operate in a much more complex environment, and the need for the individual CAVs to select actions that are efficient for the group as a whole is highly desired. We formulate this environment as a multiagent collaboration problem represented via a coordination graph, thus decomposing the problem with local utility functions, based on the interactions between vehicles. We produce a tractable and scalable solution by estimating the joint action of all vehicles via the anytime max-plus algorithm, with local utility functions provided by potential fields, designed to promote collision avoidance. Specifically, the fi...
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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... more
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, of road departures and of negative speeds. Connectivity implies that connected vehicles are able to exchange with each other (V2V) or the infrastructure (V2I), real-time information about their last generated path. For the numerical solution of the optimal control problem, an efficient feasible direction algorithm is used. To ensure high-quality local minima, a simplified Dynamic Programming algorithm is also conceived to deliver the initial guess trajectory for the feasible direction algorithm. Thanks to 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. 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 Aimsun 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 compared to the corresponding non-connected controlled vehicles, due to the improved real-time information and short-term prediction.
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This paper investigates the effectiveness of a Model Predictive Control (MPC) scheme for motorway traffic involving vehicles equipped with Vehicle Automation and Communication Systems (VACS). A stretch of the motorway A20, which connects... more
This paper investigates the effectiveness of a Model Predictive Control (MPC) scheme for motorway traffic involving vehicles equipped with Vehicle Automation and Communication Systems (VACS). A stretch of the motorway A20, which connects Rotterdam to Gouda in the Netherlands, is modeled in a microscopic traffic simulation environment. In order to ensure the reliability of the microscopic simulation outcome, the simulation parameters are tuned with the purpose of replicating realistic traffic conditions. The MPC framework is then applied to the calibrated microscopic simulation model aiming at the mitigation of traffic congestion in the case study motorway. The synergistic control measures for coordinated and integrated traffic control are ramp metering, with the use of conventional traffic lights, vehicle speed control, and lane changing control actions that are enabled with the aid of VACS.
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The main purpose of this work is to generate optimal trajectories for vehicles crossing a signalized junction, with traffic signals operated in either fixed-time or real-time (adaptive) mode. In the latter case, the next switching time is... more
The main purpose of this work is to generate optimal trajectories for vehicles crossing a signalized junction, with traffic signals operated in either fixed-time or real-time (adaptive) mode. In the latter case, the next switching time is decided in real time based on the prevailing traffic conditions and is therefore uncertain in advance. The GLOSA (Green Light Optimal Speed Advisory) problem is addressed by using traffic lights information and calculating a trajectory and velocity profile for the vehicle based on the vehicle’s initial state (position and speed) and a fixed final destination state. At first, an appropriate optimal control problem is formulated and solved analytically via Pontryagin’s minimum principle (PMP) for the case of known switching times. Subsequently, for the case of real-time signals, availability of a time-window of possible signal switching times, along with the corresponding probability distribution, is assumed, and the problem is cast in the format of ...
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The development and deployment of simple, yet efficient, coordinated and integrated control tools for motorway traffic control remains a challenge. A generic integrated feedback-based motorway traffic flow control concept has been... more
The development and deployment of simple, yet efficient, coordinated and integrated control tools for motorway traffic control remains a challenge. A generic integrated feedback-based motorway traffic flow control concept has been proposed recently by the authors of this paper. It is based on the combination and suitable extension of control algorithms and tools proposed or deployed in other studies, such as ramp metering or VSL (Variable Speed Limit)-enabled cascade-feedback mainstream traffic flow control, and allows for consideration of multiple bottlenecks. The new controller enables coordination of ramp metering actions at a series of on-ramps, as well as integration with VSL control actions towards a common control goal, which is bottleneck throughput maximization. While doing this, the approach considers a pre-specified (desired) balancing of the incurred delays upstream of the employed actuators, via a suitably designed knapsack problem. Despite the multitude of the offered ...
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This paper is concerned with the impacts of smart lane changes of connected and automated vehicles (CAVs) on their own travel performance as well as the entire traffic flow. Based on MOBIL and reinforcement learning, two ego-efficient... more
This paper is concerned with the impacts of smart lane changes of connected and automated vehicles (CAVs) on their own travel performance as well as the entire traffic flow. Based on MOBIL and reinforcement learning, two ego-efficient lane-changing strategies were developed in this work to enable lane-changing decisions for CAV s to improve their travel efficiency. The MOBIL approach intends to establish such a lane-changing strategy by optimizing MOBIL's two parameters, while the reinforcement learning approach tries to develop such a strategy from scratch using Q-learning with sufficient traffic environmental information. The lane-changing strategies were developed and compared on the basis of intensive microscopic traffic simulation. In addition, the information impact on the performance of the reinforcement learning approach was examined to determine the essential amount of environmental information required.
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This paper develops a path planning algorithm for Connected and Automated Vehicles (CAVs) driving on a lane-free highway, according to a recently proposed novel paradigm for vehicular traffic in the era of CAVs. The approach considers a... more
This paper develops a path planning algorithm for Connected and Automated Vehicles (CAVs) driving on a lane-free highway, according to a recently proposed novel paradigm for vehicular traffic in the era of CAVs. The approach considers a simple model of vehicle kinematics, along with appropriate constraints for control variables and road boundaries. Appropriate, partly competitive sub-objectives are designed to enable efficient vehicle advancement, while avoiding collisions with other vehicles and infeasible vehicle maneuvers. Based on these elements, a nonlinear Optimal Control Problem (OCP) is formulated for each ego vehicle, and a Feasible Direction Algorithm (FDA) is employed for its computationally efficient numerical solution. The OCP is solved repeatedly for short time horizons within a Model Predictive Control (MPC) framework, while the vehicle advances. It is demonstrated via traffic simulation, involving many such vehicles, on a lane-free ring-road that the proposed approach delivers promising results and can be considered as a candidate for use in further developments related to lane-free CAV traffic.
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This paper proposes a freeway traffic controller with the objective of minimizing, at the same time, congestion phenomena and traffic emissions. A multi-class framework is considered in the paper, i.e two classes of vehicles (cars and... more
This paper proposes a freeway traffic controller with the objective of minimizing, at the same time, congestion phenomena and traffic emissions. A multi-class framework is considered in the paper, i.e two classes of vehicles (cars and trucks) are explicitly modelled and specific control actions for each vehicle class are computed. The controller is based on the formulation and solution of a constrained discrete-time nonlinear optimal control problem for which a specific solution algorithm, the feasible direction algorithm, is used. The effectiveness of the proposed approach is shown and discussed in the paper by means of some simulation results.
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In a recent series of articles ([1-5]) with largely indentical confents an preformance of the well-[6,7] and of some extended version such as UP-ALINEA and ALINEA/Q expressed claim are based on result produced by B S Kermer with a soff.... more
In a recent series of articles ([1-5]) with largely indentical confents an preformance of the well-[6,7] and of some extended version such as UP-ALINEA and ALINEA/Q expressed claim are based on result produced by B S Kermer with a soff. made microscopic answer to specially [5], showing that alt raised claims are utterly flawed. ALINEA's efficiency (compared to other known strategies) is due to its feedback character [5] are based on an insufficient of the feedback character of the ALINEA algorith which led to an inappropriate the maintream measurement could not be monitored: this renther blind to the traffic condition undre control and negates the very notion of feedback. The paper also includes some new results related to the ALINEA application based on measurements (UP-ALINEA).
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Cooperative intelligent transportation systems (C-ITS) support the exchange of information between vehicles and infrastructure (V2I or I2V). This paper presents an in-vehicle C-ITS application to improve traffic efficiency around a... more
Cooperative intelligent transportation systems (C-ITS) support the exchange of information between vehicles and infrastructure (V2I or I2V). This paper presents an in-vehicle C-ITS application to improve traffic efficiency around a merging section. This application balances the distribution of traffic over the available lanes of a freeway, by issuing targeted lane-changing advice to a selection of vehicles. We add to existing research by embedding multiple vehicle classes in the lane-changing advisory framework. We use a multi-class multi-lane macroscopic traffic flow model to design a feedback-feedforward control law that is based on a linear quadratic regulator (LQR). The performance of the proposed system is evaluated using a microscopic traffic simulator. The results indicate that the lane-changing advisory system is able to suppress Shockwaves in traffic flow and can significantly alleviate congestion. Besides bringing substantial travel time benefits around merging sections of...
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In lane-free traffic, recently proposed for connected automated vehicles (CAV), incremental changes of the road width lead to corresponding incremental changes of the traffic flow capacity. This property enables the controlled shifting of... more
In lane-free traffic, recently proposed for connected automated vehicles (CAV), incremental changes of the road width lead to corresponding incremental changes of the traffic flow capacity. This property enables the controlled shifting of the internal road boundary separating the two opposite traffic directions, so as to optimize the road infrastructure utilization. Internal boundary control aims at flexible sharing of the total road width and capacity among the two traffic directions of a road in real-time-, in response to the prevailing traffic conditions. A model-free adaptive control scheme is applied to efficiently address this problem. Simulation investigations, involving a realistic highway stretch and challenging demand scenario, demonstrate that the efficiency of the proposed control scheme.
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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... more
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.
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Lane changes are a vital part of vehicle motions on roads, affecting surrounding vehicles locally and traffic flow collectively. In the context of connected and automated vehicles (CAVs), this paper is concerned with the impacts of smart... more
Lane changes are a vital part of vehicle motions on roads, affecting surrounding vehicles locally and traffic flow collectively. In the context of connected and automated vehicles (CAVs), this paper is concerned with the impacts of smart lane changes of CAVs on their own travel performance as well as on the entire traffic flow with the increase of the market penetration rate (MPR). On the basis of intensive microscopic traffic simulation and reinforcement learning technique, an ego-efficient lane-changing strategy was first developed in this work to enable foresighted lane changing decisions for CAVs to improve their travel efficiency. The overall impacts of such smart lane changes on traffic flow of both CAVs and human-driven vehicles were then examined on the same simulation platform, which reflects a real freeway infrastructure with real demands. It was found that smart lane changes were beneficial for both CAVs and the entire traffic flow, if MPR was not more than 60%.
Abstract Modern traffic control and management systems in urban networks require real-time estimation of the traffic states. In this paper, a novel approach for modeling traffic flow in urban networks that is especially suitable for state... more
Abstract Modern traffic control and management systems in urban networks require real-time estimation of the traffic states. In this paper, a novel approach for modeling traffic flow in urban networks that is especially suitable for state estimation is proposed. The complexity of the urban traffic model is reduced by assuming availability of connected vehicle data. We first investigate the observability issue in urban traffic networks using a graphical approach. Then, the proposed model for the evolution of the traffic flow in urban traffic networks is developed and used in two layers, i.e., link layer and network layer, to estimate, in high-resolution (second-by-second), the traffic states in the whole network. Traffic states in the link layer include queue tail location and the number of vehicles in the queue, while in the network layer, estimation of the total number of vehicles per link and turning rates at the intersections is carried out. In a first step, it is shown that the estimation approach only requires the detectors at the borders of the network. We further demonstrate that in the proposed scheme, one may reduce or drop the need for spot detectors for the price of reduced, but still reasonable estimation accuracy. The validation of the approach has been undertaken by comparing the produced estimates with realistic micro-simulation results as ground truth, and the achieved simulation results are promising.
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The wide deployment of vehicle automation and communication systems (VACS) in the next decade is expected to influence traffic performance on freeways. Apart from safety and comfort, one of the goals is the alleviation of traffic... more
The wide deployment of vehicle automation and communication systems (VACS) in the next decade is expected to influence traffic performance on freeways. Apart from safety and comfort, one of the goals is the alleviation of traffic congestion which is a major and challenging problem for modern societies. The paper investigates the combined use of two feedback control strategies utilizing VACS at different penetration rates, aiming to maximize throughput at bottleneck locations. The first control strategy employs mainstream traffic flow control using appropriate variable speed limits as an actuator. The second control strategy delivers appropriate lane-changing actions to selected connected vehicles using a feedback-feedforward control law. Investigations of the proposed integrated scheme have been conducted using a microscopic simulation model for a hypothetical freeway featuring a lane-drop bottleneck. The results demonstrate significant improvements even for low penetration rates of...
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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... more
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.
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... Rodrigo C. Carlson, Dynamic Systems and Simulation Laboratory, Technical University of Crete, Chania 73100, Greece, and The Capes Foundation ... 6. Gomes, G. and Horowitz, R., "Optimal freeway ramp metering using... more
... Rodrigo C. Carlson, Dynamic Systems and Simulation Laboratory, Technical University of Crete, Chania 73100, Greece, and The Capes Foundation ... 6. Gomes, G. and Horowitz, R., "Optimal freeway ramp metering using asymmetric cell transmission model," Transportation Res. ...
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ABSTRACT