1,721,021 research outputs found
Traffic-Prediction-Based Optimal Control of Electric and Autonomous Buses
No full textThis letter considers electric and autonomous buses which have to follow a given route, including fixed stops, in extra-urban roads with a given timetable. A charging infrastructure is present in each stop, allowing to charge the bus batteries. An optimal control scheme is proposed in this letter in order to regulate the optimal speed of buses along the route and the stopping/charging times at stops. The proposed control scheme, acting in real time according to a receding-horizon logic, consists of two modules: a traffic prediction model and an optimal control problem solver. The traffic model measures the traffic state in real time, provides the traffic state prediction in the considered road stretch and, in particular, communicates the predicted average speed in each road section to the second module. This latter computes the optimal behavior of buses by optimizing their expected final energy level, by maximizing their compliance with the timetable and by reducing oscillations in the speed profile. Simulation results based on a real case study show the effectiveness of the proposed control scheme
Day-to-day discrete-time traffic assignment model for transport networks affected by disruptive events
No full textIn this paper, a day-to-day discrete-time traffic assignment model is introduced to represent the evolution of users’ choices and their progressive adjustments towards new equilibria in transport networks in which new conditions occur. Specifically, the proposed model considers a proportional switch assignment process, in which every day the users decide whether to maintain the same path chosen the previous day or to switch it, not only on the basis of the congestion level experienced on the chosen routes but also according to the extent of topological similarity between the potential new paths and the one already used. In this paper, the potential of this model to analyse the performance degradation in a transport network affected by disruptive events is shown by reporting two simulation examples
A topology-based bounded rationality day-to-day traffic assignment model
No full textThis paper analyzes the day-to-day adjustment process of users’ behaviors in a transport network which is affected by relevant alterations such as disruptions due to critical events which cause the impossibility to use one or more links. For representing the progressive adjustment of the flows on the network to reach a new equilibrium, a day-to-day discrete-time model is proposed, based on the idea that people are bounded rational in their choices, i.e. they often do not behave according to the optimal solution but they accept solutions they consider satisfying. Users, in their choice process, are influenced by the topological similarity between the route they are currently using and others. This means that they tend to prefer the solutions that are more similar to the one they are already using. In parallel, users exhibit a myopic behavior, i.e., they tend to overestimate the goodness of a route if, when using it, they suddenly experience a significant reduction in travel time compared to what they are used to. In the paper it is shown that such route choice behaviour implies that the steady state of the system corresponds to a Bounded Rational User Equilibrium, i.e., a state that does not diverge from the user equilibrium more than a certain value which increases when the relative importance given to the topological similarity grows. The model also assumes that these biases vanish, at least with respect to those routes that are most frequently used by users, after a sufficient amount of time. Under certain conditions, it is then shown that the steady state can eventually collapse into a User Equilibrium. The effectiveness of the proposed model is assessed via simulation results in which two test networks are analyzed in detail to show the evolution of the users’ behaviour in a transport network after a disruption
Stability analysis of controlled freeway traffic systems with different on-ramp configurations
No full textThis paper considers a freeway stretch controlled via ramp metering and proposes a stability analysis for this system. The dynamics of the system is represented with the Asymmetric Cell Transmission Model, so that a freeway stretch can be seen as a piecewise-affine system switching among different sets of linear difference equations. The stability analysis is firstly referred to the uncontrolled system and, secondly, to the closed-loop system in which a switching proportional feedback control law is applied. In particular, different on-ramp configurations are analysed, including to the two extreme cases of only one on-ramp in a freeway stretch or on-ramps in each cell of the freeway stretch
Stabilizing piecewise linear state feedback controllers for freeway networks
No full textThis paper considers a freeway traffic system regulated via ramp metering. By adopting the Asymmetric Cell Transmission Model, a freeway stretch can be seen as a discrete-time piecewise affine system. A general state-space representation for this system is reported in the paper, for a generic number of cells composing the freeway stretch and a generic number of on-ramps. Piecewise linear full-state feedback controllers are defined for each on-ramp, for which the stabilizing properties are investigated. In particular the regulator gains are determined to guarantee the stability of the controlled system with reference to the error signal. The results reported in the paper suggest that, instead of full-state regulators, local regulators can be employed, relying on the state measurements of a subset of cells that are in the neighborhood of the on-ramp
Network performance evaluation under disruptive events through a progressive traffic assignment model
No full textThe purpose of this paper is to present an assignment model as a basis for evaluating the performance of a traffic network, capable of describing its evolution immediately after the occurrence of a disruptive event. First of all, a User-Equilibrium traffic assignment problem is solved in order to obtain an estimation of the system state before the disruption. Starting from the critical event, a Progressive Assignment procedure is performed in order to obtain reasonable traffic assignments on the network, taking into account the users' tolerance to increases in travel times as well as the inherent inertia of the system. Therefore a metric for the description of the network performance is proposed as well as implementation of the model on a test network
A progressive traffic assignment procedure on networks affected by disruptive events
No full textThe purpose of this paper is to implement a dynamic model as a base for evaluating the resilience of a traffic network, capable of describing its evolution shortly after the occurrence of a disruptive event. First of all, a User-Equilibrium traffic assignment problem is solved in order to obtain an estimation of the system state before the disruption. Starting from the critical event, a Progressive Assignment procedure is performed in order to obtain reasonable traffic assignments on the network, taking into account the users' tolerance to increases in travel times as well as the inherent inertia of the system
Multi-objective optimization of electric automated bus trajectories based on the ε-constraint method
No full textThis paper deals with electric automated buses that have to follow a given route in inter-urban roads including stops, with a given timetable. Some stops are provided with a charging infrastructure allowing to charge the batteries while others are not. In order to control these buses, it is necessary to account for the traffic conditions along the road and to minimize two objectives, respectively related to the minimization of the deviations from the timetable and the minimization of the energy lack, at the end of the bus route, with respect to a desired final energy level. To address this problem and to investigate the conflicting nature of these objectives, two multi-objective methods based on the ε-constraint approach are applied in this paper, allowing to find different sets of efficient solutions for the problem. The results obtained in a real case study show that the two objective are in conflict, and compromise solutions can be found using the methods proposed in this paper
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