This paper presents a solution to an on-ramp merging trajectory planning problem within a multiple target vehicles environment by employing model predictive control principles. The shrinking horizon MPC (SHMPC) scheme is used to guarantee that the optimal trajectories are selected among the available gaps into which the ego vehicle can merge. For each trajectory, a time-varying terminal set is used to ensure recursive feasibility and to fulfill the safety and obstacle avoidance constraints. To enhance computational efficiency, a procedure is proposed for defining the terminal set to be as large as possible, derived from the offline-calculated maximum controlled invariant set. We present a simple decision mechanism, accounting for safety, comfort, and efficiency. Then, we demonstrate the effectiveness of the proposed solution by applying it to two different scenarios.

This paper focuses on the characterization of the asymptotic behavior of the critical characteristic roots for a class of delay-differential dynamical systems of neutral type whose coefficients smoothly depend on certain parameters. Such systems can be described by coupled delay-differential and delay-difference equations, and model time heterogeneity in propagation and transport phenomena. The asymptotic behavior of the characteristic roots is addressed by expressing the solutions as a convergent Puiseux series, which facilitates handling multiple solutions. Particular attention is paid to the way the parameters affect the stability of the delay-difference operator. Illustrative examples complete the presentation and show the effectiveness of the proposed method.

In this study, we investigate the stabilization of general linear second-order non-minimum phase time-delay systems using PI controllers. Our primary objective is to determine optimal control gains, if any, such that the spectral abscissa of the system is shifted as far left as possible, ensuring enhanced stability. To achieve this, we employ a comprehensive geometrical analysis, providing a methodology to tune the control gains that yield the desired decay rate. The presented approach not only contributes theoretical insights but also facilitates practical implementation. The effectiveness of the proposed methodology is demonstrated through numerical examples.

Eco-routing is a vehicle navigation method that aims to minimize fuel or energy consumption for a given trip. It is based on a hypothesis that we can trade extra travel time for lower consumption. While the hypothesis was experimentally verified the design of a method that would fully exploit its potential proves challenging. Current solutions hinge on assumption that energy spent on any given road does not change in time. We challenge validity of this assumption by studying performance of such methods in detailed second-by-second simulation that pronounces the time-dependencies. This allows us to quantify the real savings attainable with current eco-routing.

We present a large-scale dataset for testing, benchmarking, and offline learning of map-matching algorithms. For the first time, a large enough dataset is available to prove or disprove map-matching hypotheses on a world-wide scale. There are several hundred map-matching algorithms published in literature, each tested only on a limited scale due to difficulties in collecting truly large scale data. Our contribution aims to provide a convenient gold standard to compare various map-matching algorithms between each other. Moreover, as many state-of-the-art map-matching algorithms are based on techniques that require offline learning, our dataset can be readily used as the training set. Because of the global coverage of our dataset, learning does not have to be be biased to the part of the world where the algorithm was tested.

The present work deals with the reference tracking problem for processes with linear dynamics and multi-sensor information which is subjected to delays or communication packets missing. It is shown that fault tolerance can be achieved through the separation between the invariant sets characterizing the closed-loop system with the communication channels with or without defect. For this purpose, a reference governor scheme is designed using a receding horizon technique in order to provide fault detection and isolation (FDI)-compliant reference signals to practically guarantee the sufficient detection conditions in real time.

The presence of a communication network in a control loop induces many imperfections such as varying transmission delays, varying sampling/transmission intervals and packet loss, which can degrade the control performance significantly and can even lead to instability. Various techniques have been proposed in the literature for stability analysis and controller design for these so-called networked control systems (NCSs). The goal of this paper is to survey a particular class of techniques using discrete-time models that are based on polytopic overapproximations of the uncertain NCS model and lead to stability conditions in terms of linear matrix inequalities (LMIs). We discuss the advantages and disadvantages of the existing techniques in both qualitative and quantitative manners. In particular, we apply all methods to a benchmark example providing a numerical comparison of the methods with respect to conservatism as well as numerical complexity.

This paper addresses a new control strategy for synchronizing two or more distributed and interconnected dynamic systems having communication time delays. The proposed strategy that uses the Smith predictor principle and delay information not only achieves synchronization but also preserves the natural local dynamics of each subsystem without being affected by the feedback nature of control. The proposed synchronization scheme is generalized to cases that deal with an arbitrary number of heterogeneous interconnected systems through dynamic scaling of input under a ring-type network configuration. In addition, possibility of applying the proposed scheme to nonlinear systems is discussed. Simulation and experimental tests are conducted to validate theoretical results.

We propose a new RTT based congestion control scheme. The key idea is to use some results developed in delay system theory to perform exact stability bounds. If the measured RTT belongs to the defined bounds, the network is stable (asymptotic stability of some continuous model associated to the network), which can be translated in no congestion in the network. This "exact" estimator can be used to estimate the path status and to adjust the sending rate.