A Survey on Novel Estimation Approach of Motion Controllers for Self-Driving Cars

The motion planning framework is one of the challenging tasks in autonomous driving cars. During motion planning, predicting of trajectory is computed by Gaussian propagation. Recently, the localization uncertainty control will be estimating by Gaussian framework. This estimation suffers from real time constraint distribution for (Global Positioning System) GPS error. In this research article compared novel motion planning methods and concluding the suitable estimating algorithm depends on the two different real time traffic conditions. One is the realistic unusual traffic and complex target is another one. The real time platform is used to measure the several estimation methods for motion planning. Our research article is that comparing novel estimation methods in two different real time environments and an identifying better estimation method for that. Our suggesting idea is that the autonomous vehicle uncertainty control is estimating by modified version of action based coarse trajectory planning. Our suggesting framework permits the planner to avoid complex and unusual traffic (uncertainty condition) efficiently. Our proposed case studies offer to choose effectiveness framework for complex mode of surrounding environment.

Impact of cyber dependencies in critical infrastructures: The reliability of grid splitting in power systems

The growing presence of cyber interdependencies in critical infrastructures can be exemplified by grid splitting, which is an application in power system stability and control dependent on communication services. It involves the controlled separation of a power system into islands in reaction to an imminent instability. Communication is necessary for gathering system-wide synchronized measurements for state estimation as well as for the dispatch of line switch-opening signals. However, grid splitting may become ineffective due to a degradation in communication, which is accrued by the use of non-dedicated, open communication networks. To address this issue, this article aims to quantify the reliability of grid splitting under degraded communication conditions. A simulation framework is developed that allows the integration of a transient electrical model and a stochastic communication delay model that captures the effects of congestion and traffic uncertainty. The application to the IEEE 39-Bus Test System shows that the reliability of grid splitting is reduced under the influence of degraded communication leading to increased time delays. Furthermore, the results identify a critical transition range in the grid splitting reliability for a very narrow range of external interfering traffic and network data rate. Finally, the interdependency of the electric and the communication network is quantified by the expected efficiency of the communication network subject to degraded communication following the grid splitting action. The decrease in the expected communication efficiency under degraded communication is driven by increased congestion levels and by failures of electrical and co-located communication nodes and is related to the critical transition range for reliability. The developed methodology allows identifying the communication requirements for a reliable grid splitting execution under traffic uncertainty and congestion.

Effect of Traffic Uncertainities on the Design of Mixed Line Rate (MLR) Optical Networks

In the existing studies on Mixed Line Rate (MLR) optical networks, the network design methodology is based on the assumption of deterministic traffic, and hence, the effect of traffic uncertainty on the design of an MLR network remains an open problem of research. In this study, we upgrade our previously proposed cost-efficient mixed integer linear program (MILP) formulation for an MLR network, which considered a specific mean traffic for every network source-destination pair. Our upgraded model employs an optimization technique to account for the traffic uncertainties that an actual MLR optical network may encounter. Our simulation results show that (i) if the MLR network is cost-optimized under the assumption that approximately 10-20% of the demands are at their maximum (or peak) value then, the network demonstrates robustness to traffic peaks in approximately all the other demands, and (ii) the saturation of network cost for a number of source-destination pairs is network topology dependent.

The Role of Capacity and Traffic Uncertainty in Hinterland Connections

Ports are crucial links in supply chains, creating wealth for adjacent regions. Concerning port competitiveness, it is indicated in literature that good hinterland connections are crucial. Therefore, this chapter offers a framework to make decisions about hinterland connections. To do this, analysis of scientific studies and consulting reports was conducted in combination with discussions with experts. Last, the structure of analysis is applied upon the Port of Zeebruges, which features a strong imbalance between its strong maritime potential, and the relatively weak hinterland connections. The analysis results in strategies of optimizing the strategic decision making. From the real option theory, it is clear that a phased strategy is most suitable. The integrated analysis provides a framework to make investment decisions about port investments in general and hinterland connections in particular, and a pathway solution to a concrete case. Therefore, the study is relevant for policy makers and scientific researchers.

Optimal coordination of variable speed limit to eliminate freeway wide moving jams

Variable speed limit (VSL) is well-known for the ability to eliminate freeway wide moving jam (WMJ). Different VSL maneuvers have been proposed and proved to be useful theoretically or empirically. However, the coordination of VSL still needs to be analyzed in order to cater for different traffic conditions encountered on the roadway. In this paper, we execute a study on freeway VSL method based on the three-phase traffic theory and Cellular Automata (CA) based simulations. Results indicate that VSL is a promising method in solving freeway WMJs, but in some cases, it induces new congestions due to improper configurations and the stochastic feature of traffic flow. Therefore, in this paper, we propose an optimal coordination model of VSL including five main principles. The purpose of our model lies on two aspects, to ensure the elimination of WMJ and to avoid the emergence of new traffic jams. By analyzing the traffic dynamics, we first present several theoretical principles of VSL configuration with respect to the WMJ elimination. Second, we study the relation between VSL effectiveness and the traffic uncertainty through CA model-based simulations and some empirical principles are raised.