On-ramp merging strategy for connected and automated vehicles based on complete information static game

Improper handling of vehicle on-ramp merging may hinder traffic flow and contribute to lower fuel economy,while also increasing the risk of collisions.Cooperative control for connected and automated vehicles(CAVs)has the potential to significantly reduce negative environmental impact while also improve driving safety and traffic efficiency.Therefore,in this paper,we focus on the scenario of CAVs on-ramp merging and propose a centralized control method.Merging sequence(MS)allocation and motion planning are two key issues in this process.To deal with these problems,we first propose an MS allocation method based on a complete information static game whereby the mixed-strategy Nash equilibrium is calculated for an individual vehicle to select its strategy.The on-ramp merging problem is then formulated as a bi-objective(total fuel consumption and total travel time)optimization problem,to which optimal control based on Pontryagin's minimum principle(PMP)is applied to solve the motion planning issue.To determine the proper parameters in the bi-objective optimization problem,a varying-scale grid search method is proposed to explore possible solutions at different scales.In this method,an improved quicksort algorithm is designed to search for the Pareto front,and the(approximately)unbiased Pareto solution for the bi-objective optimization problem is finally determined as the optimal solution.The proposed on-ramp merging strategy is validated via numerical simulation,and comparison with other strategies demonstrates its effectiveness in terms of fuel economy and traffic efficiency.

LINEAR REGRESSION OF INTERVAL-VALUED DATA BASED ON COMPLETE INFORMATION IN HYPERCUBES

Recent years have witnessed an increasing interest in interval-valued data analysis. As one of the core topics, linear regression attracts particular attention. It attempts to model the relationship between one or more explanatory variables and a response variable by fitting a linear equation to the interval-valued observations. Despite of the well-known methods such as CM, CRM and CCRM proposed in the literature, further study is still needed to build a regression model that can capture the complete information in interval-valued observations. To this end, in this paper, we propose the novel Complete Information Method （CIM） for linear regression modeling. By dividing hypercubes into informative grid data, CIM defines the inner product of interval-valued variables, and transforms the regression modeling into the computation of some inner products. Experiments on both the synthetic and real-world data sets demonstrate the merits of CIM in modeling interval-valued data, and avoiding the mathematical incoherence introduced by CM and CRM.

A Model-calibration Approach to Using Complete Auxiliary Information from Stratified Sampling Survey Data

In stratified survey sampling, sometimes we have complete auxiliary information. One of the fundamental questions is how to effectively use the complete auxiliary information at the estimation stage. In this paper, we extend the model-calibration method to obtain estimators of the finite population mean by using complete auxiliary information from stratified sampling survey data. We show that the resulting estimators effectively use auxiliary information at the estimation stage and possess a number of attractive features such as asymptotically design-unbiased irrespective of the working model and approximately model-unbiased under the model. When a linear working-model is used, the resulting estimators reduce to the usual calibration estimator（or GREG）.

Shift, the Law of the Invention of Zero

After posing the axiom of linear algebra, the author develops how this allows the calculation of arbitrary base powers, which provides an instantaneous calculation of powers in a particular base such as base ten;first of all by developing the any base calculation of these powers, then by calculating triangles following the example of the “arithmetical” triangle of Pascal and showing how the formula of the binomial of Newton is driving the construction. The author also develops the consequences of the axiom of linear algebra for the decimal writing of numbers and the result that this provides for the calculation of infinite sums of the inverse of integers to successive powers. Then the implications of these new forms of calculation on calculator technologies, with in particular the storage of triangles which calculate powers in any base and the use of a multiplication table in a very large canonical base are discussed.

The tragedy of the commons and energy price depression of China

This article indicates by example about power price of Henan province that the energy resources of Henan province are ＂the commons＂. According to analysis of the game of ＂the tragedy of the commons＂, this article demonstrates that, whether under complete information or not, energy commons are abused. Based upon the situation, the author gives out the strategy to solve ＂the tragedy of the commons＂ of China energy sources.

Detecting high-dimensional multipartite entanglement via some classes of measurements

Mutually unbiased bases, mutually unbiased measurements and general symmetric informationally complete measure- ments are three related concepts in quantum information theory. We investigate multipartite systems using these notions and present some criteria detecting entanglement of arbitrary high dimensional multi-qudit systems and multipartite sys- tems of subsystems with different dimensions. It is proved that these criteria can detect the k-nonseparability （k is even） of multipartite qudit systems and arbitrary high dimensional multipartite systems of m subsystems with different dimensions. We show that they are more efficient and wider of application range than the previous ones. They provide experimental implementation in detecting entanglement without full quantum state tomography.

Separability criteria via some classes of measurements

Mutually unbiased bases (MUBs) and symmetric informationally complete (SIC) positive operator-valued measurements (POVMs) are two related topics in quantum information theory. They are generalized to mutually unbiased measurements (MUMs) and general symmetric informationally complete (GSIC) measurements, respectively, that are both not necessarily rank 1. We study the quantum separability problem by using these measurements and present separability criteria for bipartite systems with arbitrary dimensions and multipartite systems of multi-level subsystems. These criteria are proved to be more effective than previous criteria especially when the dimensions of the subsystems are different. Furthermore, full quantum state tomography is not needed when these criteria are implemented in experiment.

Average coherence with respect to complementary measurements

We investigate the average coherence with respect to a complete set of complementary measurements.By using a Wigner-Yanase skew information-based coherence measure introduced in Luo and Sun(2017 Phys.Rev.A 96,022130),we evaluate the average coherence of a state with respect to any complete set of mutually unbiased measurements and general symmetric informationally complete measurements,respectively.We also establish analytically the relations among these average coherences.