Search

In order to correctly reflect the change of the arm current during the pole-to-pole fault in the pseudo-bipolar back-to-back DC grid, a multi-stage analytic model of pole-to-pole fault is established, which is divided into three stages: the pre-blocking stage of the converter after the fault, the pre-tripping stage of the circuit breaker after the converter is blocked, and the stage after the circuit breaker trips. A three-stage circuit model is established accordingly, and the analytical expression or analytical equation of the arm current of each phase after the fault is derived. Simulation results have validated the accuracy of the analytical model.

Distributional Semantic Models (DSMs) established themselves as a standard for the representation of word and sentence meaning. However, DSMs provide quantitative measurement of how strongly two linguistic expressions are related, without being able to automatically classify different semantic relations. Hence the notion of semantic similarity is underspecified in DSMs. We introduce Evalution-MAN in this paper as an effort to address this underspecification problem. Following the EVALution 1.0 dataset for English, we present a dataset for evaluating DSMs on the task of the identification of semantic relations in Mandarin Chinese. Moreover, we test different types of word vectors on the automatic learning of these semantic relations, and we evaluate them both in a unsupervised and in a supervised setting, finding that distributional models tend, in general, to assign higher similarity scores to synonyms and that deep learning classifiers are the best performing ones in the identification of semantic relations.

LiDAR becomes a promising sensor in intelligent transportation for traffic data collection. Unlike the onboard LiDAR sensors which only focus on the surroundings of the vehicle, we set up LiDAR sensors at the infrastructure side to cover a wider detection range. In order to extract real-time movement status of road users, background filtering is the initial step to reduce a large amount of unrelated information. Since the LiDAR sensors are fixed at roadside, the detected background objects at a specific location are unchanged, which is different from dynamic backgrounds detected by onboard LiDAR sensors in a moving vehicle. This paper proposed an innovative real-time Azimuth-Height background filtering method for roadside LiDAR systems by comparing the heights between raw LiDAR data and background objects based on laser channels and azimuth angles. A case study showed more than 98% background data were successfully filtered and target (non-background) data were kept well. The proposed filtering process is performed while parsing original data stream and only target data are stored, thus the speed of processing LiDAR data in real time is increased, and computer memory is saved. The roadside LiDAR sensing systems provide a new approach to extracting pedestrian and vehicle trajectories.

It is imperatively important to spot hidden road hazards which cause a high proportion of traffic incidents. Social media data is featured by its innumerable and up-to-date information, and provides a promising approach to road hazard spotting. However, this research area is not well studied yet. In this paper, we present our view of the important research issues, including challenges of mining spatio-temporal dataset, road hazards reasoning and etc.

The Z-source NPC three-level inverter can realize buck-boost energy conversion without introducing extra dc-dc stage compared with the conventional three-level inverters. However, the problem of low-frequency neutral-point (NP) voltage oscillations is a drawback for its applications. In this paper, a hybrid modulation strategy based on the combination of double signals pulse-width modulation (DSPWM) and SPWM with injected zero-sequence signal is proposed, which can eliminate the low-frequency NP voltage oscillations under different conditions. First, based on the operating principle that average NP current should be zero in a switching period, the optimal solution of the compensation zero-sequence signal is calculated using the mathematic model of averaged NP current. And then, amplitude limitation of zero-sequence signal is set to avoid affecting voltage boosting. The DSPWM is adopted if the value of zero-sequence signal is bigger than the amplitude limitation, otherwise, zero-sequence signal injection method is selected. The proposed hybrid modulation strategy can realize NP voltage oscillations elimination and voltage boosting simultaneously. Finally, the performance of the hybrid modulation strategy are verified by simulation results.

An instantaneous rotation rate (IRR) estimation algorithm based on the chirp rate of the scattering centre in the same Doppler cell is proposed to complete the cross-range scaling of the RID ISAR images.

In this paper, based on symbolic computation, we apply the Pfaffianization procedure of Ohta and Hirota to the variable-coefficient mKP (vcmKP) equation. We first present the N-soliton solutions in terms of Grammian determinant by employing the bilinear formalism . Then by applying the method of Pfaffianization to the vcmKP case, we derive the bilinear form of the Pfaffianized vcmKP equation. Finally by the dependent variable transformation, a new integrable, coupled vcmKP system in nonlinear form is derived. To our knowledge, the procedure of Pfaffianization has not been extended to the non-isospectral and variable-coefficient equations before. We expect that this Pfaffianization technique is applicable to other non-isospectral and variable-coefficient integrable equations which admit determinant solutions.

In this paper, three heuristic solution algorithms, (the Dive-and-Fix method, the Ratio-cluster method, and the Cumulative-departure method) are specially designed to solve the traffic signal control problem formulated as a 0–1 mixed-integer linear programming problem with cell transmission model. These three solution algorithms are based on two fundamental approaches. First, the 0–1 mixed-integer linear program is solved via linear relaxation (LR). Second, the non-integer solutions obtained from the LR are converted into the integer solutions by taking advantage of the underlying physical mechanism embedded in the LR solutions that lead to the optimal signal control. In particular, proportional capacities for different approaches and the cumulative exit flow at each intersection obtained from the LR solutions are utilized to determine green time allocation for each approach. It is demonstrated that the near-optimal solutions obtained with these algorithms are very close to the optimal solutions under both uncongested and congested traffic conditions.

A different objective function (OF) and model of reactive power optimization is proposed in this paper. In the model, the values of compensator are regarded as the controllable variables to be evaluated and the objective is to minimize the voltage deviation. An efficient algorithm for approximation of initial problem is described. The proposed method overcomes the drawbacks of conventional reactive power optimization method. Compared with that obtained using a traditional optimization method, Simulation has been applied to practical IEEE 30-bus system. The test results show that this method is feasible and practical method.

This paper presents development and application of a real-time virtual differential map-matching algorithm. Taking advantage of the slowly drifting property of the GPS errors and the continuity in map errors, the authors first define a differential vector between the vehicle's GPS track points and their corresponding mapped points by historical tracks. This information is then applied to a pre-correction process for examining the on-line vehicle tracks. As the differential vector is only the approximate of the real-time deviation (i.e., virtual differential vector), it is corrected continuously along with the vehicle movement. As a result, the algorithm takes into account both historical information and real-time data of vehicle velocity and direction, as well as the topological structure of the road network map in the map-matching process. The performance of the algorithm is examined through a sample application.

A critical issue encountered in implementing a transit signal priority system is to ensure that communication between transit vehicles and the traffic centre can be established for transmitting priority request and arrival time information needed for executing signal priority control. The available communication channel bandwidth, however, is not guaranteed to meet the demand from a potentially large number of transit vehicles requesting signal priority service. In this paper, we define and analyse this supply-demand problem with simulations of a simple time model. The emphasis is to investigate the logistic issues and identify the critical parameters, so that this simple model might serve as a framework for constructing a more complex realistic model upon which an efficient scheduling protocol could be designed to meet signal priority service demand.

We develop an algorithm for predicting the arrival time of a transit vehicle at a signalised intersection, with specific application for signal priority control. In order to accurately predict the arrival time, real-time GPS bus location information is made available. We propose an algorithm that uses both realtime and historical vehicle location information for predicting the arrival time at the next traffic light. The predictor is consisted of two models: (i) a historical model and (ii) an adaptive model that adaptively adjusts its filter gain based on the real-time data. The estimates generated by these two models are molded in a weighted average. The prediction algorithm adaptively adjusts its weight distribution according to some error variances obtained from the two models

A colored Petri net (CPN) model for traffic signal priority/preemption is described. The model incorporates the priority/preemption request of transit vehicles into traffic signal control. Compared with 'uncolored' Petri nets (PN), CPN provides a broader modeling capability for traffic signal priority control. A simple priority evaluation procedure is proposed to provide different priorities to multiple priority requests. An example for the queue jump phase modeled with CPN is presented.

This paper attempts to enhance the existing linear programming (LP) formulation of the system optimal dynamic traffic assignment SO-DTA problem by treating the priority ratio of a merge junction with a linear programming module equivalent to the non-linear merge component in the cell transmission model. The proposed formulation preserves the proper merge priority rule and can be readily embedded into an LP formulation of the SO-DTA problem for a single destination. It is capable of distinguishing control governed by the roadway geometry and control imposed by the system provider. The other contribution of the paper is that the model proposed also provides an alternative graphical interpretation of the merge rule described in the cell transmission model. I. BACKGROUND

The equity issue has been recognized as one of the main causes for public opposition to ramp metering. This communication note summarizes some findings of our recent study on defining and addressing user inequality in ramp metering. We discuss the definition and measure for user inequality of ramp metering, and present the observations of equity performance of three selected ramp metering algorithms and provide some thoughts on how to balance the efficiency and equity of ramp metering.

Traffic signals may induce unexpected bottlenecks when queues from an intersection spill back and block its adjacent upstream intersection. The information of whether and when queues from the downstream intersection would reach the upstream intersection is of particular significance to signal tuning of closely spaced oversaturated intersections. This paper presents a macroscopic simulation approach to emulate the formation and propagation of backward and forward waves along closely spaced traffic signals and demonstrates its application to the evaluation of point queue based signal timing plans.

Agent is a populous phenomenon in economy system today no matter in industry sectors and in services sectors. Agent has become an efficient method to enlarge business for many enterprises in service sectors, for example Mcdonald's. But how to encourage the agent improving the quality of service as demanded by the firm is an impotent problem. After all the agent keep in touch with customers directly instead of firm, the quality of service offered by the agent affect the impression of the firm among customers. In some extent this is a kind of principle-agent problem. In this study we develop a principle-agent to explain the relationship between the compensation scheme offered by firm and the incentive of agent to improve the quality of service. We find the when the effort can be perceived the agent refers to the fixed compensation. When the effort cannot be perceived, the agent inclines to decrease the level of effort. But when the cooperation happens in more than one period, the agent considers the effect of reputation and refers to take effort to improve the quality of service.

Video surveillance technology has been widely used in intelligent transportation system (ITS) to measure traffic flow parameters and detect accidents. Occlusion of moving objects by stationary or other moving foreground objects always causes tracking errors. This paper presents a novel module for vehicle tracking under the condition of occlusion, which can be conveniently added to the existing video surveillance systems as a complementary part. The appearance information of the object (shape and texture) is combined with the spatial-temporal Markov random field (MRF) based tracking model through a kind of special structuring elements in mathematical morphology (MM) theory. As a result, the sites in MRF are reduced, which saves computational cost greatly, and the assumption on the vehicle shape model in prior is not needed. Experiments on various kinds of image sequences show that the proposed module can effectively track vehicles with severe occlusion.

In this paper, a fault current limiter (FCL) with series compensation is proposed. It is composed of a limiting reactor and a compensation capacitor that is parallel with a by-pass reactor controlled by GTO. The FCL can not only control fault current, but also perform series compensation. The good performance of this device is proved by simulation, it will be a practical protection device for power systems in the future.