船舶轨迹异常检测方法研究进展

近年来,异常检测技术在分析和利用船舶轨迹数据中扮演着越来越重要的角色,已经成为航海领域的一个热点研究方向。船舶轨迹的异常检测旨在利用相关的异常检测算法,研究船舶个体或群体的行为特征,发现隐藏在其中的船舶异常行为模式或船位。主要从船舶位置和行为方面分析了船舶异常行为的概念和分类,综述了船舶轨迹异常检测的方法,评述了各方法在船舶轨迹异常检测中应用的优点和不足,讨论了船舶轨迹异常检测存在的问题和面临的挑战。     

Essential tools for food safety surveillance in catering services: On-site inspections and control of high risk cross-contamination surfaces

The aim of this study was to assess the routine food safety procedures carried out in catering services so as to provide a useful monitoring program for managers based on the relevant deviations detected in the observational survey and activities carried out in 15 catering services located in Navarra (region of northern Spain). The main hygiene standards, food handler practices and compliance with the HACCP system were evaluated by means of visual inspections (checklist), monitoring of critical control points (food storage and food processing temperatures, total polar compounds) and microbiological analysis of food-contact and hand-contact surfaces. While general high scores were obtained in the observational survey (73.3% above 36 points), none of the evaluated services had obtained the maximum rate of 48 points. The mayor deficiencies were related to the presence of dirty uniforms, improper hand washing or use of gloves, incorrect disinfection of vegetables and the missing records of stated critical points (temperatures and polar compounds in oil). The performed monitoring activities confirmed the safety of frying oil in all the kitchens, despite the fact that only 33% of them applied scientific methods to measure polar compounds. By contrast, holding temperatures were unsatisfactory in 77% of cold dishes and in 19% of hot meals. Despite the fact that 77% of food contact surfaces were considered acceptable (<4 CFU/cm²), high levels of total mesophilic microorganisms and Enterobacteriaceae were detected in hand-contact surfaces such as aprons and handles. The periodic visual supervision focusing on hygienic practices and the microbiological surveillance of surfaces of high risk for cross-contamination should provide valuable information for improving the knowledge, attitudes and practices of food handlers regarding food safety.     

Optimal allocation for electric vehicle charging stations using Trip Success Ratio

This paper proposes a new model for optimally allocating Plug–in Electric Vehicle (PEV) Charging Stations (CSs) in the network. The model considers Trip Success Ratio (TSR) in order to enhance CS accessibility for PEV drivers. Diversity of usage and different driving habits are considered in the presented model, as well as different trip types (In-city, Highway). The allocation model has two stages: modeling TSR to estimate Charging Station Service Range (CSSR), and the CS allocation stage. In the first stage, the service range of charging stations has been estimated using TSR with consideration of the uncertainty of trip distances (In-city, Highway) and the uncertainty in the Remaining Electric Range (RER) of PEVs. The estimated CSSR is utilized in the CS allocation stage in order to optimize the CS location set that covers the network with a certain guaranteed TSR level. The allocation problem has been formulated as the Maximum Covering Location Problem (MCLP) in order to make the optimal decision for allocating CSs in the network.     

Exact formulations and algorithm for the train timetabling problem with dynamic demand

In this paper we study the design and optimization of train timetabling adapted to a dynamic demand environment. This problem arises in rapid train services which are common in most important cities. We present three formulations for the problem, with the aim of minimizing passenger average waiting time. The most intuitive model would consider binary variables representing train departure times but it yields to non-linear objective function. Instead, we introduce flow variables, which allow a linear representation of the objective function. We provide incremental improvements on these formulations, which allows us to evaluate and compare the benefits and disadvantages of each modification. We present a branch-and-cut algorithm applicable to all formulations. Through extensive computational experiments on several instances derived from real data provided by the Madrid Metropolitan Railway, we show the advantages of designing a timetable adapted to the demand pattern, as opposed to a regular timetable. We also perform an extensive computational comparison of all linear formulations in terms of size, solution quality and running time.     

Active–reactive power approaches for optimal placement of charge stations in power systems

Electric Vehicles (EVs) have been suggested as alternatives to conventional vehicles for reducing petrol consumption and carbon dioxide (CO₂) emissions. When a large number of EVs connect to the grid, they can cause a large amount of power loss. Where to install multiple charge stations in the grid, so as to mitigate losses caused by EVs when providing energy to those EVs, is becoming vitally important. In this paper, a distribution test-network model is described. A new analytical method is proposed, using the stations’ cooperation in terms of optimal active and reactive power dispatch as well as power flow analysis for locating the optimal placement of charge stations, so as to reduce power losses. This method is compared with the previously developed current density method for single charge stations using system simulation results. It was demonstrated that the methods proposed in this paper are more accurate than the current density method, and that 17% of the average active power loss can be saved for three different types of load profile. In addition, 27% of the average active power loss was saved by installing two charge stations rather than no charge stations in the test-line. It is shown that this could represent a 2.6% annual yield above inflation for investing in installing and running such charge stations.     

Development and application of an integrated traffic simulation and multi-driving simulators

Professional virtual reality experiment tools, including driving simulators and traffic simulators, have their strengths and weaknesses. The integration of the two simulators will enhance the ability of both traffic modeling and driving simulation and present a new area of applications. This paper develops, implements, and validates an experimental platform that integrated a traffic simulator with multiple driving simulators (TSMDS). As a connected multi-user framework that allows multiple drivers who are simultaneously handling many driving simulators, it not only allows driver behavior experiments to be more accurate, controlled, and versatile but also simulates special driving behavior or multi-vehicle interactions under more realistic traffic flow environments. To validate the performance of TSMDS, 27 drivers were recruited to attend the lane changing experiments at a recurring on-ramp bottleneck and left-turn experiments at a two-phase signalized intersection in Shanghai. Both experiments required several drivers to drive the TSMDS and fulfill several complicated lane changing/crossing behaviors through their interaction. The results show that both the participants’ response and lane changing/crossing data that were obtained from the experiment are consistent with the field observation, which confirms the validity of the integrated platform.     

Integrated planning and scheduling under production uncertainties: Bi-level model formulation and hybrid solution method

We propose a novel method for integrating planning and scheduling problems under production uncertainties. The integrated problem is formulated into a bi-level program. The planning problem is solved in the upper level, while the scheduling problems in the planning periods are solved under uncertainties in the lower level. The planning and scheduling problems are linked via service level constraints. To solve the integrated problem, a hybrid method is developed, which iterates between a mixed-integer linear programming solver for the planning problem and an agent-based reactive scheduling method. If the service level constraints are not met, a cutting plane constraint is generated by the agent-based scheduling method and appended to the planning problem which is solved to determine new production quantities. The hybrid method returns an optimality gap for validating the solution quality. The proposed method is demonstrated by two complicated problems which are solved efficiently with small gaps less than 1%.     

A continuous bi-level model for the expansion of highway networks

Adding new corridors to a highway network represents a multicriteria decision process in which a variety of social, environmental and economic factors must be evaluated and weighted for a large number of corridor alternatives. This paper proposes a new bi-level continuous location model for expansion of a highway network by adding several highway corridors within a geographical region. The upper level problem determines the location of the highway corridors, taking into account the budgetary and technological restrictions, while the lower level problem models the users’ behavior in the located transport network (choices of route and transport system). The proposed model takes into account the demand in the area served by the new network highway corridors, the available budget and the user behavior. This model uses geographical information in order to estimate the length-dependent costs (such as pavement and construction costs) and the cost of earth movement. The proposed method is tested using the standard particle swarm optimization algorithm and applied to the Castilla–La Mancha geographic database. The previous methodology has been extended to a multiobjective approach in order to handling uncertainty in demand.     

Modeling pedestrian flow accounting for collision avoidance during evacuation

Collision avoidance behavior has become an open challenging problem since it is one of critical factors that influence the pedestrian flow dynamics. In this paper, a cellular automaton (CA) model is developed to depict the pedestrian movements when collision avoidance behaviors exist during evacuation. Then, we utilize the proposed model to simulate the influences of the collision avoidance on the pedestrian movements during the evacuation in a classroom with two exits. The numerical results indicate that more collision avoidance behaviors have negative influences on the evacuation efficiency, and that more competition behaviors generate more collisions while have no prominent positive impacts on the evacuation efficiency. Moreover, the evacuation time increases with the decreasing number of aisles in the classroom and the number of collisions increases with the increasing number of parts in the classroom divided by aisles. The above results are helpful to develop effective evacuation strategies and design the internal layouts of buildings.