Methods for choosing loaded train and car routes along a railroad network

We consider the problems of designing the routes for freight cars from departure stations to destination stations and problems and planning model for the works and for finding the necessary number of trains to deliver a given number of freight cars from departure stations to destination stations.     

Driving monotonous routes in a train simulator: the effect of task demand on driving performance and subjective experience

Although monotony is widely recognised as being detrimental to performance, its occurrence and effects are not yet well understood. This is despite the fact that task-related characteristics, such as monotony and low task demand, have been shown to contribute to performance decrements over time. Participants completed one of two simulated train-driving scenarios. Both were highly monotonous and differed only in terms of the level of cognitive demand required (i.e. low demand or high demand). These results highlight the seriously detrimental effects of the combination of monotony and low task demands and clearly show that even a relatively minor increase in cognitive demand can mitigate adverse monotony-related effects on performance for extended periods of time. Monotony is an inherent characteristic of transport industries, including rail, aviation and road transport, which can have adverse impact on safety, reliability and efficiency. This study highlights possible strategies for mitigating these adverse effects. Practitioner Summary: This study provides evidence for the importance of cognitive demand in mitigating monotony-related effects on performance. The results have clear implications for the rapid onset of performance deterioration in low demand monotonous tasks and demonstrate that these detrimental performance effects can be overcome with simple solutions, such as making the task more cognitively engaging.     

Soft computing methods applied to train station parking in urban rail transit

This paper presents three models - a linear model, a generalized regression neural network (GRNN) and an adaptive network based fuzzy inference system (ANFIS) - to estimate the train station parking (TSP) error in urban rail transit. We also develop some statistical indices to evaluate the reliability of controlling parking errors in a certain range. By comparing modeling errors, the subtractive clustering method other than grid partition method is chosen to generate an initial fuzzy system for ANFIS. Then, the collected TSP data from two railway stations are employed to identify the parameters of the proposed three models. The three models can make the average parking errors under an acceptable error, and tuning the parameters of the models is effective in dynamically reducing parking errors. Experiments in two stations indicate that, among the three models, (1) the linear model ranks the third in training and the second in testing, nevertheless, it can meet the required reliability for two stations, (2) the GRNN based model achieves the best performance in training, but the poorest one in testing due to overfitting, resulting in failing to meet the required reliability for the two stations, (3) the ANFIS based model obtains better performance than model 1 both in training and testing. After analyzing parking error characteristics and developing a parking strategy, finally, we confirm the effectiveness of the proposed ANFIS model in the real-world application.     

From timetabling to train regulation—a new train operation model

A new train operation model proposed here not only considers the flexibility of train regulation, or train rescheduling problem, but also the objectives of timetabling process. A genetic algorithm is applied to solve this problem efficiently. Thus no matter the problem is planning the timetable of trains, the unusual passenger flow occurrence or the incident caused delay, our model will make the train regulation as the same as the timetable construction. This will simplify the work of administration. Our model also shows that once the delay occurred, the waiting time of the passengers will be the cost to delay every train. If the delay is not large enough, the system can have some rooms for removing the influence of the delay through our model.     

基于硬时间窗的技术站解编方案综合协调优化

针对现有制定的解编方案无法有效地满足铁路技术站阶段计划配流工作,基于牵引质量和换长的不同硬时间窗满轴约束,并综合考虑车流接续和编组去向约束,以总车流量、满轴出发列车最多为目标,建立了技术站多目标动态配流模型。为实现解编方案综合协调优化,依据解体和编组顺序调整规则,并通过定义可解集合和改进蚁群算法的状态转移规律及信息素更新策略,设计了一种基于蚁群算法的辅助决策支持系统。算例表明该辅助决策支持系统可以缩小配流问题规模,帮助决策者选择满意的解编配流方案,同时可以考虑解编顺序的改变对配流结果带来的影响,做到解体照顾编组,从而为实现铁路技术站调度系统的综合协调优化提供理论支持。     

Network-based reconfiguration routes for a self-reconfigurable robot

This paper presents a network-based analysis approach for the reconfiguration problem of a self-reconfigurable robot. The self-reconfigurable modular robot named ＂AMOEBA-I＂ has nine kinds of non-isomorphic configurations that consist of a configuration network. Each configuration of the robot is defined to be a node in the weighted and directed configuration network. The transformation from one configuration to another is represented by a directed path with nonnegative weight. Graph theory is applied in the reconfiguration analysis, where reconfiguration route, reconfigurable matrix and route matrix are defined according to the topological information of these configurations. Algorithms in graph theory have been used in enumerating the available reconfiguration routes and deciding the best reconfiguration route. Numerical analysis and experimental simulation results prove the validity of the approach proposed in this paper. And it is potentially suitable for other self-reconfigurable robots＇ configuration control and reconfiguration planning.     

磁浮列车搭接结构的非线性解耦控制

磁浮列车的搭接结构是一个多输入多输出的非线性系统, 对该系统进行稳定控制是确保磁浮列车可靠性的关键. 本文采用微分几何方法对系统解耦; 采用反馈线性化方法对解耦后的系统进行线性化, 确保了系统的全局稳定性; 对线性化之后的系统采用极点配置的方法进行控制律设计, 使系统的动态性能达到一定的指标; 最后给出了应用此方法的一个实际例子.     

Simulation based optimization of a train maintenance facility

In this paper, a simulation based optimization method is developed for optimization of scheduling policies. This method uses the technique of coupling industrial simulation software with a multi-objective optimizer based on genetic algorithms. It is used to optimize the performances of a railway maintenance facility by choosing the best scheduling policy. Numerical results show that a significant improvement is achieved with respect to the simulation results of the existing system. The method adapted by our problem can be extended to deal with the selection of scheduling rules in using other types of simulation models.     

Prediction of pedestrians routes within a built environment in normal conditions

Modelling and prediction of pedestrian routing behaviours within known built environments has recently attracted the attention of researchers across multiple disciplines, owing to the growing demand on urban resources and requirements for efficient use of public facilities. This study presents an investigation into pedestrians’ routing behaviours within an indoor environment under normal, non-panic situations. A network-based method using constrained Delaunay triangulation is adopted, and a utility-based model employing dynamic programming is developed. The main contribution of this study is the formulation of an appropriate utility function that allows an effective application of dynamic programming to predict a series of consecutive waypoints within a built environment. The aim is to generate accurate sequence waypoints for the pedestrian walking path using only structural definitions of the environment as defined in a standard CAD format. The simulation results are benchmarked against those from the A¹ algorithm, and the outcome positively indicates the usefulness of the proposed method in predicting pedestrians’ route selection activities.     

On constructing a family of student delivery routes in minimal time

We consider the school bus routing problem which is to construct the routes for delivering students after classes by multiple buses in minimal time. We show the corresponding linear partially integer model. Together with an exact algorithm we show a simple heuristic algorithm and present the results of a computational experiment.     

Matrix modelling in dynamics of a 2-DOF orienting gear train

Recursive matrix relations for kinematics and dynamics analysis of a 2-DOF orienting gear train are established in this paper. The mechanism is a parallel system with five moving links and three bevel gear pairs controlled by two electric motors. Knowing the rotation motion of the end-effector, the inverse dynamic problem is solved using an approach based on the principle of virtual work and have verified the results in the framework of the Lagrange equations of the second kind. Finally, some graphs for the input angles of rotation, the forces and the powers of the actuators are obtained.     

The periodicity and robustness in a single-track train scheduling problem

The most important operating problem in any railway industry is to produce robust train timetables with minimum delays. The train scheduling problem is defined as an application of job shop scheduling which is considered to be one of the most interesting research topics. This paper deals with scheduling different types of trains in a single railway track. The authors have focused on the robust and periodic aspects of produced timetables. This paper is also concerned with some applicable constraints, such as the acceleration and deceleration times, station capacity and headway constraints. The periodic timetable for railways is modeled based on the periodic event scheduling problem (PESP). Furthermore, a fuzzy approach is used to reach a tradeoff among the total train delays, the robustness of schedules, and the time interval between departures of trains from the same origins. To solve large-scale problems, a meta-heuristic algorithm based on simulated annealing (SA) is utilized and validated using some numerical examples on a periodic robust train scheduling problem. Finally, a robustness measure is defined in order to assure the effectiveness of the proposed SA to find robust solutions.     

Messages of oscillatory correlograms: a spike train model

Oscillatory correlograms are widely used to study neuronal activity that shows a joint periodic rhythm. In most cases, the statistical analysis of cross-correlation histograms (CCH) features is based on the null model of independent processes, and the resulting conclusions about the underlying processes remain qualitative. Therefore, we propose a spike train model for synchronous oscillatory firing activity that directly links characteristics of the CCH to parameters of the underlying processes. The model focuses particularly on asymmetric central peaks, which differ in slope and width on the two sides. Asymmetric peaks can be associated with phase offsets in the (sub-) millisecond range. These spatiotemporal firing patterns can be highly consistent across units yet invisible in the underlying processes. The proposed model includes a single temporal parameter that accounts for this peak asymmetry. The model provides approaches for the analysis of oscillatory correlograms, taking into account dependencies and nonstationarities in the underlying processes. In particular, the auto- and the cross-correlogram can be investigated in a joint analysis because they depend on the same spike train parameters. Particular temporal interactions such as the degree to which different units synchronize in a common oscillatory rhythm can also be investigated. The analysis is demonstrated by application to a simulated data set.     

Multi-functional design of a composite high-speed train body structure

A multi-level, multi-functional, optimisation methodology is suggested for the design of a composite high speed train car body. The structure consists of a layer of inner lining (glass fibre/vinyl ester), a layer of fibrous insulation, and a load carrying sandwich panel (carbon fibre/epoxy face sheets on a PMI core). Besides the most commonly used design constraints, such as mechanical strength, stiffness and geometry, also acoustic and thermal insulation as well as fire safety is included in the optimisation. The results suggest that well over 40 % mass reduction can be achieved with these types of structures.     

一种混合型货运列车车内通讯网络的设计

构建可靠的货运列车车内通讯网络是实现货运列车状态在线监测的基础。针对车内无线通讯网络的研究现状,提出了一种混合型货运列车车内通讯网络。该网络利用CAN总线完成单节车辆及机车的内部通讯,并在机车的尾端和车辆两端安装无线模块,可实现同列车的所有机车、车辆之间通讯。通过将有线通讯和无线数据传输相结合,可以显著减小无线通讯距离,提高通讯效率及可靠性。实验表明,该系统可以较好地满足货运列车状态在线监测的通讯功能要求,对于提高货运列车的运行效率和安全性具有重要意义。     

Efficient computation of evacuation routes on a three-dimensional geometric network

We consider a real-time emergency evacuation problem that seeks to compute a set of rapid evacuation routes in a building. Given a three-dimensional geometric structure of the evacuation network, an emergency evacuation route is a sequence of movements of people away from the threat or actual occurrence of a hazard (such as a fire, a hidden bomb) to a safe exit in the network. In such a network each room/crossing/exit in the building is designated as a node and the corridors/staircases/links between the rooms are edges. The evacuation times assigned to the edges are normally distributed random variables. This stochastic routing problem subject to deadline constraints is NP-hard. We provide a new pseudo-polynomial-time dynamic programming algorithm to solve this problem. Based on this algorithm, we construct two types of approximation algorithm, namely a fully polynomial-time approximation scheme providing “almost-optimal” solutions and a fully polynomial-time approximately feasible scheme yielding a best “almost feasible” solution. We present a case study and results of computational experiments to illustrate the working and efficacy of the proposed solution methods, respectively.     

Finding routes in anonymous sensor networks

We consider networks of anonymous sensors and address the problem of constructing routes for the delivery of information from a group of sensors in response to a query by a sink. In order to circumvent the restrictions imposed by anonymity, we rely on using the power level perceived by the sensors in the query from the sink. We introduce a simple distributed algorithm to achieve the building of routes to the sink and evaluate its performance by means of simulations.     

Heuristic approach for solving employee bus routes in a large-scale industrial factory

This paper compares different methods for solving a location-routing problem (LRP), using real-world data from the bus transport service for employees of a large-scale industrial factory in Thailand. We tested four AI (artificial intelligence) techniques Maximin, K-means, Fuzzy C-means, and Competitive Learning and two hybrids of these four K-means with Competitive Learning and K-means with Maximin to allocate the bus stops. The efficiency of the algorithms was compared, in terms of the quality of the solutions. The K-means with Maximin provided the best solution, as it minimized number of bus stop locations and employees’ total traveling distance while satisfied employee at maximum radius 1.73 km, compared to K-means with Competitive Learning, as the same number of bus stop it provided higher total traveling distance and maximum radius. The other non-hybrid techniques provided higher number of bus stop locations.We then used ant colony optimization (ACO) to determine the optimal routing between the 300–700 bus stops as allocated by K-means with Maximin. The optimal bus routing to transport the factory’s 5000 plus employees required 134 buses (134 independent routes) covering 500 bus stops and traveling nearly 5000 km. While optimal, this routing was costly and created monitoring difficulties. To address these concerns, we constrained the number of bus routes; while this dramatically increased the total distance, it provided a more practical solution for the factory.     

Participatory design with train drivers — a process analysis

A participatory design process involving train drivers is analyzed and described in this paper. A group of six drivers were involved in the design process, and within a short period, four design iterations were completed. The present case study was the final part of a larger research project (TRAIN) investigating the train driving task including the drivers' information environment, number and nature of hours worked, work situation and work environment, and their effect on the drivers' behaviour and the train driver system safety.Although usability activities are widely used in IT development today, the users are not involved to the desired extent. This paper argues that to produce usable systems, quality time has to be spent initially to acquire knowledge of a work domain and establishing a common ground in terms of shared knowledge and a better understanding of the work context between the parties involved in system development. Our suggestions on participatory analysis and design that conclude the paper are based on the present case study including train drivers, as well as our experiences from previous case studies.     

Effective visualization of short routes

In this work we develop a new alternative to conventional maps for visualization of relatively short paths as they are frequently encountered in hotels, resorts or museums. Our approach is based on a warped rendering of a 3D model of the environment such that the visualized path appears to be straight even though it may contain several junctions. This has the advantage that the beholder of the image gains a realistic impression of the surroundings along the way which makes it easy to retrace the route in practice. We give an intuitive method for generation of such images and present results from user studies undertaken to evaluate the benefit of the warped images for orientation in unknown environments.