T.K. Ho

A Fiber Bragg Grating Sensor System for Train Axle Counting

Railway signaling facilitates two main functions, namely, train detection and train control, in order to maintain safe separations among the trains. Track circuits are the most commonly used train detection means with the simple open/close circuit principles; and subsequent adoption of axle counters further allows the detection of trains under adverse track conditions. However, with electrification and power electronics traction drive systems, aggravated by the electromagnetic interference in the vicinity of the signaling system, railway engineers often find unstable or even faulty operations of track circuits and axle counting systems, which inevitably jeopardizes the safe operation of trains. A new means of train detection, which is completely free from electromagnetic interference, is therefore required for the modern railway signaling system. This paper presents a novel optical fiber sensor signaling system. The sensor operation, field setup, axle detection solution set, and test results of an installation in a trial system on a busy suburban railway line are given.

Evaluation of Maintenance Schedules on Railway Traction Power Systems

Abstract In electrified railways, the traction power systems carry power to trains and their reliability is vital to the quality of train services. There are many components in the traction power system, from interface with utility distribution network to contacts with trains, and they are physically located along the rail line. Subject to usage, environment, and ageing, conditions of components deteriorate with time. Regular maintenance has to be carried out to restore their conditions and prevent them from failure. However, the decisions on the suitable length of maintenance intervals often lead railway operators to the dilemma of minimizing both risk of failure and operation cost. On the basis of a stochastic lifetime model, this article presents a generic software evaluation tool that enables the operators to manage risk of failure and cost quantitatively in order to match their preferred levels of service quality. The lifetime model includes the effects of condition restoration because of maintenance of regular intervals and ageing acceleration because of electrical stress from traffic demands. Examples of simulation results are given to illustrate the applicability of this lifetime model.

Coast control of train movement with genetic algorithm

Railway service is now the major transportation means in most of the countries around the world. With the increasing population and expanding commercial and industrial activities, a high quality of railway service is the most desirable. We present an application of genetic algorithms (GA) to search for the appropriate coasting point(s) and investigate the possible improvement on fitness of genes. Single and multiple coasting point control with simple GA are developed to attain the solutions and their corresponding train movement is examined. The multiple coasting point control with hierarchical genetic algorithm (HGA) is then proposed to integrate the determination of the number of coasting points.

Train service timetabling in railway open markets by particle swarm optimisation

Railway timetabling is an important process in train service provision as it matches the transportation demand with the infrastructure capacity while customer satisfaction is also considered. It is a multi-objective optimisation problem, in which a feasible solution, rather than the optimal one, is usually taken in practice because of the time constraint. The quality of services may suffer as a result. In a railway open market, timetabling usually involves rounds of negotiations amongst a number of self-interested and independent stakeholders and hence additional objectives and constraints are imposed on the timetabling problem. While the requirements of all stakeholders are taken into consideration simultaneously, the computation demand is inevitably immense. Intelligent solution-searching techniques provide a possible solution. This paper attempts to employ a particle swarm optimisation (PSO) approach to devise a railway timetable in an open market. The suitability and performance of PSO are studied on a multi-agent-based railway open-market negotiation simulation platform.

Optimal Track Access Rights Allocation for Agent Negotiation in an Open Railway Market

In open railway access markets, a train service provider (TSP) negotiates with an infrastructure provider (IP) for track access rights. This negotiation has been modeled by a multiagent system in which the IP and the TSP are represented by separate software agents. One of the tasks of the IP agent is to generate feasible (and preferably optimal) track access rights, subject to the constraints submitted by the TSP agent. This paper formulates an IP-TSP transaction and proposes a branch-and-bound algorithm for the IP agent to identify the optimal track access rights. Empirical simulation results show that the model is able to emulate rational agent behaviors. The simulation results also show good consistency between the timetables that were attained from the proposed methods and those that were derived by the scheduling principles adopted in practice.

A New and Efficient Intelligent Collaboration Scheme for Fashion Design

Technology-mediated collaboration process has been extensively studied for over a decade. Most applications with collaboration concepts reported in the literature focus on enhancing efficiency and effectiveness of the decision-making processes in objective and well-structured workflows. However, relatively few previous studies have investigated the applications of collaboration schemes to problems with subjective and unstructured nature. In this paper, we explore a new intelligent collaboration scheme for fashion design which, by nature, relies heavily on human judgment and creativity. Techniques such as multicriteria decision making, fuzzy logic, and artificial neural network (ANN) models are employed. Industrial data sets are used for the analysis. Our experimental results suggest that the proposed scheme exhibits significant improvement over the traditional method in terms of the time-cost effectiveness, and a company interview with design professionals has confirmed its effectiveness and significance.

A parallel solution to linear systems

Streaming SIMD Extensions (SSE) is a unique feature embedded in the Pentium III and IV classes of microprocessors. By fully exploiting SSE, parallel algorithms can be implemented on a standard personal computer and a theoretical speedup of four can be achieved. In this paper, we demonstrate the implementation of a parallel LU matrix decomposition algorithm for solving linear systems with SSE and discuss advantages and disadvantages of this approach based on our experimental study.

Train Control to Reduce Delays upon Service Disturbances at Railway Junctions

Train delay is one of the most important indexes to evaluate the service quality of the railway. Because of interactions among different trains, a delayed train may hinder subsequent trains scheduled on other lines at junction area. Trains may be forced to stop or decelerate, which consequently leads to the loss of run-time. This paper proposes a time-saving control method to recover the train delay as much as possible. In the proposed method, golden section search is adopted to identify the optimal train speed at the time of signal upgrade in the conflicting area, which enables the train to depart from the conflicting area as soon as possible. A heuristic method is then developed to attain the train control scheme to realize the optimal train speed at the time of signal upgrade in the conflicting area. Simulation study indicates that the proposed method enables the train to across the conflicting area with smaller run-time and therefore leads to larger delay reduction, in comparison with the traditional maximum speed control method and the green wave control method.

Conflict Resolution through Negotiation in a Railway Open Access Market: a Multi-agent System Approach

Open access reforms to railway regulations allow multiple train operators to provide rail services on a common infrastructure. As railway operations are now independently managed by different stakeholders, conflicts in operations may arise, and there have been attempts to derive an effective access charge regime so that these conflicts may be resolved. One approach is by direct negotiation between the infrastructure manager and the train service providers. Despite the substantial literature on the topic, few consider the benefits of employing computer simulation as an evaluation tool for railway operational activities such as access pricing. This article proposes a multi-agent system (MAS) framework for the railway open market and demonstrates its feasibility by modelling the negotiation between an infrastructure provider and a train service operator. Empirical results show that the model is capable of resolving operational conflicts according to market demand.Abstract Open access reforms to railway regulations allow multiple train operators to provide rail services on a common infrastructure. As railway operations are now independently managed by different stakeholders, conflicts in operations may arise, and there have been attempts to derive an effective access charge regime so that these conflicts may be resolved. One approach is by direct negotiation between the infrastructure manager and the train service providers. Despite the substantial literature on the topic, few consider the benefits of employing computer simulation as an evaluation tool for railway operational activities such as access pricing. This article proposes a multi-agent system (MAS) framework for the railway open market and demonstrates its feasibility by modelling the negotiation between an infrastructure provider and a train service operator. Empirical results show that the model is capable of resolving operational conflicts according to market demand.

A study of the generalised max-min fair rate allocation for ABR control in ATM

In the rate-based flow control for ATM Available Bit Rate service, fairness is an important requirement, i.e. each flow should be allocated a fair share of the available bandwidth in the network. Max–min fairness, which is widely adopted in ATM, is appropriate only when the minimum cell rates (MCRs) of the flows are zero or neglected. Generalised max–min (GMM) fairness extends the principle of the max–min fairness to accommodate MCR. In this paper, we will discuss the formulation of the GMM fair rate allocation, propose a centralised algorithm, analyse its bottleneck structure and develop an efficient distributed explicit rate allocation algorithm to achieve the GMM fairness in an ATM network. The study in this paper addresses certain theoretical and practical issues of the GMM fair rate allocation.