Rehabilitation, employment and follow-up [Rehabilitation, employment and follow-up unit]

Sep 1, 2020 - Sep 1, 2024

Rehabilitation, employment and follow-up unit

Scholarships and Cultural Relations [Head of scholarships and Cultural Relations Unit]

Sep 1, 2024 - Present

Head of scholarships and Cultural Relations Unit

Internet of Things – ICIOT 2025

Sep 15, 2025

Journal Springer Nature

publisher Springer Nature

DOI https://doi.org/10.1007/978-3-032-06170-6

This book constitutes the refereed proceedings of the 10th International Conference on Internet of Things – ICIOT 2025, held as part of the Services Conference Federation, SCF 2025, in Hong Kong, China during September 27–30, 2025.

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The Impact of Train Positioning Inaccuracies on Railway Traffic Management Systems: Framework Development and Impacts on TMS Functions

May 4, 2020

Journal IET Intelligent Transport Systems

DOI doi.org/10.1049/iet-its.2019.0503

Nowadays the railway industry is beginning to give serious consideration to using intelligent traffic management systems (TMSs) in order to improve railway performance regarding train and passenger delays and robust use of capacity. The TMS is responsible for handling railway traffic once a disturbance happens. A fundamental input parameter of a TMS is the train positions, to be used for traffic re-planning purposes. Inaccuracy in the train positioning data could significantly influence the effectiveness of a TMS. In this study, the authors developed a framework to evaluate how inaccuracies in the train position reporting may affect the TMS performance. This is achieved by assessing the impact of adding inaccuracies to the train position reported to a simulated TMS as it handles operational disturbances in real-time. The performance of the TMS is analysed by considering variability in overall delay outcomes after re-planning based on using accurate/inaccurate positional data. They demonstrate the usefulness of their framework in determining the positional accuracy required for the effective application of a basic rescheduling system via an example on a bottleneck area. Results show how the positioning inaccuracies can affect TMS and thus the overall delay.

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Using information engineering to understand the impact of train positioning uncertainties on railway subsystems

Dec 16, 2019

Journal University of Birmingham, School of Engineering, Department of Electronic, Electrical and Systems Engineering

Many studies propose new advanced railway subsystems, such as Driver Advisory System (DAS), Automatic Door Operation (ADO) and Traffic Management System (TMS), designed to improve the overall performance of current railway systems. Real time train positioning information is one of the key pieces of input data for most of these new subsystems. Many studies presenting and examining the effectiveness of such subsystems assume the availability of very accurate train positioning data in real time. However, providing and using high accuracy positioning data may not always be the most cost-effective solution, nor is it always available. The accuracy of train position information is varied, based on the technological complexity of the positioning systems and the methods that are used. In reality, different subsystems, henceforth referred to as ‘applications’, need different minimum resolutions of train positioning data to work effectively, and uncertainty or inaccuracy in this data may reduce the effectiveness of the new applications. However, the trade-off between the accuracy of the positioning data and the required effectiveness of the proposed applications is so far not clear. A framework for assessing the impact of uncertainties in train positions against application performance has been developed. The required performance of the application is assessed based on the characteristics of the railway system, consisting of the infrastructure, rolling stock and operational data. The uncertainty in the train positioning data is considered based on the characteristics of the positioning system. The framework is applied to determine the impact of the positioning uncertainty on the application’s outcome. So, in that way, the desired position resolution associated with acceptable application performance can be characterised. In this thesis, the framework described above is implemented for DAS and TMS applications to understand the influence of positioning uncertainty on their fundamental functions compared to base case with high accuracy (actual position). A DAS system is modelled and implemented with uncertainty characteristic of a Global Navigation Satellite System (GNSS). The train energy consumption and journey time are used as performance measures to evaluate the impact of these uncertainties compared to a base case. A TMS is modelled and implemented with the uncertainties of an on-board low-cost low-accuracy positioning system. The impact of positioning uncertainty on the modelled TMS is evaluated in terms of arrival punctuality for different levels of capacity consumption. The implementation of the framework for DAS and TMS applications determines the following: • which of the application functions are influenced by positioning uncertainty; • how positioning uncertainty influences the application output variables; • how the impact of positioning uncertainties can be identified, through the application output variables, whilst considering the impact of other railway uncertainties; • what is the impact of the underperforming application, due to positioning uncertainty, on the whole railway system in terms of energy, punctuality and capacity.

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An Investigation into the Impact of Positioning System Inaccuracies with a Traffic Management System on Line Capacity

Dec 12, 2018

Journal IEEE Intelligent Rail Transportation

DOI 10.1109/ICIRT.2018.8641580

Demand for passenger and freight railway services has increased in recent years. This puts the railway system under pressure to maximize the use of available capacity. An intelligent traffic management systems (TMS) is used to improve railway performance and handle the railway traffic once a disturbance happens. TMS needs a variety of input data to monitor the current traffic, predict the future traffic and solve potential conflicts. A fundamental input parameter of an intelligent TMS is the position of trains in real-time. Train position reporting inaccuracies can significantly influence the TMS performance and lead it to provide suboptimal solutions. In this paper, we assess the impact of position reporting inaccuracies on a local TMS applied to timetables consuming different amounts of capacity. A case study on Dundee Central Junction, in the Scotland/UK, has been investigated. The results are compared using the trains' total delay and the number of cases where TMS has been misguided and a suboptimal solution was produced. The results show that, once TMS is misguided by positioning inaccuracies, a high capacity timetable's TMS solution leads to more delays compared with a lower capacity timetable.

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Investigation into the Positioning Accuracy Required for Traffic Management Systems on Different Types of Railway Services

May 17, 2018

Journal IET Railway Engineering

DOI doi.org/10.1049/cp.2018.0073

Nowadays, the digitisation and automation of railway systems are being carried out all over the world, in order to increase the systems' accuracy, efficiency and reduce maintenance costs. As part of this trend, intelligent traffic management systems (TMS) are under investigation as a way to increase punctuality and automatically return trains back to the original traffic plan when an operational disturbance happens. A TMS needs a variety of input data to consider the current traffic conditions, predict the future state and decide on a new traffic plan when necessary. Numerous studies have proposed TMS designs; all the proposed systems need to read the train positions in real-time for monitoring and analysis purposes. However, the accuracy of the train positions that can be reported in real-time varies; it depends mainly on the control system design and type of positioning sensor used. Train position uncertainty can significantly influence the performance of a proposed TMS, although the impact has rarely been assessed. In this study, TMS positional accuracy requirements for different railway services are investigated. The influence of train positioning uncertainty is studied with respect to TMS of urban, inter-city and high-speed and mixed-traffic services. This is achieved by simulating the characteristics of these railway services in terms of different trains, tracks, a local TMS and train positioning systems with their associated uncertainty. The experiment is carried out first using exact position data; then it is repeated using position data containing stochastic inaccuracies. The TMS outputs are compared with respect to the train order of the traffic plan and the trains' total delay. The results show that a small positioning deviation can influence the TMS performance of an urban service, while the TMS of highspeed service is affected less by positioning deviation than the TMS of other services.

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Investigation into train positioning systems for saving energy with optimised train trajectories

Aug 23, 2016

Journal IEEE Intelligent Rail Transportation

DOI 10.1109/ICIRT.2016.7588769

One approach to reduce energy consumption in railway systems is to implement optimised train trajectories. These are speed profiles that reduce energy consumption without foregoing customer comfort or running times. This is achieved by avoiding unnecessary braking and running at reduced speed whilst maintaining planned arrival times. An optimised train trajectory can be realised using a driver advisory system (DAS). The optimal train trajectory approach needs a variety of input data, such as the train's position, speed, direction, gradient, maximum speed, dwell time, and station locations. Many studies assume the availability of a very accurate train position in real time. However, providing and using high precision positioning data is not always the most cost-effective solution. The aim of this research is to investigate the use of appropriate positioning systems, with regard to their performance and cost specifications, with optimised trajectories. This paper first presents a single train trajectory optimisation to minimise overall energy consumption. It then explores how errors in train position data affect the total consumed energy, with regard to the tractive force due to gradient when following the optimised trajectory. A genetic algorithm is used to optimise the train speed profile. The results from simulation indicate that a basic GPS system for specifying train position is sufficient to save energy via an optimised train trajectory. The authors investigate the effect of error in positioning data, to guarantee the reliability of employing the optimised solution for saving energy whilst maintaining an acceptable journey time.

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Vehicle Traffic Congestion Estimation Based on RFID

Jan 1, 2012

Journal International Journal of Engineering Business Management

DOI doi.org/10.5772/54923

Due to the proliferation in the number of vehicles on the road, traffic problems are bound to exist. Therefore, the use of Intelligent Transportation Systems (ITS) has become mandatory for obtaining traffic information from roads. Radio Frequency Identification (RFID) technology has been used to obtain vehicles' IDs (tag ID) from RFID readers and to collect traffic information in real-time. This paper proposes a simulation system for the Vehicle Traffic Congestion Estimation (VTCE) based on RFID. The RFID reader will read the vehicle tags and transfer the necessary information to a database in a Central Computer System (CCS). The CCS utilizes these data to determine the traffic congestion status of the road network by following a specific procedure.

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Vehicle Location System Based on RFID

Dec 8, 2011

Journal IEEE Developments in E-systems Engineering (DeSE)

DOI 10.1109/DeSE.2011.11

Due to the rapid worldwide growth in the number of vehicles on the road, traffic problems are bound to exist. Hence, the implementation of Intelligent Transportation Systems (ITS) to obtain traffic information from roads is becoming an urgent necessity. This paper tackles the problem of designing a Vehicle Location System (VLS) based on Radio Frequency Identification (RFID). The proposed system consists of passive RFID tags on vehicles, RFID readers, wireless Ethernet communication with a Central Computer System (CCS) and commanding software. The gathered information will be filtered and stored in a suitable form to be easily used in many useful applications. Such applications include, but not limited to, location of vehicles in intersections at any time, path and orientation of vehicle in intersections, the numbers and the IDs of vehicles passing each intersection at any time, traffic information statistics, estimate the traffic congestion situation in roads, etc.

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RFID Based Design for Vehicle Location System

Dec 1, 2011

Journal Al-Nahrain University; Computer Engineering

Due to the rapid growth in the number of vehicles on the street, traffic problems are bound to exist. Hence, implementation of Intelligent Transportation Systems (ITS) to obtain traffic information from roads by Automatic Vehicle Identification (AVI) is becoming an urgent necessity. The Radio Frequency Identification (RFID) Technology can be used for AVI to collect the traffic information in real-time from roads by getting the vehicles ID from RFID readers. This thesis tackles the problem of designing Vehicle Location System (VLS), the proposed system consists of a passive RFID tags on vehicles, RFID reader, reader's antenna, wireless communication with a Central Computer System (CCS) and commanding software (RFID middleware and database structure), also VLS applications, SMS server and website. The designed system controls, manages and monitors the performance of RFID readers. It also filters and stores the information in a suitable form to be easily used in the application system and website. The system implemented by using Rifidi Platform as simulator for RFID system and VLS is programmed by Visual Basic 2010. The VLS is composed of installing of two RFID readers in traffic intersections; each reader has four antennas, for monitoring all entries and exits of the intersection. The VLS used the gathered data from traffic intersections RFID readers in many applications including the following: location of vehicles in intersections at any time, path and orientation of vehicle in intersections, numbers and vehicles ID passed in each intersection at any time, estimate the traffic congestion situation in roads and intersections through SMS server and websites, drawing path of vehicles within VLS region on map, monitoring illegal and stolen vehicles real-time and tracking certain vehicle color.

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