Learning from accidents : machine learning for safety at railway stations

In railway systems, station safety is a critical aspect of the overall structure, and yet, accidents at stations still occur. It is time to learn from these errors and improve conventional methods by utilizing the latest technology, such as machine learning (ML), to analyse accidents and enhance safety systems. ML has been employed in many fields, including engineering systems, and it interacts with us throughout our daily lives. Thus, we must consider the available technology in general and ML in particular in the context of safety in the railway industry. This paper explores the employment of the decision tree (DT) method in safety classification and the analysis of accidents at railway stations to predict the traits of passengers affected by accidents. The critical contribution of this study is the presentation of ML and an explanation of how this technique is applied for ensuring safety, utilizing automated processes, and gaining benefits from this powerful technology. To apply and explore this method, a case study has been selected that focuses on the fatalities caused by accidents at railway stations. An analysis of some of these fatal accidents as reported by the Rail Safety and Standards Board (RSSB) is performed and presented in this paper to provide a broader summary of the application of supervised ML for improving safety at railway stations. Finally, this research shows the vast potential of the innovative application of ML in safety analysis for the railway industry

Ensuring Cyber-Security in Smart Railway Surveillance with SHIELD

Modern railways feature increasingly complex embedded computing systems for surveillance, that are moving towards fully wireless smart-sensors. Those systems are aimed at monitoring system status from a physical-security viewpoint, in order to detect intrusions and other environmental anomalies. However, the same systems used for physical-security surveillance are vulnerable to cyber-security threats, since they feature distributed hardware and software architectures often interconnected by ‘open networks’, like wireless channels and the Internet. In this paper, we show how the integrated approach to Security, Privacy and Dependability (SPD) in embedded systems provided by the SHIELD framework (developed within the EU funded pSHIELD and nSHIELD research projects) can be applied to railway surveillance systems in order to measure and improve their SPD level. SHIELD implements a layered architecture (node, network, middleware and overlay) and orchestrates SPD mechanisms based on ontology models, appropriate metrics and composability. The results of prototypical application to a real-world demonstrator show the effectiveness of SHIELD and justify its practical applicability in industrial settings

Investigating rock mass failure precursors using a multi-sensor monitoring system. Preliminary results from a test-site (Acuto, Italy)

In the last few years, several approaches and methods have been proposed to improve early warning systems for managing risks due to rapid slope failures where important infrastructures are the main exposed elements. To this aim, a multi-sensor monitoring system has been installed in an abandoned quarry at Acuto (central Italy) to realise a natural-scale test site for detecting rock-falls from a cliff slope. The installed multi-sensor monitoring system consists of: i) two weather stations; ii) optical cam (Smart Camera) connected to an Artificial Intelligence (AI) system; iii) stress- strain geotechnical system; iv) seismic monitoring device and nano-seismic array for detecting microseismic events on the cliff slope. The main objective of the experiment at this test site is to investigate precursors of rock mass failures by coupling remote and local sensors. The integrated monitoring system is devoted to record strain rates of rock mass joints, capturing their variations as an effect of forcing actions, which are the temperature, the rainfalls and the wind velocity and direction. The preliminary tests demonstrate that the data analysis methods allowed the identification of external destabilizing actions responsible for strain effects on rock joints. More in particular, it was observed that the temperature variations play a significant role for detectable strains of rock mass joints. The preliminary results obtained so far encourage further experiments

A deep learning approach towards railway safety risk assessment

Railway stations are essential aspects of railway systems, and they play a vital role in public daily life. Various types of AI technology have been utilised in many fields to ensure the safety of people and their assets. In this paper, we propose a novel framework that uses computer vision and pattern recognition to perform risk management in railway systems in which a convolutional neural network (CNN) is applied as a supervised machine learning model to identify risks. However, risk management in railway stations is challenging because stations feature dynamic and complex conditions. Despite extensive efforts by industry associations and researchers to reduce the number of accidents and injuries in this field, such incidents still occur. The proposed model offers a beneficial method for obtaining more accurate motion data, and it detects adverse conditions as soon as possible by capturing fall, slip and trip (FST) events in the stations that represent high-risk outcomes. The framework of the presented method is generalisable to a wide range of locations and to additional types of risks

Transportation, Terrorism and Crime: Deterrence, Disruption and Resilience

Abstract: Terrorists likely have adopted vehicle ramming as a tactic because it can be carried out by an individual (or “lone wolf terrorist”), and because the skills required are minimal (e.g. the ability to drive a car and determine locations for creating maximum carnage). Studies of terrorist activities against transportation assets have been conducted to help law enforcement agencies prepare their communities, create mitigation measures, conduct effective surveillance and respond quickly to attacks. This study reviews current research on terrorist tactics against transportation assets, with an emphasis on vehicle ramming attacks. It evaluates some of the current attack strategies, and the possible mitigation or response tactics that may be effective in deterring attacks or saving lives in the event of an attack. It includes case studies that can be used as educational tools for understanding terrorist methodologies, as well as ordinary emergencies that might become a terrorist’s blueprint

The use of geomatic techniques to improve the management of metro infrastructure

The management of large infrastructures requires comprehensive knowledge of their characteristics and the elements that constitute them. It is essential to know which elements are involved and where they are located. At the same time also, it is vital to understand the overall geometry. However, it is difficult to obtain this information about underground infrastructures due to their lighting characteristics, hazards, lack of GNSS (Global Navigation Satellite System) signals and time available. In this case, to achieve the required quality in both tasks, the mobile mapping systems that are widely used in large surveys and urban inventories have to be adapted to obtain data in underground conditions. To achieve this, geodesic support is necessary. Therefore, a laser scanning and kinematic photogrammetry survey was carried out to obtain the centimetric precision and complete information that is still used today. This paper presents an adaptation of these systems for use in the Ferrocarril Metropolità de Barcelona.Peer ReviewedPostprint (author's final draft

Wireless Communication Systems for Urban Transport

This chapter describes the main features of the wireless communication systems of urban rail and related applications. The perspective will be complete: application, network and physical layers will be discussed. Moreover, to properly address some of the challenges that these systems face, we will provide a deep insight into propagation issues related to tunnels and urban areas. Finally, a detailed survey on the directions of research on all these topics will be provided

Inter-modality hubs in the Metropolitan Area of Barcelona: A comparison between the metropolitan and the local scale in a GIS tool to support urban planning decisions

Tratar con las necesidades de transporte de la sociedad urbana y, al mismo tiempo, mejorar la habitabilidad y la sostenibilidad de la ciudad es el problema al que nos enfrentamos hoy. El bicibox es un servicio gratuito de estacionamiento de bicicletas de larga duración que presenta una oportunidad única para incorporar la movilidad activa en las estaciones de tránsito y, al mismo tiempo, mejorar la vida en las calles de los barrios. Por lo tanto, el objetivo de este estudio es determinar el impacto que tienen los servicios de bicibox en el crecimiento de la zona de influencia de las estaciones de FGC (Ferrocarrils de la Generalitat de Catalunya) en el municipio de Sant Cugat del Vallès. El Àrea Metropolitana de Barcelona (AMB) proporcionó datos sobre los usuarios de Bicibox para este estudio. Para lograr los objetivos del estudio, los datos de los usuarios se analizaron en tres escalas para identificar las preferencias de los usuarios, los comportamientos y las variables de influencia. Los métodos utilizados para esta investigación incluyeron la comparación de gráficos, un mapa QGIS y una investigación de los servicios cerca del centro de movilidad. Esta tesis concluye que los usuarios prefieren estaciones de Bicibox colocadas directamente frente a las estaciones de tránsito y que estas sean muy visibles. Adicionalmente, se determinó que las estaciones de bicicletas que se encuentran justo en frente de una estación de tren, en una estación de autobuses o en el medio de ambas estaciones funcionan mejor que las estaciones de bicibox situadas en una ubicación más lejana. Además, se ha comprobado que el uso de bicibox tiene un efecto positivo en la ampliación de las áreas de captación de las estaciones de FGC en el Municipio de Sant Cugat del Vallès. También se estimó el tamaño del área de captación y la dirección de expansión. .Dealing with the transportation needs of urban society while simultane-ously enhancing the liveability and sustainability of the city is the problem we confront today. The bicibox, a free long-term bicycle parking service, presents a unique opportunity to incorporate active mobility into transit stations while also enhancing the street life of the neighbourhoods. Therefore, the purpose of this study is to determine the extent of impact bicibox services have on the growth of the catchment area for FGC (Ferro-carrils de la Generalitat de Catalunya) railway stations in the Municipality of Sant Cugat del Vallès. Àrea Metropolitana de Barcelona (AMB) provided data on Bicibox users for this study. To achieve the study's objectives, user data was analysed on three scales to identify user preferences, behaviours, and influence varia-bles. Methods used for this research included graph comparison, a QGIS map, and an investigation of amenities near the mobility hub. This thesis concluded that users prefer biciboxes that are placed directly in front of transit stations and are highly visible. Additionally, it was de-termined that bicycle stations that are situated right in front of a railway station, a bus station, or in the middle of both stations perform better than bicibox stations located further away from the station. The usage of bicibox was also found to have a positive effect on the expansion of the catchment areas for the FGC railway stations in the Municipality of Sant Cugat del Vallès. The catchment area's size and expansion direction were also estimated