Visual Analysis of Reactionary Train Delay from an Agent Based Model

We design and apply interactive visualisation to help understand reactionary (knock-on) delay in trains using a set of ‘Monte-Carlo’ style Agent Based Model runs, and to help train operating companies design interventions. Our interactive graphics indicate the locations where primary delay occurs, where reactionary delay occurs, the types of primary delays, how these vary across the runs and the mechanisms of delay. We continue to work with the train industry to refine these methods. Interactive visualisation still has unexplored potential to help make Agent Based Models more explainable

Uncertainty management at the airport transit view

Air traffic networks, where airports are the nodes that interconnect the entire system, have a time-varying and stochastic nature. An incident in the airport environment may easily propagate through the network and generate system-level effects. This paper analyses the aircraft flow through the Airport Transit View framework, focusing on the airspace/airside integrated operations. In this analysis, we use a dynamic spatial boundary associated with the Extended Terminal Manoeuvring Area concept. Aircraft operations are characterised by different temporal milestones, which arise from the combination of a Business Process Model for the aircraft flow and the Airport Collaborative Decision-Making methodology. Relationships between factors influencing aircraft processes are evaluated to create a probabilistic graphical model, using a Bayesian network approach. This model manages uncertainty and increases predictability, hence improving the system's robustness. The methodology is validated through a case study at the Adolfo Suárez Madrid-Barajas Airport, through the collection of nearly 34,000 turnaround operations. We present several lessons learned regarding delay propagation, time saturation, uncertainty precursors and system recovery. The contribution of the paper is two-fold: it presents a novel methodological approach for tackling uncertainty when linking inbound and outbound flights and it also provides insight on the interdependencies among factors driving performance

Systemic risk approach to mitigate delay cascading in railway networks

In public railway systems, minor disruptions can trigger cascading events that lead to delays in the entire system. Typically, delays originate and propagate because the equipment is blocking ways, operational units are unavailable, or at the wrong place at the needed time. The specific understanding of the origins and processes involved in delay-spreading is still a challenge, even though large-scale simulations of national railway systems are becoming available on a highly detailed scale. Without this understanding, efficient management of delay propagation, a growing concern in some Western countries, will remain impossible. Here, we present a systemic risk-based approach to manage daily delay cascading on national scales. We compute the {\em systemic impact} of every train as the maximum of all delays it could possibly cause due to its interactions with other trains, infrastructure, and operational units. To compute it, we design an effective impact network where nodes are train services and links represent interactions that could cause delays. Our results are not only consistent with highly detailed and computationally intensive agent-based railway simulations but also allow us to pinpoint and identify the causes of delay cascades in detail. The systemic approach reveals structural weaknesses in railway systems whenever shared resources are involved. We use the systemic impact to optimally allocate additional shared resources to the system to reduce delays with minimal costs and effort. The method offers a practical and intuitive solution for delay management by optimizing the effective impact network through the introduction of new cheap local train services.Comment: 27 pages, 14 figure

Capacity assessment of railway infrastructure: Tools, methodologies and policy relevance in the EU context

The transport sector is increasingly faced with several issues related to the rising of traffic demand such as congestion, energy consumption, noise, pollution, safety, etc.. Due to its low external and environmental costs, railway can be considered (together with inland waterways and short-sea-shipping) as a key factor for the sustainable development of a more competitive and resource-efficient transport system (European Commission, White Paper 2011). In order to reinforce the role of rail in European transport , there is a strong need of addressing the efficiency of the system and customers' satisfaction through targeted actions, i.e. rising reliability and quality of service. This becomes particularly pressing as many parts of the existing railway infrastructures are reaching their maximum capacity thus shrinking their capability to provide users and customers a higher or even adequate level of service. Taking also into account that transport demand forecasts for 2030 clearly show a marked increase of rail activity across the whole Europe, we aim to address the issue of rail congestion in the context of relevant policy questions: Is the actual rail Infrastructure really able to absorb forecasted traffic, without significant impacts on punctuality of the system? Would the already planned interventions on the European railway infrastructure guarantee an adequate available capacity and consequently adequate reliability and level of service? To which extent would the coveted competition in an open railway market be influenced by capacity scarcity, mainly during peak hours or along more profitable corridors? An accurate estimation of capacity of the rail network can help answer these questions, leading policy makers to better decisions and helping to minimize costs for users. In this context this report explores the issue of capacity scarcity and sets this issue in the context of other relevant policy issues (track access charges, cost/benefit and accessibility measures, maintenance programmes, freight services’ reliability, external, marginal congestion or scarcity cost for rail, impacts of climate changes, etc.), providing a methodological review of capacity and punctuality assessment procedures. To better explore the real applicability and the time and/or data constraints of each methodology, the study reports some practical applications to the European railway network. Finally in the last section the report discusses the topic from a modelling perspective, as the quantitative estimation of railway capacity constraints is a key issue in order to provide better support to transport policies at EU level.JRC.J.1-Economics of Climate Change, Energy and Transpor

Pilot3 D5.2 - Verification and validation report

The deliverable provides the outcomes from the verification and validation activities carried during the course of work package 5 of the Pilot3 project, and according to the verification and validation plan defined in deliverable D5.1 (Pilot3 Consortium, 2020c). Firstly, it presents the main results of the verification activities performed during the development and testing of the different software versions. Then, this deliverable reports on the results of internal and external validation activities, which aimed to demonstrate the operational benefit of the Pilot3 tool, assessing the research questions and hypothesis that were defined at the beginning of the project. The Agile principle adopted in the project accompanying with the five five-level hierarchy approach on the definition of scenarios and case studies enabled the flexibility and tractability in the selection of experiments through different versions of prototype development. As a result of this iterative development of the tool, some of the research questions initially defined have been revisited to better reflect the validation results. The deliverable also reports the feedback received from the experts during the internal and external meetings, workshops and dedicated (on-line) site visits. During the validation campaign, both subjective qualitative information and objective quantitative data were collected and analysed to assess the Pilot3 tool. The document also summarises the results of the survey that were distributed to the external experts to assess the human-machine interface (HMI) mock-up developed in the project

Engage D3.10 Research and innovation insights

Engage is the SESAR 2020 Knowledge Transfer Network (KTN). It is managed by a consortium of academia and industry, with the support of the SESAR Joint Undertaking. This report highlights future research opportunities for ATM. The basic framework is structured around three research pillars. Each research pillar has a dedicated section in this report. SESAR’s Strategic Research and Innovation Agenda, Digital European Sky is a focal point of comparison. Much of the work is underpinned by the building and successful launch of the Engage wiki, which comprises an interactive research map, an ATM concepts roadmap and a research repository. Extensive lessons learned are presented. Detailed proposals for future research, plus research enablers and platforms are suggested for SESAR 3

Cyber-Physical Embedded Systems with Transient Supervisory Command and Control: A Framework for Validating Safety Response in Automated Collision Avoidance Systems

The ability to design and engineer complex and dynamical Cyber-Physical Systems (CPS) requires a systematic view that requires a definition of level of automation intent for the system. Since CPS covers a diverse range of systemized implementations of smart and intelligent technologies networked within a system of systems (SoS), the terms “smart” and “intelligent” is frequently used in describing systems that perform complex operations with a reduced need of a human-agent. The difference between this research and most papers in publication on CPS is that most other research focuses on the performance of the CPS rather than on the correctness of its design. However, by using both human and machine agency at different levels of automation, or autonomy, the levels of automation have profound implications and affects to the reliability and safety of the CPS. The human-agent and the machine-agent are in a tidal lock of decision-making using both feedforward and feedback information flows in similar processes, where a transient shift within the level of automation when the CPS is operating can have undesired consequences. As CPS systems become more common, and higher levels of autonomy are embedded within them, the relationship between human-agent and machine-agent also becomes more complex, and the testing methodologies for verification and validation of performance and correctness also become more complex and less clear. A framework then is developed to help the practitioner to understand the difficulties and pitfalls of CPS designs and provides guidance to test engineering design of soft computational systems using combinations of modeling, simulation, and prototyping