Dispatching and Rescheduling Tasks and Their Interactions with Travel Demand and the Energy Domain: Models and Algorithms

Abstract The paper aims to provide an overview of the key factors to consider when performing reliable modelling of rail services. Given our underlying belief that to build a robust simulation environment a rail service cannot be considered an isolated system, also the connected systems, which influence and, in turn, are influenced by such services, must be properly modelled. For this purpose, an extensive overview of the rail simulation and optimisation models proposed in the literature is first provided. Rail simulation models are classified according to the level of detail implemented (microscopic, mesoscopic and macroscopic), the variables involved (deterministic and stochastic) and the processing techniques adopted (synchronous and asynchronous). By contrast, within rail optimisation models, both planning (timetabling) and management (rescheduling) phases are discussed. The main issues concerning the interaction of rail services with travel demand flows and the energy domain are also described. Finally, in an attempt to provide a comprehensive framework an overview of the main metaheuristic resolution techniques used in the planning and management phases is shown

Modelling of interactions between rail service and travel demand: a passenger-oriented analysis

The proposed research is situated in the field of design, management and optimisation in railway network operations. Rail transport has in its favour several specific features which make it a key factor in public transport management, above all in high-density contexts. Indeed, such a system is environmentally friendly (reduced pollutant emissions), high-performing (high travel speeds and low values of headways), competitive (low unitary costs per seat-km or carried passenger-km) and presents a high degree of adaptability to intermodality. However, it manifests high vulnerability in the case of breakdowns. This occurs because a faulty convoy cannot be easily overtaken and, sometimes, cannot be easily removed from the line, especially in the case of isolated systems (i.e. systems which are not integrated into an effective network) or when a breakdown occurs on open tracks. Thus, re-establishing ordinary operational conditions may require excessive amounts of time and, as a consequence, an inevitable increase in inconvenience (user generalised cost) for passengers, who might decide to abandon the system or, if already on board, to exclude the railway system from their choice set for the future. It follows that developing appropriate techniques and decision support tools for optimising rail system management, both in ordinary and disruption conditions, would consent a clear influence of the modal split in favour of public transport and, therefore, encourage an important reduction in the externalities caused by the use of private transport, such as air and noise pollution, traffic congestion and accidents, bringing clear benefits to the quality of life for both transport users and non-users (i.e. individuals who are not system users). Managing to model such a complex context, based on numerous interactions among the various components (i.e. infrastructure, signalling system, rolling stock and timetables) is no mean feat. Moreover, in many cases, a fundamental element, which is the inclusion of the modelling of travel demand features in the simulation of railway operations, is neglected. Railway transport, just as any other transport system, is not finalised to itself, but its task is to move people or goods around, and, therefore, a realistic and accurate cost-benefit analysis cannot ignore involved flows features. In particular, considering travel demand into the analysis framework presents a two-sided effect. Primarily, it leads to introduce elements such as convoy capacity constraints and the assessment of dwell times as flow-dependent factors which make the simulation as close as possible to the reality. Specifically, the former allows to take into account the eventuality that not all passengers can board the first arriving train, but only a part of them, due to overcrowded conditions, with a consequent increase in waiting times. Due consideration of this factor is fundamental because, if it were to be repeated, it would make a further contribution to passengers’ discontent. While, as regards the estimate of dwell times on the basis of flows, it becomes fundamental in the planning phase. In fact, estimating dwell times as fixed values, ideally equal for all runs and all stations, can induce differences between actual and planned operations, with a subsequent deterioration in system performance. Thus, neglecting these aspects, above all in crowded contexts, would render the simulation distorted, both in terms of costs and benefits. The second aspect, on the other hand, concerns the correct assessment of effects of the strategies put in place, both in planning phases (strategic decisions such as the realisation of a new infrastructure, the improvement of the current signalling system or the purchasing of new rolling stock) and in operational phases (operational decisions such as the definition of intervention strategies for addressing disruption conditions). In fact, in the management of failures, to date, there are operational procedures which are based on hypothetical times for re-establishing ordinary conditions, estimated by the train driver or by the staff of the operation centre, who, generally, tend to minimise the impact exclusively from the company’s point of view (minimisation of operational costs), rather than from the standpoint of passengers. Additionally, in the definition of intervention strategies, passenger flow and its variation in time (different temporal intervals) and space (different points in the railway network) are rarely considered. It appears obvious, therefore, how the proposed re-examination of the dispatching and rescheduling tasks in a passenger-orientated perspective, should be accompanied by the development of estimation and forecasting techniques for travel demand, aimed at correctly taking into account the peculiarities of the railway system; as well as by the generation of ad-hoc tools designed to simulate the behaviour of passengers in the various phases of the trip (turnstile access, transfer from the turnstiles to the platform, waiting on platform, boarding and alighting process, etc.). The latest workstream in this present study concerns the analysis of the energy problems associated to rail transport. This is closely linked to what has so far been described. Indeed, in order to implement proper energy saving policies, it is, above all, necessary to obtain a reliable estimate of the involved operational times (recovery times, inversion times, buffer times, etc.). Moreover, as the adoption of eco-driving strategies generates an increase in passenger travel times, with everything that this involves, it is important to investigate the trade-off between energy efficiency and increase in user generalised costs. Within this framework, the present study aims at providing a DSS (Decision Support System) for all phases of planning and management of rail transport systems, from that of timetabling to dispatching and rescheduling, also considering space-time travel demand variability as well as the definition of suitable energy-saving policies, by adopting a passenger-orientated perspective

Defining Reserve Times for Metro Systems: An Analytical Approach

The aim of this paper is to provide an analytical approach for determining operational parameters for metro systems so as to support the planning and implementation of energy-saving strategies. Indeed, one of the main targets of train operating companies is to identify and implement suitable strategies for reducing energy consumption. For this purpose, researchers and practitioners have developed energy-efficient driving profiles with the aim of optimising train motion. However, as such profiles generally entail an increase in travel times, the operating parameters in the planned timetable need to be appropriately recalibrated. Against this background, this paper develops a suitable methodology for estimating reserve times which represent the main rate of extra time needed to put ecodriving strategies in place. Our proposal is to exploit layover times (i.e., times spent by a train at the terminus waiting for the next trip) for energy-saving purposes, keeping buffer times intact in order to preserve the flexibility and robustness of the timetable in case of delays. In order to show its feasibility, the approach was applied in the case of a real metro context, whose service frequency was duly taken into account. In particular, after stochastic analysis of the parameters involved for calibrating suitable buffer times, different operating schemes were simulated by analysing the relationship between layover times, number of convoys, and feasible headway values. Finally, some operation configurations are analysed in order to quantify the amount of energy that can be saved

Methodology for Determining Dwell Times Consistent with Passenger Flows in the Case of Metro Services

Abstract The importance of a mobility system based on railway technology as the backbone of public transport is now widely acknowledged. Indeed, rail systems are green, high performing, smart and able to ensure a high degree of safety. Therefore, modal split should be steered towards rail transport by increasing the attractiveness of this transport mode. In this context, a key element is represented by the timetabling design phase, which must aim to guarantee an appropriate degree of robustness of rail operations in order to ensure a high degree of system reliability and increase service quality. A crucial factor in the task of timetabling entails evaluating dwell times at stations. The innovative feature of this paper is the analytical definition of dwell times as flow dependent. Our proposal is based on estimating dwell times according to the crowding level at platforms and related interaction between passengers and the rail service in terms of user behaviour when a train arrives. An application in the case of a real metro system is provided in order to show the feasibility of the proposed approach

Assessing the sustainability of the city-port transformations: Multi-Criteria Decision Analysis (MCDA) for alternatives portfolio selection.

In recent years, the EU has sought to define sustainable transition pathways towards more equitable, prosperous, and inclusive urban and territorial models, capable of responding to the rapid degradation of ecosystems, and improving quality of life of citizens. In this context, ports have been recognised as key strategic hubs not only for economic and logistical competitiveness, but also to generate employment and investment opportunities, and to address the challenges of the climate change. The research presents a multi-scale, multi-dimensional and multi- group methodological framework to support decision-making processes related to the development of sustainable transformations of port cities, capturing the complexity of interactions and conflicts. Integrating Multi-Criteria Decision Analysis (MCDA) approaches and Problem Structuring Methods (PSM), the proposed methodology aims to address the following gaps identified in the literature: (i) a scattered application of multi-group methods; (ii) the lack of social instances within the decision problem; (iii) a weak sustainability perspective; (iv) the use of one-dimensional scale assessment in sectoral studies. The case study of the city-port of Gela in Sicily (Italy) provided an opportunity to test the proposed methodology and to integrate multi-dimensional sustainability issues into feasibility studies, promoting a more balanced relationship between city and port. The interdependencies between environment, society and economy allowed MCDA to be identified as a suitable approach to address complex decision-making and support the sustainability assessment of port areas transformation. Two multi-criteria and multi-group evaluation methods guided the decision-making process to select a portfolio of preferred alternatives by assessing technical, environmental, and economic impacts and analysing stakeholder conflicts and coalitions. The process was carried out as follows: on the one hand, a multidimensional impact matrix integrating Key Performance Indicators (KPIs) divided into technical, financial-economic, and environmental categories through the application of the multi-criteria method EVAMIX; on the other hand, a social assessment with a dendrogram of coalitions derived from the application of the multi-group method NAIADE by modelling stakeholders’ preferences regarding a portfolio of alternatives related to the decision problem

A methodology for long-term analysis of innovative signalling systems on regional rail lines

A rail system may be considered a useful tool for reducing vehicular flows on a road system (i.e. cars and trucks), especially in high-density contexts such as urban and metropolitan areas where greenhouse gas emissions need to be abated. In particular, since travellers maximise their own utility, variations in mobility choices can be induced only by significantly improving the level-of-service of public transport. Our specific proposal is to identify the economic and environmental effects of implementing an innovative signalling system (which would reduce passenger waiting times) by performing a cost-benefit analysis based on a feasibility threshold approach. Hence, it is necessary to calculate long-term benefits and compare them with intervention costs. In this context, a key factor to be considered is travel demand estimation in current and future conditions. This approach was tested on a regional rail line in southern Italy to show the feasibility and utility of the proposed methodology

An analytical approach for determining reserve times on metro systems

In recent years the growing interest in environmental issues has prompted researchers to investigate two main areas in the field of rail systems: how to improve performance in order to attract users from other transport modes with greater environmental impacts (such as private cars) and how to reduce energy consumption. On the latter issue, some procedures have been developed for determining suitable ‘green’ driving profiles which are, however, subject to greater travel times. Since precise quantification is critically important, in this paper we propose an approach to determining all operational times analytically, including reserve times. Finally, the methodology is applied in the case of a real metro line for validating the proposal

An analytical methodology for extending passenger counts in a metro system

The planning of a rail system requires the definition of travel demand in terms of passengers (or freight) flows for sizing physical and technological elements (such as number of trains, signalling system type, length and width of platforms). Moreover, once a system has been set up and functional elements have been acquired, system management in terms of services and related timetables requires knowledge of travel demand flows. Much has been written about the methods and techniques for estimating travel demand by means of analytical models (calibrated by surveys), statistical processing of survey data and/or correcting model results by using properly collected traffic counts. However, whatever the adopted approach, it is necessary to proceed with survey campaigns to acquire experimental data. Obviously, the greater the number of detected data (and related acquisition costs and times), the greater the accuracy of travel demand estimations. Hence, in real cases, a fair compromise between survey costs and estimation accuracy has to be struck. In this context, we propose an analytical methodology for identifying space-time relations between passenger counts to reduce the amount of data to be surveyed without affecting estimation accuracy. In particular, our proposal is based on defining analytical functions to provide boarding and alighting flows depending on the station (space component) and the time period (time component) in question. Finally, in order to show the feasibility of the proposed methodology and related improvements with respect to traditional approaches, we applied our proposal to the case of a real metro line in Naples (Italy) by comparing different levels of detail in passenger surveys

A methodological approach for managing rail disruptions with different perspectives

Public transport systems represent a potentially effective tool for managing mobility in urban and metropolitan areas. In particular, especially in high density contexts, rail systems can be adopted as the backbone of transportation services. However, rail systems are also somewhat vulnerable to system failure since, for instance, a faulty train cannot be easily removed or overtaken. Hence, our proposal is to develop an off-line procedure based on a microsimulation approach for analysing the most frequent breakdown conditions and suggesting the adoption of optimal intervention strategies. Finally, different perspectives (i.e. requirements of passengers and rail operators) are proposed and applied in the case of a real metro line in the south of Italy

Preliminary results on different perspectives in managing rail disruptions

Rail systems represent a useful tool for reducing the use of private cars especially in urban and metropolitan areas. However, since a faulty train cannot be easily removed or overtaken, in the case of rail system failures, restoring operative conditions could take a very long time and result in considerable delays for passengers. In this context, our proposal is to provide rail systems managers (i.e. dispatchers) with an off-line procedure which adopts a microsimulation approach for analysing the most frequent breakdown conditions and suggests in advance the optimal intervention strategies to adopt. In particular, different perspectives are proposed and applied in the case of a real metro line in the south of Italy