Susceptibility of optimal train schedules to stochastic disturbances of process times

Larsen, Rune; Pranzo, Marco; D’Ariano, Andrea; Corman, Francesco; Pacciarelli, Dario

doi:10.1007/s10696-013-9172-9

Cited by 62 publications

(43 citation statements)

References 32 publications

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“…Typically, measures are based on punctuality, delays, number of violated connections, or number of trains being on-time to a station (possibly weighted by the number of passengers affected). For example, Büker and Seybold (2012) measure punctuality, mean delay and delay variance, Larsen et al (2013) use secondary and total delays as performance indicators and Medeossi et al (2011) measure the conflict probability. All of the examples above are based on perturbing a timetable with observed or simulated disturbances.…”

Section: Traffic Performance Measuresmentioning

confidence: 99%

Assessment of Robustness in Railway Traffic Timetables

Andersson

2014

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A tendency seen for the last decades in many European railway networks is a growing demand for capacity. An increased number of operating trains has led to a delay sensitive system where it is hard to recover from delays, where even relatively small delays are easily propagating to other traffic.The overall aim of this thesis is to analyse the robustness of railway traffic timetables; why delays are propagating in the network and how the timetable design and dispatching strategies influence the delays. In this context we want to establish quantitative measures of timetable robustness. There is a need for measures that can be used by the timetable constructors. Measures that identify where and how to improve the robustness and thereby indicating how and where margin time should be inserted. It is also important that the measures can capture interdependencies between different trains.In this thesis we introduce the concept of critical points, which is a practical approach to identify robustness weaknesses in a timetable. In contrast to other measures, critical points can be used to identify specific locations in both time and space. The corresponding measure, Robustness in Critical Points (RCP) provides the timetable constructors with concrete suggestions for which trains that should be given more runtime or headway margin. The measure also identifies where the margin time should be allocated to achieve a higher robustness.In a case study we show that the delay propagation is highly related to the operational train dispatching. This study shows that the current prioritisation rule used in Sweden results in an economic inefficiency and therefore should be revised. This statement is further supported by RCP and the importance of giving the train dispatchers more flexibility to efficiently solve conflict situations.

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Section: Traffic Performance Measuresmentioning

confidence: 99%

Assessment of Robustness in Railway Traffic Timetables

Andersson

2014

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“…By contrast, micro-simulation approaches are better able to take into account the stochasticity of the analysed phenomenon which lies in several factors: the temporal and spatial distribution of passengers, passenger and train driver behaviours, and train delays. Stochastic variations in dwell time are taken into account in [19], while [20] addressed the problem by determining dwell times by separating them into both deterministic and stochastic sub-processes.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2017

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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.

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“…Generally, it is presented in the form of average delay (Khan and Zhou [11], Fischetti et al [9], Kroon et al [14], and Vromans et al [20]), secondary and total delay (Larsen et al [15]), punctuality (Andersson et al [3]), and the number of affected passengers (Dewilde et al [8]). However, the importance of the ex-ante measures cannot be denied because the traffic performance is based on the design quality of the timetable.…”

Section: Introductionmentioning

confidence: 99%

Ex-ante robustness measures for single track train timetables

2017

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Preliminary communicationThe goal of the paper is to propose a measurement to quantify and improve the robustness of the train timetables at the design stage. The paper presents the modeling and application of an ex-ante robustness measure for single track railways, known as the Critical Robustness Measure (CRM). Efficiency of the CRM is demonstrated by comparing the technique with the available ex-ante robustness measures, e.g., the number of trains per hour per section, the total amount of runtime margin for each individual train, sum of shortest headway reciprocals, weighted average distance, marginal runtime difference, robustness at the critical points, and margins along the longest path. Numerical experiment sare conducted on a hypothetical example and a selected single track segment of the Pakistan Railways. Computational results reveal that it is not useful to add the time margins to all activites (e.g., running times, headways) in the timetable because not all components of margins are effective for the robustness of a timetable. Furthermore, the robustness is not statically quantifiable, since it may change with time and be associated with the way of the train's interactions. Keywords: critical points; ex-ante measures; robustness measurement; train timetableEx-ante mjere dugotrajnosti za vozne redove jednokolosiječne željezničke pruge Prethodno priopećenje Cilj je ovoga rada predložiti mjerenje u svrhu kvantificiranja i poboljšanja dugotrajnosti voznih redova već kod izrade. U radu se predstavlja modeliranje i primjena ex-ante mjere dugotrajnosti za vozne jednokolosiječne željezničke pruge, poznate kao Critical Robustness Measure (CRM). Učinkovitost te mjere demonstrira se usporedbom te metode s dostupnim ex-ante mjerama izdržljivosti, tj. brojem vlakova po satu po dionici, ukupnim iznosom granice vremena vožnje za svaki pojedinačni vlak, zbirom najkraćih uzajamnih vemenskih intervala između dva vlaka, ponderiranim prosjekom udaljenosti, marginalnom razlikom u vremenu vožnje, izdržljivosti u kritičnim točkama, i granicama vremena vožnje na najdužoj stazi. Numerički eksperimenti provedeni su na hipotetičkom primjeru i izabranom dijelu jednokolosiječne pruge na pakistanskim željeznicama. Rezultati proračuna pokazuju da nije korisno dodati vremenska ograničenja kod svih aktivnosti (na pr. vrijeme vožnje, vremenski razmak između dva vlaka) u voznom redu jer nisu sve komponente uključene u granicu vremena vožnje korisne za dugotrajnost nekog voznog reda. Nadalje, ta se dugotrajnost ne može statistički kvantificirati budući da se tijekom vremena može promijeniti i povezati s načinom interakcija između vlakova. Ključne riječi: ex-ante mjere; kritične točke; mjerenje dugotrajnosti (izdržljivosti); vozni red vlaka

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Susceptibility of optimal train schedules to stochastic disturbances of process times

Cited by 62 publications

References 32 publications

Assessment of Robustness in Railway Traffic Timetables

Assessment of Robustness in Railway Traffic Timetables

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

Ex-ante robustness measures for single track train timetables

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