This special issue originated with the organisation of the 6th International Symposium on Transportation Network Reliability (INSTR), which was held in August 2015 in Nara, Japan. The INSTR series is the premier gathering of the world’s leading researchers and professionals interested in transportation network reliability, where they discuss both recent research and future directions in this increasingly important field of research. This special issue includes five papers on the state of the art in research dealing with transport dynamics of disruptions, with a focus on public transportation reliability. Although most of these papers are drawn from those presented at the INSTR 2015 symposium, an open call for papers was also made which attracted several submissions. All submitted papers were rigorously reviewed to ensure the quality and correctness of their content
In the first paper, by O. Cats and E. Jenelius investigate the impacts of a range of public transport network performance. They introduce the idea of a vulnerability curve and related metrics to investigate the relationship between network performance and the degradation of line or link capacities. The impacts of capacity reductions are assessed using a non-equilibrium dynamic public transport operations and assignment model. The proposed method is applied to a full-scan analysis of planned temporary line-level capacity reductions and an analysis of unplanned link-level capacity reductions on the most central segments in the multi-modal rapid public transport network of Stockholm. The results of the case study suggest that policy-makers and service operators should devote disproportional attention to major capacity reductions in case of planned line disruptions in the study network.
In the second paper, by Lu and Dong propose a method to estimate travel times based on data collected from roadside radar sensors, considering car-following behaviour and spatially correlated traffic conditions. The proposed travel time estimation model can well capture the temporal pattern of travel time and its distribution. The paper concentrates on the analyses of link-level travel times based on spatio-temporal radar data and the random variable distribution approach, where the fits of various probability density functions are sought. Travel time estimations from radar data are mapped to relevant distributions and are correlated with probe data. Based on the results, as route travel time reliabilities derived from link-level distributions, it is concluded that the proposed model outperforms probe data in terms of mapping travel time patterns and approximating their distributions.
The third paper, by Nosedal-Sanchez and Piaera, addresses a causal analysis of the airport turnaround processes, which is a key factor to enhance the air traffic management reliability. Cause–effect relationship analysis demands for a knowledge representation technique that considers the stochastic, dynamic and synchronous nature of the turnaround process, and allows representing both the structure and the different ways in which the sub-processes can be influenced. It is important that the causal analysis of the different perturbations has been measured in order to provide insights for better design of policies and strategies for a robust and efficient turnaround that could mitigates undesirable dynamics or at least detect them in advance and enhance the robustness of the turnaround and their related processes and actors performance with direct and indirect impact on ATM system reliability
The fourth paper in this special issue, by Xiong at el., develops an agent-based approach to modelling travel behaviour under uncertainty and information provision, motivated by the aforementioned theoretical and practical issues that arise in a simulation-based approach. The methodology of this paper improves the behavioural foundation embedded in the models used to analyse information provision. Utility-maximizing agents are replaced by artificially intelligent agents who can acquire information, learn and update knowledge, search, and make decisions. With this model, routing algorithms used in DTA models is replaced and (dynamic) user equilibrium condition is replaced by behavioural equilibrium.
The fifth paper, by Sun and Schmöcker, focuses on considering passenger choices and overtaking in the bus bunching problem. The characteristics of this research deal with the passenger behaviour when there is more than one bus serving the stop, focusing on their choices and possible switching actions from the queue of the bus they are waiting to board. They evaluate the resulting service regularity given an initial disturbance to an early bus at one of the first stops along a corridor. For this they obtain the standard deviation and maximum headways between two bus departures.
The five papers included in this special issue provide comprehensive coverage of the landscape of research and development and recent advances in the area of transport network reliability. The guest editors would like to express their sincere gratitude to Prof. Hong K. Lo and Prof. Agachai Sumalee, co-editor in chief of Transportmetrica B: Transport Science for providing an opportunity for this special issue to be disseminated in this journal. The guest editors also would like to thank all of the authors, reviewers and participants of INSTR 2015 for their invaluable contributions to this special issue.