Passenger Behavior Simulation in Congested Urban Rail Transit System: A Capacity-Limited Optimal Strategy Model for Passenger Assignment

Optimal strategy, one of the main transit assignment models, can better demonstrate the flexibility for passengers using routes in a transit network. According to the basic optimal strategy model, passengers can board trains based on their frequency without any capacity limitation. In the metropolitan cities such as Beijing, Shanghai, and Hong Kong, morning commuters face huge transit problems. Especially for the metro system, there is heavy rush in metro stations. Owing to the limited train capacity, some passengers cannot board the first coming train and need to wait for the next one. To better demonstrate the behavior of passengers pertaining to the limited train capacity, we consider capacity constraints for the basic optimal strategy model to represent the real situation. We have proposed a simulation-based algorithm to solve the model and apply it to the Beijing Subway to demonstrate the feasibility of the model. The application of the proposed approach has been demonstrated using the computational results for transit networks originating from practice.

Vulnerability Analysis of Urban Rail Transit Network by Considering the Station Track Layout and Passenger Behavior

The vulnerability of an urban rail transit (URT) network is an index that reflects its ability to cope with risks. However, existing URT network vulnerability studies have paid less attention to station track layout and passenger choice behavior, both of which significantly affect the consequences of a disruption incident. In the present study, we first analyze an actual scenario of URT section disruption and passenger behavior during an incident. Then, we propose two section vulnerability indexes that quantitatively evaluate the effect of a URT section disruption from two aspects: detour delay and loss in passenger flow. To make the application scenario of this method more realistic, the track layout and depot location are taken into account. By considering the relationship between train routing and the sections, a concept of “dominant section” is put forward to make the calculation of the vulnerability indexes more efficient and can be used for a simultaneous multi-section-disruption scenario. Finally, a case study of the Beijing Subway network is provided. The results show that disruptions in only a few critical sections can significantly affect the URT network passenger flow. Disruption of only 3% of the sections can lead to 80% passenger-flow loss, which reflects the high vulnerability of URT networks. The method proposed in this paper can provide support for the evaluation of URT network performance.

Review of Transit Data Sources: Potentials, Challenges and Complementarity

Public transport has become one of the major transport options, especially when it comes to reducing motorized individual transport and achieving sustainability while reducing emissions, noise and so on. The use of public transport data has evolved and rapidly improved over the past decades. Indeed, the availability of data from different sources, coupled with advances in analytical and predictive approaches, has contributed to increased attention being paid to the exploitation of available data to improve public transport service. In this paper, we review the current state of the art of public transport data sources. More precisely, we summarize and analyze the potential and challenges of the main data sources. In addition, we show the complementary aspects of these data sources and how to merge them to broaden their contributions and face their challenges. This is complemented by an information management framework to enhance the use of data sources. Specifically, we seek to bridge the gap between traditional data sources and recent ones, present a unified overview of them and show how they can all leverage recent advances in data-driven methods and how they can help achieve a balance between transit service and passenger behavior.

Roadmap to Early Implementation of Passenger Air Mobility: Findings from a Delphi Study

Urban air mobility (UAM) has recently increased in popularity as an emerging mode of transportation, covering a wide range of applications, for on-demand or scheduled operations of smaller aircraft, in and around metropolitan areas. Due to its novelty and as it has not yet been implemented, UAM research still faces uncertainties. In particular, there is a need to develop a roadmap for the early implementation of passenger air mobility, aiming to identify the most prominent challenges, opportunities, hazards, and risks, but also to highlight the most promising use cases, or on the contrary, the ones associated with the least benefits compared to the risks or complexity they entail. To answer the previous questions, and therefore address this research gap, this study used a two-round Delphi questionnaire, targeting various stakeholder groups (product owners, policymakers, researchers, consultants, investors), leading to a total of 51 experts, out of which 34 also participated in the second round. In the first round, the main challenges, opportunities, and hazards facing the implementation of passenger UAM were identified. Findings on challenges and opportunities that were dependent on use cases only (as opposed to being dependent on technology or external factors) were then fed back into the second round, which helped evaluate the use cases based both on their complexities, as well as the associated benefits. Accordingly, medical/emergency was identified as the best use case and intracity transport as the worst (in terms of complexity vs. benefits). Similarly, a risk analysis evaluated the potential hazards associated with the implementation of UAM and their impacts on the system viability. Community backlash was found to be the most hazardous one, while malicious passenger behavior and improperly designed infrastructure as the least. Findings from this study can help better understand stakeholders’ opinions, highlighting promising use cases, but also risks to be aware of, constituting therefore a roadmap for future implementation.

Departure Time Choice in Schedule-Based Transit Assignment

This paper investigates existing departure time models for a schedule-based transit assignment and their parametrization. It analyzes the impact of the temporal resolution of travel demand and suggests functions for evaluating the adaptation time as part of the utility of a path. The adaptation time quantifies the time between the preferred and the scheduled departure times. The findings of the analysis suggested that travel demand should be discretized into intervals of 1 min, with interval borders right between the full minute, that is, ±0.5 min. It was shown that longer time intervals led to arbitrary run volumes, even for origin–destination pairs with just one transit line and a fixed headway. Although a linear relationship between adaptation time and adaptation disutility is a common assumption in several publications, it cannot represent certain types of passenger behavior. For some trip purposes, passengers may be insensitive to small adaptation times, but highly sensitive to large adaptations. This requires a nonlinear evaluation function.

What Causes Changes in Passenger Behavior in South-East Europe during the COVID-19 Pandemic?

The appearance of the COVID-19 virus in Europe, at the beginning of 2020, brought many challenges and changes to society. These changes affected the behavior, desires, and needs of passengers in vehicles. The change in passenger behavior has contributed to the more difficult organization of passenger transport and traffic management. For these reasons, in the countries of South-East Europe (Serbia, Montenegro, Slovenia, Bosnia and Herzegovina, Greece, the Republic of Northern Macedonia and Croatia), this survey was conducted in order to examine which demographic characteristics of respondents (age, gender, residence, education, and health) influence choice of transport, with the aim to optimize the transport system in times of crisis in this region. 786 respondents participated in the research. The results showed that the acceptability of vehicle occupancy most often differs with respect to age, education, and health conditions of the respondents. The obtained results will greatly help the organizers of public transport and the transport system in the region, since based on these results they can have an insight into the demographic factors that influence the choice of transport mode during a crisis.