Traveller behaviour in public transport in the early stages of the COVID-19 pandemic in the Netherlands

The impact of subway car interior design on passenger evacuation and boarding/alighting efficiency

This study investigated the impact of subway car interior design on passenger evacuation and boarding/alighting efficiency. The usability of pedestrian agent models was verified through real-life experiments. A seven-factor orthogonal simulation experiment was designed, using key geometric features of the subway car interior as variables. The results of the computer simulation showed that the impact of subway car interior design factors on evacuation and boarding/alighting time was not entirely consistent, with seat layout and door width being the most important factors affecting passenger movement. In the evacuation scenario, only the connectivity of the subway car has no effect on evacuation time, while in the boarding and alighting scenario, seat layout, car type, door width, and foyer width all significantly affect boarding and alighting time. Multivariate regression models were established to predict evacuation and boarding/alighting times through design features, which can explain 86.7% and 58.9% of the time variation, respectively. The research results were used to guide subway car design, and the proposed new scheme demonstrated better performance.

Quantifying the impact of COVID-19 on travel behavior in different socio-economic segments

The COVID-19 pandemic has resulted in substantial negative impacts on social equity. To investigate transport inequities in communities with varying medical resources and COVID controlling measures during the COVID pandemic and to develop transport-related policies for the post-COVID-19 world, it is necessary to evaluate how the pandemic has affected travel behavior patterns in different socio-economic segments (SES). We first analyze the travel behavior change percentage due to COVID, e.g., increased working from home (WFH), decreased in-person shopping trips, decreased public transit trips, and canceled overnight trips of individuals with varying age, gender, education levels, and household income, based on the most recent US Household Pulse Survey census data during Aug 2020 ∼ Dec 2021. We then quantify the impact of COVID-19 on travel behavior of different socio-economic segments, using integrated mobile device location data in the USA over the period 1 Jan 2020-20 Apr 2021. Fixed-effect panel regression models are proposed to statistically estimate the impact of COVID monitoring measures and medical resources on travel behavior such as nonwork/work trips, travel miles, out-of-state trips, and the incidence of WFH for low SES and high SES. We find that as exposure to COVID increases, the number of trips, traveling miles, and overnight trips started to bounce back to pre-COVID levels, while the incidence of WFH remained relatively stable and did not tend to return to pre-COVID level. We find that the increase in new COVID cases has a significant impact on the number of work trips in the low SES but has little impact on the number of work trips in the high SES. We find that the fewer medical resources there are, the fewer mobility behavior changes that individuals in the low SES will undertake. The findings have implications for understanding the heterogeneous mobility response of individuals in different SES to various COVID waves and thus provide insights into the equitable transport governance and resiliency of the transport system in the "post-COVID" era.

Curbing vehicular urban pollution in China: Investigating the usage intentionof public electric buses

Public electric bus (PEB) usage remains critical in reducing carbon emissions, traffic congestion, energy consumption, resource exhaustion, and environmental pollution. PEB usage revolves around consumer acceptance, and assessing the psychological factors accounting for using PEBs is essential in mitigating these challenges for a sustainable environment. The study extends the reasoned action theory (TRA) with environmental awareness, convenience, and personal norms in investigating residents' intention to use electric buses in Nanjing, China. 405 responses were gathered through an online survey and evaluated using Structural Equation Modeling (SEM). Statistical analysis showed that the structural model (66.4%) explained public electric bus use better than the original TRA model (20.7%). Attitude, subjective norms, personal norms, environmental awareness, and convenience directly influenced the intention to use PEBs. Personal norms related to attitude positively. Environmental awareness related to personal norms in PEB use. Subjective norms partially mediated the impact of personal norms on the intention to use PEBs. Convenience moderated the interaction between personal norms and intention to use PEBs. Respondents differed in income level, educational level, and employment but not gender in their inclinations to use PEBs. The current study recommends potent policy implications to enhance and ensure the maximum use of PEBs.

Modelling pandemic behaviour using an economic multiplayer game

During a pandemic, isolating oneself from the community limits viral transmission and helps avoid repeated societal lockdowns. This entails a social dilemma—either distance oneself from others for the benefit of the public good or free-ride and enjoy the benefits of freedom. It is not yet understood how the unfamiliar incentive structure and interpersonal context presented by a pandemic together modulate individuals’ approach to this social dilemma. In this preregistered study, we take a game-theoretical approach and investigate people’s decisions to self-isolate, using a novel iterated multiplayer game designed to capture the decision-making environment in the pandemic. To elucidate players’ thinking, we use a variation of the strategy method and elicit beliefs about how much others will self-isolate. Players tend to respond to social norms with abidance, rather than transgression; they resist the temptation to freeride when others are self-isolating. However, they deal with exponential growth poorly, as they only self-isolate sufficiently when lockdowns are imminent. Further, increased collective risk can motivate more self-isolation, even though the link between self-isolation and lockdowns is stochastic. Players underreport the influence of others’ choices on their own, and underestimate others’ self-isolation. We discuss implications for public health, and communication to the public.

Has COVID-19 changed our loyalty towards public transport? Understanding the moderating role of the pandemic in the relationship between service quality, customer satisfaction and loyalty

COVID-19 has been associated with a decline in public transport ridership in many cities. However, the impact of the pandemic on passenger perceptions of public transport, particularly loyalty, has remained largely unexplored. Using a case study of Tehran's bus system, this paper aims to assess the moderating effect of COVID-19 on passenger loyalty. A cross-sectional survey of bus users was conducted in two similar periods, before and during COVID-19. The data was analysed using structural equation modelling, with the effect of observed heterogeneity evaluated using multiple indicators multiple causes models and multi-group analysis. The results indicate that during COVID-19, perceptions of service quality have improved, particularly in relation to comfort (including crowding), safety, reliability and information. While this has led to increased customer satisfaction, loyalty to the system has decreased. An increase in the perceived attractiveness of using private cars was found to be the primary factor for reducing passenger loyalty with the perceived monetary and psychological costs of using cars being less effective in encouraging people to use the bus. Taking into account the significant utility of private vehicles in urban transportation during COVID-19, the present study identifies feasible areas for improving the performance of bus services to increase satisfaction with this form of public transport among car owners.

Preferences for using the London Underground during the COVID-19 pandemic

The COVID-19 pandemic has drastically impacted people's travel behaviour and introduced uncertainty in the demand for public transport. To investigate user preferences for travel by London Underground during the pandemic, we conducted a stated choice experiment among its pre-pandemic users (N = 961). We analysed the collected data using multinomial and latent class logit models. Our discrete choice analysis provides two sets of results. First, we derive the crowding multiplier estimate of travel time valuation (i.e., the ratio of the value of travel time in uncrowded and crowded situations) for London underground users. The results indicate that travel time valuation of Underground users increases by 73% when it operates at technical capacity. Second, we estimate the sensitivity of the preference for the London Underground relative to the epidemic situation (confirmed new COVID-19 cases) and interventions (vaccination rates and mandatory face masks). The sensitivity analysis suggests that making face masks mandatory is a main driver for recovering the demand for the London underground. The latent class model reveals substantial preference heterogeneity. For instance, while the average effect of mandatory face masks is positive, the preferences of 30% of pre-pandemic users for travel by the Underground are negatively affected. The positive effect of mandatory face masks on the likelihood of taking the Underground is less pronounced among males with age below 40 years, and a monthly income below 10,000 GBP. The estimated preference sensitivities and crowding multipliers are relevant for supply-demand management in transit systems and the calibration of advanced epidemiological models.

Role of latent factors and public policies in travel decisions under COVID-19 pandemic: Findings of a hybrid choice model

Policy measures to control the spread of COVID-19 imposed by different countries have a devastating impact on people's travel behaviors. Differing from the normal situation where general concerns on travel time and cost determine the travel choices, the uncertainty underlying behavior change in the case of a pandemic might be largely attributed to the latent aspects, i.e., social responsibility, risk perception, attitudes, which could diminish the effects of main attributes on travel decisions. Therefore, this paper examines the effects of COVID-19 related policies on individuals' travel choices influenced by the latent aspects. A stated choice experiment was designed to collect people's responses under policy measures to various transportation modes. Results of a hybrid choice model show that COVID-19 related policies significantly affect individuals' transportation mode choice decisions during pandemic situations. The attributes, like travel time and travel cost, which significantly impact travel behavior in normal situations, become less relevant. Moreover, the travel preferences during the pandemic are significantly associated with latent factors of social responsibility, fear of infection, perceived risk, and travel anxiety. In general, public transportation is identified as an insecure alternative compared with other private modes, and people who are more socially responsible tend to travel less during the pandemic. Outcomes of this study could be of value to policymakers and public health emergencies, e.g., government authorities to utilize such knowledge in providing social support for these COVID-19 countermeasures and designing customized policies for specific population groups.