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This paper discusses the dual role of the transport sector in the Covid-19 pandemic: spreading the virus around the world and being most negatively impacted by the pandemic. This paper describes and analyzes the following: (a) actions taken by the governments and international community in order to control the spreading and to alleviate negative economic impacts including massive fiscal and monetary stimulus funding; (b) detailed discussions on the impacts of the pandemic on air transport, rail and bus transport, and urban transit, and major countries' responses to reduce the negative effects; (c) discussions on the positive effects of the pandemic on the environment and climate change by suggesting policy measures in order to make it sustainable over the long term. Finally, the paper addresses social acceptance issue of the behavioral changes necessary in the post-pandemic world, in particular reflecting historical experience of the Spanish flu case. We end the paper with some observations and discussion of the normative issues for a sustainable development of the transport sector. • The impacts of three Covid-19 waves on the world economies have enforced many countries to start large stimulus packages. • The negative impacts on transportation activities are severe for aviation, rail and public transit. • Car travel is on the way of recovering while biking rides are increasing and parcel services are booming. • It will be difficult for mass transport modes to return to previous Covid growth paths because of reduced confidence of passengers. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease 2019 (COVID-19) crisis has influenced economies and societies across the globe and will thoroughly reshape our world as it continues to unfold. The pandemic is likely to trigger permanent long-term impacts on the transport sector in the post-COVID world. While a post-COVID "new normal" will be likely to incur negative consequences, it may provide an opportunity to move toward a more sustainable transport sector. This paper is aimed at developing an urban economic model with an energy focus to depict the dynamics of travel demand, energy consumption, and emissions in the post-COVID world. A set of scenarios was created according to model assumptions regarding lifestyle changes and policy interventions accompanied by the expected post-COVID new normal, to explore long-term pathways toward a deep decarbonization of the transport sector. Scenario simulations demonstrated that working from home, online shopping, and a bike-friendly infrastructure will contribute to a reduction in energy consumption and CO 2 emissions, whereas a significant shift from bus to car transport and the decreasing use of car-sharing services will adversely affect CO 2 emission reductions. The arrival of the post-COVID world may contribute to an 11% reduction in CO 2 emissions by 2060, while the maximum reduction potential could be as high as 44%. Supporting policies and strategies for encouraging remote work and online shopping as well as for promoting safe public transport, active transport, and carpooling services are needed to strongly decarbonize the transport sector in the post-COVID world. Moreover, population distribution and urban structure may also be influenced by the arrival of the post-COVID new normal, which warrant further attention for urban planning. • An urban economic model that accommodates detailed transport and energy technology representations is presented. • Several scenarios are analyzed to depict decarbonization pathways for the transport sector in the post-COVID world. • The arrival of the post-COVID new normal may contribute to reducing CO 2 emissions by a maximum of 44% by 2060. • The impacts of the oncoming new normal on urban structure deserve more attention. [ABSTRACT FROM AUTHOR]

To design effective policies against COVID-19, there is a need for more evidence-based research. However, associations between actual policies and temporal behavior changes have remained underexplored. To fill this important research gap, a nationwide retrospective life-oriented panel survey on individuals' behavior changes from April to September 2020 was implemented in Japan. Reliability of information sources, risk perceptions, and attitudes toward policymaking were also investigated. Valid data were collected from 2643 respondents residing in different parts of the country. Risks were reported about general infections and public transport use. Attitudes toward policymaking were mainly about policymaking capacity and PASS-LASTING based policy measures. A dynamic structural equation model (DSEM) was developed to quantify dynamic associations between individuals' behavior changes over time and subjective assessments (i.e., attitudes) of policymaking. Survey results revealed that behavior changes are mostly characterized by avoidance behaviors. Modeling estimation results showed a statistically-significant sequential cause-effect relationship between accumulated behavior changes in the past, subjective factors, and the most recent behavior changes. The most recent behavior changes are mostly affected by accumulated behavior changes in the past. Effects of subjective assessments of policymaking on the most recent behavior changes are significant but moderate. Among attitudes toward policymaking, attitudes toward policymaking capacity are more influential than willingness to follow PASS-LASTING based policy measures. High risks of using public transport are found to significantly influence the most recent behavior changes, together with other risk perception factors. Insights into effective COVID-19 policymaking are summarized. [Display omitted] • A nationwide life-oriented panel survey was implemented online in Japan in 2020. • Various behavior changes are mostly characterized by avoidance behaviors in Japan. • Impacts of risk perception during the use of public transport are revealed. • Impacts of policymaking capability on activity-travel behaviors are confirmed. • Impacts of PASS-LASTING policies on activity-travel behaviors are confirmed. [ABSTRACT FROM AUTHOR]

This study attempts to provide scientifically-sound evidence for designing more effective COVID-19 policies in the transport and public health sectors by comparing 418 policy measures (244 are transport measures) taken in different months of 2020 in Australia, Canada, Japan, New Zealand, the UK, and the US. The effectiveness of each policy is measured using nine indicators of infections and mobilities corresponding to three periods (i.e., one week, two weeks, and one month) before and after policy implementation. All policy measures are categorized based on the PASS approach (P: prepare-protect-provide; A: avoid-adjust; S: shift-share; S: substitute-stop). First, policy effectiveness is compared between policies, between countries, and over time. Second, a dynamic Bayesian multilevel generalized structural equation model is developed to represent dynamic cause-effect relationships between policymaking, its influencing factors and its consequences, within a unified research framework. Third, major policy measures in the six countries are compared. Finally, findings for policymakers are summarized and extensively discussed. [Display omitted] • COVID-19 transport-related policymaking in six developed countries are compared. • Effectiveness of 418 PASS-based policy measures are examined by using 27 indicators. • Policy effectiveness is compared between policies, between countries and over time. • A dynamic Bayesian multilevel generalized structural equation model is developed. • Dynamic relationships between policymaking, factors and consequences are revealed. [ABSTRACT FROM AUTHOR]

Travelers often change their behavior in reaction to adverse weather conditions. This paper seeks to conduct an empirical evaluation of both ordered and unordered discrete outcome frameworks for examining the adaptive behavior decisions of intercity travelers and investigate the varying effects of explanatory factors on different alternatives of adaptive behavior during adverse weather. The data from 754 respondents in the Beijing-Tianjin-Hebei urban agglomeration, China are collected by a two-phase survey instrument. To capture the unobserved heterogeneity more effectively, this paper develops three advanced models to investigate the variations in intercity travel behavior during adverse weather. Four alternative adaptive behaviors are determined as outcome variables: maintaining original travel plans, changing only the intercity mode, changing the departure date, and canceling the trip, while potential influencing factors including adverse weather conditions, trip-related characteristics, individual attributes and urban agglomeration attributes are statistically assessed. The results indicate that the unordered models consistently outperform their ordered counterparts, and the incorporation of multilayer heterogeneity enhances the model fit. Furthermore, significant factors and their coefficient values vary across the different adaptive behavior alternatives. Intercity travelers demonstrate a higher probability of changing departure dates or canceling trips during snowy and windy days compared to rainy and foggy days. Trains exhibit higher flexibility and reliability during adverse weather, and access attributes significantly affect intercity travel adaptive behavior. Additionally, the analysis of individual and urban agglomeration attributes uncovers variations in adaptive behavior among individuals and cities. These findings provide profound insights into the complexities and variations of intercity travel behavior during adverse weather, and propose practical strategies to mitigate the detrimental impacts of adverse weather on intercity travelers. • Adaptive behavior of intercity travelers during adverse weather is investigated. • Unordered framework outperforms ordered counterparts in adaptive behavior study. • Multilayer unobserved heterogeneity in the adaptive behavior is accounted for. • The varying effects of explanatory factors on different adaptive alternatives are examined. • Practical strategies are proposed to mitigate negative impacts of adverse weather. [ABSTRACT FROM AUTHOR]

Impacts of coronavirus disease 2019 (COVID-19) on the transport sector and the corresponding policy measures are becoming widely investigated. Considering the various uncertainties and unknowns about this virus and its impacts (especially long-term impacts), it is critical to understand opinions and suggestions from experts within the transport sector and related planning fields. To date, however, there is no study that fills this gap in a comprehensive way. This paper is an executive summary of the findings of the WCTRS COVID-19 Taskforce expert survey conducted worldwide between the end of April and late May 2020, obtaining 284 valid answers. The experts include those in the field of transport and other relevant disciplines, keeping good balances between geographic regions, types of workplaces, and working durations. Based on extensive analyses of the survey results, this paper first reveals the realities of lockdowns, restrictions of out-of-home activities and other physical distancing requirements, as well as modal shifts. Experts' agreements and disagreements to the structural questions about changes in lifestyles and society are then discussed. Analysis results revealed that our human society was not well prepared for the current pandemic, reaffirming the importance of risk communication. Geographical differences of modal shifts are further identified, especially related to active transport and car dependence. Improved sustainability and resilience are expected in the future but should be supported by effective behavioral intervention measures. Finally, policy implications of the findings are discussed, together with important future research issues. • Findings are derived from a worldwide expert survey implemented in April–May 2020. • Guidelines and contingency plans were reported by only about 30% of experts. • Remarkable modal shifts away from public transport usage were reported. • Developing countries were equally active in taking measures as developed countries. • Various long-term changes in lifestyles and society were revealed. [ABSTRACT FROM AUTHOR]

The novel coronavirus 2019 (COVID-19) outbreak has had wide-reaching and unprecedented impacts on the transport sector worldwide. At present, there is no globally agreed timeframe for when this pandemic will end. The current and near-future potential impacts must be addressed in a relatively comprehensive and seamless way. The present study proposed a PASS (P: Prepare–Protect–Provide; A: Avoid–Adjust; S: Shift–Share; S: Substitute–Stop) approach for policymaking that accounts for COVID-19 and future public health threats. The PASS approach was illustrated conceptually, and then policy measures were recommended by referring to the past and ongoing best practices. Policymaking challenges and research issues were discussed. Image 1 • •Impacts of COVID-19 on the transport sector are targeted. • •A PASS approach was proposed for policymaking for addressing pandemics. • •Policy measures are recommended based on the PASS approach. [ABSTRACT FROM AUTHOR]

Abstract It is essential to better understand the opinions and behaviors of various stakeholders (e.g., persons in companies, customers, government, and local community) when taking effective traffic management and operation measures. Existing studies have examined the interactions between companies and customers in the context of distribution chains; however, even though the importance of other inter-agent interactions is recognized, no efforts have been made, at least in the context of inter-city truck transport routes on expressways. To fill this research gap, this study implemented a stated preference (SP) survey to managers and drivers of transport companies along the expressways in the western part of Japan in 2014–2015, where some new traffic management measures encouraging behavioral changes are investigated. As a result, we obtained 525 valid SP responses from 52 companies (one manager and several drivers from each company). Our survey results first revealed that about 60% of truck transport routes were decided by company managers, and decisions by drivers are minor. A modeling analysis based on a path-size bivariate probit model is further conducted to explicitly represent the interaction between company managers and drivers. The existence of the interaction is statistically supported. We further revealed the similarities and dissimilarities of factors affecting managers' and drivers' decisions, together with the relative importance of measures encouraging behavioral changes. Finally, we made extensive discussions about the implications of analysis results. Graphical abstract Image 1 Highlights • Interpersonal interaction (InIn) within transport company is focused on. • A path-size bivariate probit model with InIn and route-overlapping and is built. • Inter-city truck route choices are investigated using an SP data. • About 60% of truck transport routes are decided by company managers. • The roles of monetary incentives to behavioral changes are identified to be limited. [ABSTRACT FROM AUTHOR]

Autonomous vehicles (AVs) are expected to bring various changes in people's lives. Such expected changes in life may affect people's decisions on the ownership of privately-owned AVs (PAVs) and even future travel demand structure. However, such effects remained unclear due to the lack of relevant studies. By targeting young people, this study fills this research gap by implementing a nation-wide expectation and stated preference (SP) survey in Japan, by comparing with older people. In the survey, respondents first reported their expected changes in life caused by AVs and then chose the most preferred vehicle from a choice set with three types of PAVs (conditional, high, and full automation) and a conventional car. The survey was implemented in 2016 and 3,006 valid SP responses were collected from 1,002 respondents (417 are young people). It is found that young people expected more changes in life and are more likely to choose PAVs with high and full automation than older people, which is consistent with the reported willingness-to-pay. By estimating a mixed logit model with panel data, it is revealed that expected changes in life affect the two age groups' choices of PAVs. There are more inconsistent influences of expected changes in life between the two groups than consistent influences, suggesting the presence of age-related structural differences of responses to future expectations. Diverse responses to future expectations are revealed, which policy implications are discussed. The findings support a life-oriented paradigm shift of travel behavior research and cross-sectoral transport policymaking and future sustainable society design. • Young and older people respond to expected changes in life in an opposite way, mostly. • Expected increases in in-vehicle activities could promote the ownership of AVs. • Influences of young people's expected changes in life differ across types of AVs. • Expected relocation to suburbs does not necessarily encourage the ownership of AVs. • Using AV as a moving home/office/hotel does not affect the ownership of advanced AVs. [ABSTRACT FROM AUTHOR]