COVID-19 has been large impacts on people’s behavior and policies in urban area, transportation network, market, and industry realm that have been studied in the research field of infrastructure planning and management. This special issue includes papers in the research field of infrastructure planning and management that study about people’s behavior and policies influenced by COVID-19 including ones presented in the research seminar of infrastructure planning and management that was held on 8th, August, 2020.

 In recent years, demand for medical care in Japan has been increasing. “Connected Medicine,” which incorporates ideas of ICT and MaaS, is being promoted for better patient convenience and reduction of burdens placed on medical personnel. Moreover, under the COVID-19 epidemic, it is expected to be used actively to reduce risks of infection. For this study based on results of our original questionnaire survey, we analyzed changes in intentions to use connected medicine before and after COVID-19 and factors underlying those changes. Results showed the following. 1) Benefits of “Connected Medicine” are the elimination of hospital visits and waiting times, but a shortcoming is the accuracy of diagnosis. 2) Intentions for using “Connected Medicine” have changed with the prevalence of COVID-19. The intention to use “Connected Medicine” has been particularly high for online medical services. 3) Differences in usage intentions depend on personal attributes, hospital visit behavior, the type of medical practice, and other factors.

 In this paper, we conducted a questionnaire survey on web to understand the impact of the spread of COVID-19 and the government's request to refrain from socioeconomic activities on people's attitudes and behavior. The results showed that the risk of infection and death was overestimated by several times to thousands of times more than the actual risk. In addition, people do not thoroughly avoid touching their eyes, nose and mouth, which is an effective countermeasure against contact infection, and we pointed out the problems in providing information about it by the government. The results also show that more than 65% of the respondents supported the declaration of the state of emergency, that more people find enjoyment than stress in being at home, and that the opinions of experts were more influential in making decisions than those of newscasters, pundits and politicians.

 The purpose of this study is to clarify the important factors and the tendency of domestic travel behaviors under the epidemic of COVID-19 by applying latent class analysis. 74% of the subjects were concerned about infectious diseases, and only 36% had the intention of taking domestic sightseeing trips within the next year. Furthermore, from the result of latent class analysis that can extract combination patterns of answers about important factors in destination selection, the subjects could be classified into nine classes. From the analysis results, three points were identified. 1) The class that considered all factors related to infectious disease control had the highest composition ratio. 2) The second-highest composition ratio was the class that did not consider any of them. 3) The top two classes were highly associated with gender, age group, awareness of infectious diseases, and the presence or absence of children living together. Consequently, four factors are found to be important for attracting tourists: improving the environment such as acceptance feelings, the number of infected people, the management of the number of acceptances, and the dispelling of anxiety about the development of medical support.

 The purpose of this paper is to investigate how the inter-prefecture travel were affected by the declaration of a state of emergency in Hokkaido and by the government’s declaration of a state of emergency in all 47 prefectures in Japan for avoiding the spread of COVID-19. The data used to clarify this are the Mobile Spatial Statistics (MSS) for the period January-June 2020. As MSS are provided in 500-m mesh estimated population, we aggregated the population of the mesh on prefecture to confirm the volume of travel. The results show that although the declaration of the state of emergency is significantly related to the inter-prefecture travel, it continues to be reduced even after the declaration of the state of emergency is ended, indicating that inter-prefecture travel are still constrained by structural changes and psychological effects.

 This study reveals the changes in inter-prefecture travel behavior under COVID-19 pandemic. The mobile phone location data is useful for this analysis because it enables us to obtain accurate and temporally detailed inter-prefecture travel data. We applied non-negative matrix factorization to this high-dimensional data for understanding the time-series features. Furthermore, by adding a penalty term of L₁ norm to the model, it is possible to extract more distinct features. As a result of this analysis, we have quantitatively identified the following behavioral changes. This analysis revealed the following quantitative behavioral changes: inter-prefecture commuting behavior in the Tokyo metropolitan area, weekend travel, and returning home during long vacations. Furthermore, the residual information revealed that these behavioral changes were spatially unevenly distributed.

 With the spread of COVID-19 infection, the Prime Minister came to promote the concept of “distributed land” in June 2020. However, the contents are ambiguous compared to the national land plans and city plans decided after deliberation by experts as in the past. The sense of distance from the current compact city policy, which is different in concept, is also unknown. In this research note, 1) rural areas, 2) suburbs, and 3) online, which are assumed to be the decentralization destinations of urban functions, are taken up, and the current situation and issues corresponding to decentralization in each space are objectively examined. As a result of the examination, the following three points were pointed out as important. 1) To embody the contents of the decentralization policy to rural areas, 2) Avoid going against the compactification policy in the metropolitan area, and 3) Refer to the classical three-magnet concept, and find the optimum point for use between urban space and cyberspace.

 We study the impact of highways on the geography of regional employment and establishments. To identify the causal effect and its spatial scope, we have relied on geographical random sampling, propensity score matching and difference-in-difference estimator. Using the data of highway interchanges which were put into service between 1996 and 2014 in Japan, we estimate the impact of the openings of highway interchanges on the density of employment and establishments in the surrounding area by distance bands and by industries. The results show that new highway interchanges increase regional total employment by 3.4% and that the effect appears within 4km. We also show the robustness of the proposed method by comparing with the alternative conventional method.

 With the increase number in vacancies, researchers attempt to estimate the spatial distribution of vacant housing. In specifying the model, municipality-owned data are recently included due to the existence of features that contribute to the accuracy of the model. This study constructs a predictive model of future vacant housing distribution using municipality-owned data. We employ XGBoost, a machine learning method, to deal with the existence of missing values and non-linearity of data structure. In consequence, we obtain the following findings. First, since the model proposed is based on decision trees, which enable us to flexibly deal with complicated and missing data. Second, the important features we picked up follow the arguments by previous studies, and thus confirmed the validity of the proposed model. Third, the proposed model approximates 84.3 percent of accuracy per 125-meter grid cell, which holds the sufficient level of the accuracy for municipalities to take advantage of.

 This study develops a model of multi-modal commute with bottleneck congestion and scale economies in rail transit. To this end, we incorporate the models of de Palma et al.³⁾ and Tabuchi²⁾ into the standard bottleneck model¹⁾. We then show the properties of equilibria when the regulator sets rail fares equal to the marginal cost or average cost and when there is no regulation on rail fares. By comparing these equilibria, we clarify the impacts of the regulations on the number of rail commuters and commuting costs.

 Crowdsourced delivery (CSD) is a last mile delivery system in which drivers of private cars scheduling trips make deliveries by taking detours during the trips. While the CSD system reduces delivery cost, it is required to solve the unsolvable large-scale optimization problem of matching a large number of drivers with a large number of delivery tasks. To address this problem, we propose an efficient algorithm for the matching problem of CSD. In the proposed algorithm, this matching problem is decomposed into a hierarchical problem consisting of a master problem and multiple sub-problems. Further, a virtual network that can express matching as a traffic assignment to the path is constructed, and the master problem is reformulated into a traffic assignment problem on that network, to reduce the scale of the master problem. Then, the problem is drastically reduced by transforming it from an expression that uses path variables to an expression that uses only link variables. Numerical experiments have shown that the proposed algorithm reduces the computational cost optimizing calculations in the order of several digits and enables large-scale CSD matching.

 Although disaster victims with damaged homes live in temporary housing, the effects of temporary housing location on their future residential preferences remain unclear. This study examines the relationship between the temporary housing location and disaster public housing location preferences of victims in Mashiki following the 2016 Kumamoto earthquake in Japan. The results of a mail survey reveal that, among victims who lived in rural areas before the earthquake and now live in urban or large-scale temporary housing complexes, the location of temporary housing affects their location preferences toward disaster public housing. Focus group interviews with Mashiki local government staff identified seven factors explaining the preference for areas that differ from the victims’ original residence: transport accessibility, family-related issues, post-earthquake interpersonal bonds, issues related to life in temporary housing, difficulty imagining collective housing, issues related to original residence, and job locations.

 Various evaluations have been made in the field of administrative planning to assess financial constraints imposed by population decline, but the actual situation has not been fully elucidated. For this study, we categorize changes and evaluation contents of evaluations performed in the planning field for urban planning administration. Furthermore, we clarify the characteristics and present basic information for future evaluations. From analyzing laws, plans, operation guidelines, and other documents related to city planning administration, evaluation efforts were categorized into three types: a) evaluation of partial plans, b) evaluation of plans in a project area, and c) comprehensive evaluation of plans. Results clarified that the evaluation contents were integrated, the target areas were expanded, and the evaluation periods were lengthened in the order of a), b), and c).