Bangkok suffered from the world’s worst traffic congestion in the 1990s due to rapidly increasing car ownership, reflecting the economic growth and road-dependent transport policy beginning in the 1960s. Due to its monocentric but scattered urban structure, traffic congestion is severe, causing tremendous economic loss, deteriorating air quality, and badly affecting the quality of life. A historical review reveals that the urban and transport plan and development were not efficiently coordinated, resulting in unorganized suburbanization and progressively more severe traffic congestion. It is important to reveal the impact of the transportation project on the housing market in order to incorporate the policies for transportation and urban development. To define the impact, the OLS hedonic price model and the local multiscale geographically weighted regression (MGWR) model were estimated, along with the condominium sales data. The results revealed that the impact of rail transit on a rise in property value significantly varied across the study area. It was estimated that, for the area along the major rail transit corridor in the city center, a premium of a location 100-m closer to the station would be more than 200 USD per square meter. At the same time, the value would be less than 80 USD for the area along the rail corridor in the suburb. These findings provide policy insights for future urban and railway development, including the proper coordination of rail transit development and urban development with subcenters, transit-oriented development, and improved pedestrian flow around transit stations.

Asian cities are unique, where people may need more than just walking; however, the walkability research in a local context has received less attention. This paper analyses the walking needs and the influential factors of walking behavior in Asian cities. A comparative analysis in Bangkok and Nagoya is presented, taking into account the characteristics of local street design and development. Street evaluation experiments of various streets are conducted through 360-degree videos. The factor analyses indicate that the walking needs in both cities can be considered in two levels, but the components of the needs are different. Being smooth and having no obstacles are common basic needs. Safety and security are regarded as basic needs in Nagoya, but as higher-level needs in Bangkok. Attractiveness of activity and walk pleasure are the common upper-level needs. Street elements such as width, green, traffic, parking, pollution exposure, and activity are found to be influential on the walking needs. The structural equation models indicate that higher-level needs have more of an influence than the lower-level needs for walking behavior in Bangkok and for shop walking in Nagoya, while the basic need has more influence on walking willingness for transit access. These findings call for practical attention for street design and development where local context and street functions must be carefully considered.

The discrete choice modeling paradigm and in particular the logit model are research topics that have been continuously developed and refined for years in the field of transportation applications. Modeling locational choices, however, differ from modeling transportation choices in that geographically referenced data are used and thereby give specifically spatial choices. A discrete choice model with a systematic specification of the spatial influences in the choice process is presented. The utility function of the model is specified with autoregressive expressions for the deterministic and error components, and the model is evaluated with reference to three alternative models: the standard logit model, a logit model with an autoregressive deterministic term, and the mixed logit model with autoregressive error terms. Two applications are presented: one with simulated data and another with real data for the analysis of location choice in Sendai, Japan. The proposed model shows an improved performance over the three reference models.

Many megacities in the world, especially Bangkok, are facing severe congestion in road traffic and public transport, particularly during peak hours. This situation (a) worsens the quality of life, (b) releases emissions causing air pollution and climate change, and (c) subsequently creates requests for massive investment in transport infrastructure, which easily exceed the budget’s limit. Instead of solving the problem by supply-side strategies, applying ICT-based solutions to reform people’s daily activities, particularly commuting and working behaviors, on the demand-side is an alternative solution. As a promising solution, Mobility as a Service (MaaS) introduces ICT to persuade people to use public modes of transport. However, modal shift is a partial solution to mitigate traffic congestion. With technological advancements in communication, people become more flexible in their activities in terms of place and time aspects. MaaS should not only induce a transport mode shift but also a workplace shift and working time shift by extending the planning service in daily activity-travel level, exploiting people’s flexibilities for an activity’s place and time to manage travel demand. This paper proposes the QOL-MaaS as the extended MaaS to support space–time shift of activity-travel and reveals its potential impacts on traffic congestion, quality of life, and CO₂ emission.

Rail transit systems around the world have been suffering from heavily reduced ridership due to reduced capacity for social distancing and passengers’ concern over the risk of COVID-19 infection. Various countermeasures were implemented to reduce the COVID-19 risk so that passengers felt safe to travel on rail. The objectives of this study were to evaluate COVID-19 countermeasures of Bangkok’s urban rail from passengers’ viewpoints and examine its influence on passenger’s confidence. The background of the COVID-19 pandemic in Thailand and the rail countermeasures implemented in Bangkok were summarized. The data were obtained from an interview survey of 1105 railway passengers conducted at the stations during the second wave of the pandemic. Factor analyses and structural equation modeling were conducted. The results revealed that social distancing was not satisfied by the passengers but adversely caused inconvenience and increased infection risk when the station or rail were congested. On the other hand, the passenger temperature check, face mask enforcement, and hand sanitization countermeasures were found to highly and positively contribute to passengers’ confidence. Contact tracing application was also found to raise awareness and confidence. The findings provided insights for rail authorities and related agencies to effectively implement the countermeasures that would be practically and financially sustainable.