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Emergency vehicles should be planned to have smooth access to people's residences after a large scale disaster. This study proposes ANR, the Accessible Node Rate, which represents the ratio of the number of accessible nodes to total nodes in the network, as an indicator for evaluating the reliability of a local street network. Using the ANR, this study evaluates the urban districts of Nada Ward in Kobe City where the earthquake caused extensive damage, and proposes planning changes to provide the local street networks with higher reliability. Furthermore, in order to see if the ANR can be used for analyzing another city's reliability, a case study of Beppu City which is supposed to have the possibility of the same magnitude of earthquake, is examined. A system that supports traffic network editing and analysis for reducing the workload in a wider area is developed.

In this study, a mode choice model explicitly considering travel time reliability is developed. This model quantifies travelers' attitudes towards travel time variability as well as average travel time. Data were collected from the morning commuters who have two or three alternative modes including some public transportation and private vehicles. The survey period includes both a normal period where all the transportation modes were available and an abnormal period where the main major public transportation service was closed. The model is applied to practical commuters' decision making, and one of the findings in the mode choice model is that they pay relatively large attention to the travel time variability. In this model, travel time variability is dealt with as the possibilities that the commuters arrive before or after their job starting time separately. The best-fit model indicates that the commuters pay more attention to early arrival and less to late arrival in the normal period. In the abnormal period, however, their attention shifts drastically to late arrival. This suggests that the commuters behave optimistically in the normal period and pessimistically in the abnormal period.

When decision makers encounter new assurance services that can be customized for individual clients, they must include them in their pre-existing categorization of assurance, a cognitive task known as postclassification. This paper draws upon three literatures (classification research in accounting, theory of assurance, and cognitive psychology) in order to suggest how this task might be modeled and studied empirically, using the example of SysTrust™. The role of a necessary condition for successful postclassification called the category use effect (Ross, 2000), in which decision makers are reminded of pre-existing categories when they learn to use new categories, is explained.

Improvements in digital technology, increased automation and the sharing economy are all promised changes in transport provision over the next few years. How will such changes effect an increasing ageing society? There are obvious advantages that technology can bring to improve tickets on public transport with smartcards which will help older people. Trip planning can be facilitated with better more bespoke travel information and improved satnav and real-time information. Mobility scooters, electronic bikes and better inclusive designed cars and buses all help the offering to older people to maintain their mobility. Internet-based platforms facilitate collective transport offerings and can facilitate community transport and transport networks which help older people stay mobile. Supporting policy and legislation can help older people achieve quality mobility, for example accessibility has increased step-free access to public transport across Europe, though there remains still some inaccessibility especially where modification of existing infrastructure remains a costly barrier.