Geospatial data available to researchers has increased tremendously over the last several decades, opening up opportunities to define residential location in multiple ways. is has led to a myriad of variables to define "location" in residential location choice models. In this paper, we propose a common classification for location variables and categorize findings from a wide range of studies. We find similar preferences but different measurement methods and market segments for locations across different study regions. Recent studies consider the residential unit as choice alternative, making it possible to include a detailed description of the built environment. However, these studies are still limited in number and the inclusion of socioeconomic environment is more common. Transport land-use models can benefit from the inclusion of points of interest, such as schools, network distances, and the distance to previous locations. For the results of location choice models to be transferable to different disciplines, and avoid multi-collinearity, it is necessary to present different model specifications, including variables of interest in different disciplines.

Accessibility is increasingly used as a metric when evaluating changes to public transport systems. Transit travel times contain variation depending on when one departs relative to when a transit vehicle arrives, and how well transfers are coordinated given a particular timetable. In addition, there is necessarily uncertainty in the value of the accessibility metric during sketch planning processes, due to scenarios which are underspecified because detailed schedule information is not yet available. This article presents a method to extend the concept of "reliable" accessibility to transit to address the first issue, and create confidence intervals and hypothesis tests to address the second.

The indexes for walkability proposed so far refer generally to the closest amenities and public transport stops and the existing network structure. The weights of the attributes do not reflect the independently measured preferences of the users and residents. Design attributes such as the location and type of crossings and walkway design features are usually surveyed in walkability audits. However, such attributes are usually not considered when pedestrian walksheds or other accessibility-based walkability indexes are calculated. Nevertheless, these design attributes are very relevant for actual planning decisions. The proposed walkability index can be behaviorally calibrated, has been implemented as a geographic information system tool, and is published as open source software. The pedestrian accessibility tool allows the evaluation of existing and future urban plans with regards to walkability. The tool calculates Hansen-based accessibility indicators with the use of a customizable specification of the generalized walking costs, and it incorporates user-defined weights of destination attractiveness. The basic user workflow of the tool is summarized. Three case studies show real-world applications of the tool to support the planning of pedestrian infrastructure in an urban context. With indications of potential areas of improvement that have been reported by pilot users working in an urban planning department, hints are also given for future research.

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The use of virtual reality (VR) in transport research offers the opportunity to collect behavioral data in a controlled dynamic setting. VR settings are useful in the context of hypothetical situations in which real-world data does not exist or in situations which involve risk and safety issues making real-world data collection infeasible. Nevertheless, VR studies can contribute to transport-related research only if the behavior elicited in a virtual environment closely resembles real-world behavior. Importantly, as VR is a relatively new research tool, the best-practice with regards to the experimental design is still to be established. In this paper, we contribute to a better understanding of the implications of the choice of the experimental setup by comparing cycling behavior in VR between two groups of participants in similar immersive scenarios, the first group controlling the maneuvers using a keyboard and the other group riding an instrumented bicycle. We critically compare the speed, acceleration, braking and head movements of the participants in the two experiments. We also collect electroencephalography (EEG) data to compare the alpha wave amplitudes and assess the engagement levels of participants in the two settings. The results demonstrate the ability of VR to elicit behavioral patterns in line with those observed in the real-world and indicate the importance of the experimental design in a VR environment beyond the choice of audio-visual stimuli. The findings will be useful for researchers in designing the experimental setup of VR for behavioral data collection.