Michael A.B. van Eggermond

Introducing the Pedestrian Accessibility Tool

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.

Visualizing Transport Futures: The potential of integrating procedural 3d modelling and traffic micro-simulation in Virtual Reality applications

1 In this paper we elaborate on potential use cases of Virtual Reality (VR) in transportation research 2 and planning and present how we integrated procedural 3D modelling and traffic micro-simulation 3 with the rendering capabilities of a game engine in a semi-automated pipeline. 4 Through a review of potential practical applications, we present how this pipeline will be 5 employed to distil behavioural evidence that can guide planners through dilemmas when designing 6 future cycling infrastructure. At the same time, we are studying efficacy of VR as a method for 7 assessing perceptual behaviour as opposed to traditional methods of visualization. Concretely, we 8 present how the pipeline can be adapted i) to generate parameterised visualisations for stated 9 preference surveys, ii) as a platform for a cycling simulator and iii) to communicate different 10 design scenarios for stakeholder engagement. The flexibility of procedural programming allows 11 discretionary changes to the street design and the traffic parameters. Through this experience of 12 developing procedural models, traffic microsimulations and ultimately VR models for streets in 13 Singapore, we find that visual and temporal feedback enabled by VR makes several important 14 design parameters observable and allows researchers to conduct new types of behavioural surveys 15 to understand how people will respond to different design options. In addition, we conclude that 16 such VR applications open new avenues for citizen engagement and communication of urban plans 17 to stakeholders. 18 Erath, Maheshwari, Joos, Kupferschmid and van Eggermond 3

Residential search and location choice in Singapore

1 As many spatial choices, residential location choices are made from a large pool of potential 2 alternatives. This study evaluates choice sets based on households’ search preferences as a new 3 alternative to the more commonly applied random or weighted sampling, using a recent movers 4 survey conducted in Singapore. Residential units are taken as the unit of analysis. 5 Descriptive analysis reveals that households search in a limited area and in a limited number 6 of markets. Subsequently, a choice set generation algorithm is proposed that evaluates the 7 number of alternatives available to a household based on self-reported search preferences. To 8 a large extent the size of the universal choice set is influenced by the temporal and spatial 9 dimension of the search process. 10 Model results are presented that with alternatives sampled from the universal choice set. 11 Additionally, models are presented with choice sets that take into account households’ self12 reported search preferences that include dwelling size, dwelling price and possible areas. Models 13 including spatial variables describing the social environment, combined with choice sets only 14 including alternatives within the preferred price range, perform best. The social environment 15 consisted of variable describing a household’s average distance to work, the distance to their 16 parents and the average distance to the locations where they most frequently meet their five 17 closest contacts. Other significant spatial variables included the distance to a top primary school, 18 as well as the proximity to a mass rapid transit. Given the significance of these variables tt is 19 proposed to further evaluate anchor and distance-based sampling. 20 van Eggermond, M.A.B., Erath, A. and Axhausen, Kay W. 2