Erath, Alexander

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Alexander
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Erath, Alexander

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Gerade angezeigt 1 - 9 von 9
  • Publikation
    How autonomous electric vehicles will affect the Swiss transport system. What we already know and what we can’t know yet
    (ETH Zürich, 06.12.2023) Erath, Alexander; Axhausen, Kay W. [in: NSL Kolloquium - Transport planning. Where do we go now?]
    04B - Beitrag Konferenzschrift
  • Publikation
    Nachhaltige Ansätze zur Parkraumplanung
    (14.09.2023) Erath, Alexander
    06 - Präsentation
  • Publikation
    Destination choice modeling with spatially distributed constraints
    (University of Minnesota, 03.07.2023) Vitins, Basil; Erath, Alexander [in: Journal of Transport and Land Use]
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Publikation
    Begleitstudie zum Tier-Pilotprojekt in Riehen
    (Institut Bauingenieurwesen, Hochschule für Architektur, Bau und Geomatik FHNW, 16.01.2023) Erath, Alexander; van Eggermond, Michael
    05 - Forschungs- oder Arbeitsbericht
  • Publikation
    Forecasting district-wide pedestrian volumes in multi-level networks in high-density mixed-use areas
    (Western Norway University of Applied Sciences (HVL), 06/2022) Mavros, Panos; van Eggermond, Michael; Erath, Alexander; Helle, Veera; Acebillo, Pablo; Xu, Shuchen; van Nees, Akkelies; de Koning, Remco Elric; Jacobsen Åsli, Thale [in: 13th International Space Syntax Symposium]
    This paper is concerned with improvements in the forecasting of pedestrian flows in multilevel pedestrian networks in high-density urban environments. 3D network topology measures are combined with land-use data, and validated against extensive pedestrian counts, to provide both evidence for the applicability of network analysis in tropical metropolises, as well as a calibrated tool for urban planners. The research focuses on four area in Singapore. These areas have in common that they all are prominent transport hubs, but differ in surrounding land-use types and dominant network topology (e.g. indoor, outdoor, above ground, below ground, at grade). Multi-level pedestrian networks were drawn based on OpenStreetMap, include sidewalks on both sides of major roads for a radius up to 2 kilometres from the site centroids. Spatial network analysis was performed using sDNA which allows vertical networks to generate measures describing the spatial configuration of the network. Subsequently, pedestrian counts were conducted during three consecutive days. In total, counts were conducted at more than 250 locations in 2018 and 2019, well before the global COVID19 pandemic. Pedestrian flows are set against a series of variables, including pedestrian attractors and generators (e.g. shops, offices, hotels, dwellings), and variables describing the spatial configuration of the network, using advanced regression models. Our results show that betweenness metrics (i.e. space syntax choice) combined with land-use yield high predictive power. Dependent on the study site, network metrics based on angular distance outperform those based on metric distance or perceived link distance. This research demonstrates that is necessary to account for the multi-level nature of networks, and that indoor flows through private developments cannot be neglected, in particular when planning for integrated transport developments. The paper concludes with recommendations and implications for practice.
    04B - Beitrag Konferenzschrift
  • Publikation
    Aktivitätenbasierte Verkehrsmodelle
    (Bundesamt für Strassen, 12.12.2021) Vitins, Basil; Erath, Alexander; Fellendorf, Martin; Arendt, Michael
    05 - Forschungs- oder Arbeitsbericht
  • Publikation
    Image-based reality-capturing and 3D modelling for the creation of VR cycling simulations
    (Copernicus, 17.06.2021) Wahbeh, Wissam; Ammann, Manuela; Nebiker, Stephan; van Eggermond, Michael; Erath, Alexander; Wahbeh, Wissam [in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences]
    With this paper, we present a novel approach for efficiently creating reality-based, high-fidelity urban 3D models for interactive VR cycling simulations. The foundation of these 3D models is accurately georeferenced street-level imagery, which can be captured using vehicle-based or portable mapping platforms. Depending on the desired type of urban model, the street-level imagery is either used for semi-automatically texturing an existing city model or for automatically creating textured 3D meshes from multi-view reconstructions using commercial off-the-shelf software. The resulting textured urban 3D model is then integrated with a real-time traffic simulation solution to create a VR framework based on the Unity game engine. Subsequently, the resulting urban scenes and different planning scenarios can be explored on a physical cycling simulator using a VR helmet or viewed as a 360-degree or conventional video. In addition, the VR environment can be used for augmented reality applications, e.g., mobile augmented reality maps. We apply this framework to a case study in the city of Berne to illustrate design variants of new cycling infrastructure at a major traffic junction to collect feedback from practitioners about the potential for practical applications in planning processes.
    04B - Beitrag Konferenzschrift
  • Publikation
    Using backcasting to support corporate mobility management
    (2021) van Eggermond, Michael; Erath, Alexander
    The paper at hand describes a research project conducted in collaboration with a major employer based in Basel, Switzerland. The company employs innovative mobility policies, such as a strict parking regime, with lots only available to employees who have to travel more than 45 minutes by public transport, offers bike sharing and public transport bonuses, but would like to further reduce parking lots and desires to reduce greenhouse emissions resulting from commuting while remaining an attractive employer. The aim of the project was the to better understand the impact of exogenous developments (e.g. new train lines, road pricing, infrastructure improvements, safer cycling routes) and endogenous mobility policies (e.g. bike sharing, parking fees, charging stations). These developments and policies were identified in a series of workshops with stakeholders. At the same, key performance indicators were formulated. Instead of forecasting the impact of these policy measures, the project set out to describe a desirable future (e.g., less emissions, attractive employer), reason backwards from the desired situation and formulate a package of policy measures that could in this future, whilst taking into account exogenous developments. This process is also known as backcasting and has been applied in several studies (e.g. Banister et al., 2000; Barandier 2015) To quantify the impact of the policy measures several data sets were available and newly collected. Travel times and distances for motorized private transport, walking and cycling were calculated using the Google travel time API for all employees. As Google’s API only offers limited coverage for public transport in Germany and France, use was made of publicly available public transport schedules and the open-source routing engine R5. A survey was conducted among employees, resulting in over 6000 responses. Based on the survey data, choice models were estimated and applied. Exogenous and endogenous developments for over 10 policy measures were quantified using simplified assumptions, whilst taking into account the spatial differences, and used to forecast the impact of each individual measure and combinations of measures. Measures include the impact of e-bike provision, the impact of improved cycling infrastructure, new train stations and the differentiated parking fees. The project resulted in a set of mobility policies and recommendations to monitor these mobility policies, and the methodology has been applied at other stakeholders to support sustainable mobility policies.
    06 - Präsentation
  • Publikation
    Calibration of a regional agent-based travel demand model to simulate the spread of COVID-19
    (2021) Mesaric, Raphael; Erath, Alexander
    The recent COVID-19 pandemic has shown the need of readily available tools to simulate the spreading of infectious diseases and assess the potential impact of policy measures aimed at the containment of the disease. The most common approach in epidemiology is to use compartmental models which model disease spreading as a series of stocks (compartments) and flows. The most basic version considers three compartments: susceptible, infectious and recovered. One of the core assumptions of these models, however, is a homogeneous population which is a serious limitation when it comes to clustered outbreaks. The research at hand uses an agent-based travel demand model (MATSim) coupled with a recently developed extension (EpiSim) to simulate the spread of the pandemic by tracking the interactions of agents und subsequently identifying infections by following their contact network. This overcomes the compartmental assumption of the previous models. In this presentation, we summarize the calibration results of the EpiSim model which is based on the regional activity- and agent-based travel demand model of the trinational region around Basel. The calibration procedure is based on data on case numbers and hospitalisations from three countries (Switzerland, Germany and France) at different spatial resolution. The underlying models account for the effect of border closures and spatially varying restrictions to limit the spread of COVID-19. In contrast to existing studies, this model pays particular attention to disease import through external traffic from outside the model area as well as cross-border travel demand.
    06 - Präsentation