Anna Reiffer


Last Name

Reiffer

First Name

Anna

ORCID

0000-0003-1764-0154

Organisational unit

09827 - Heinen, Eva / Heinen, Eva

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2018 - 201942020 - 202522
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Publications 1 - 10 of 26
  • The Interplay of Bikesharing, Carsharing and Public Transport - A Spatiotemporal Analysis of Booking Data
    Item type: Conference Paper
    Reiffer, Anna; Wörle, Tim; Vortisch, Peter (2022)
    ETC Conference Papers 2022
    This paper investigates relationships between carsharing, bikesharing and public transport. The analysis relies on three sources of data: dockless bikesharing booking data, free-floating carsharing booking data, and General Transit Feed Specification (GTFS) data. We propose that by comparing the trips conducted with shared mobility services such as carsharing and bikesharing to public transport service data represented by GTFS data, a first indication is given on whether these services supplement public transport or if the services have an adverse effect. Our results indicate that bikesharing is used almost entirely as a supplement to public transport. There is only a very small proportion of trips that could be conducted on a direct public transport connection. Contrary to this, we find that still a considerable part of the analysed carsharing trips is conducted although a (direct) public transport connection was available.
  • Longitudinal Analysis of Changes in Telecommuting Behavior and Associated Changes in Travel Behavior
    Item type: Other Conference Item
    Reiffer, Anna; Magdolen, Miriam; Ecke, Lisa; et al. (2023)
    2023 TRB Annual Meeting Online Program Archive
    Due to the increased use of information and communication technologies, there has been a higher proportion of telecommuting in recent years. And the Covid-19 pandemic has massively accelerated this trend. With the higher proportion of telecommuting, there is an increasing need to study the effects of telecommuting on travel behavior. While previous studies have mainly focused on differences between telecommuters and non-telecommuters, it is important to understand if travel behavior is driven by the characteristics of telecommuters themselves or if telecommuting induces a change in travel behavior. In this paper, the authors analyze panel data from the last ten years of the German Mobility Panel, a national household travel survey. A first-difference regression model is applied to assess changes in telecommuting and travel behavior beyond commuting of individuals. The authors estimate five different models to account for both long-term and short-term changes and changes in the telecommuting proportion itself. The results show that long-term decisions such as residential relocation and car ownersip are not immediately affected by a change in telecommuting frequency. However, in a short-term perspective, changes in travel behavior become evident. While the number of trips decreases with the proportion of working from home, the person kilometers show a positive association. The results indicate that the differences between telecommuters and non-telecommuters stem mainly from re-investing the time saved by telecommuting into longer non-work-related travel and not from behavioral differences between the two groups.
  • Framework for Generating 7-Day Activity Schedules Considering Household Interactions
    Item type: Other Conference Item
    Reiffer, Anna; Vortisch, Peter (2024)
    2024 TRB Annual Meeting Online Program Archive
  • Mode Choice Behavior on Access Trips to Carsharing Vehicles
    Item type: Conference Paper
    Reiffer, Anna; Wörle, Tim; Heilig, Michael; et al. (2020)
    2020 Forum on Integrated and Sustainable Transportation Systems (FISTS)
    The introduction of a carsharing service reduces both private car ownership and total vehicle miles traveled. Due to the environmentally friendly modal shifts, policy makers are keen to increase market share of carsharing. While past research has focused on both the users of carsharing services and their general mode choice, little is known about access trips to vehicles of station-based carsharing services. However, because access to a mode is critical for its success, gaining insight into the way people experience access trips is an important step towards increased mode acceptance. In this paper we present model results based on a stated choice survey regarding access trips to carsharing stations conducted by users of a regional carsharing provider in Germany. After giving a brief overview of the conducted survey and the results of a descriptive analysis, we present the results of multiple multinomial and mixed multinomial logit models. Results of the multinomial logit models show that trip-related variables are the most important determinants for access mode choice, while only a few socio-demographic parameters are significant. We estimated mixed multinomial logit models to find out how consistent respondents answered across the choice situations. The results show that respondents were not always consistent across their choices and would, e.g. choose public transportation even if that entailed long distance travel or waiting times. Our findings are consistent with both research regarding public transportation access and the small pool of research regarding access of carsharing vehicles.
  • Analysing Long-Term Effects of the Covid-19 Pandemic on Last-Mile Delivery Traffic Using an Agent-Based Travel Demand Model
    Item type: Conference Paper
    Reiffer, Anna; Kübler, Jelle; Briem, Lars; et al. (2023)
    Lecture Notes in Mobility ~ Proceedings of the 12th International Scientific Conference on Mobility and Transport
    E-commerce demand has increased steadily over the last decades and this trend has accelerated even more since the start of the Covid-19 pandemic. This entailed that user groups such as older people who previously only shopped in-store were incited to shop online to reduce risk of infection leading some to switch to online shopping as the main shopping channel. This study analyses the long-term effects of increased online shopping and subsequent delivery demand due to the Covid-19 pandemic using an agent-based travel demand model. We analyse the simulation of two scenarios for the model area Karlsruhe, Germany: one scenario simulates the parcel delivery demand before the pandemic and the other scenario simulates the demand during the pandemic of the synthetic population. Our results show that there have been shifts in both socio-demographic characteristics of online shoppers and spatial distribution of parcel delivery demand induced by the Covid-19 pandemic. The scenario simulation based on the pandemic related data shows that not only the influence of income has shifted but also the effects of age on e-commerce activity has changed due to the pandemic. The findings are of interest to transport planners and delivery service providers as they highlight the importance of recognising that the Covid-19 pandemic not only induced a shift in socio-demographic profiles of online shoppers but that this shift also entails a change in the spatial distribution of parcel deliveries.
  • Identifying Usage Profiles of Station-Based Car-Sharing Members Using Cluster Analyses
    Item type: Conference Paper
    Reiffer, Anna; Wörle, Tim; Briem, Lars; et al. (2019)
    2019 TRB Annual Meeting Online
    With the growing usage of the internet, the possibility for shared mobility has risen just as much. Beside ride-sharing, bike-sharing, and shared parking, this applies, especially to car-sharing. Past research activities have often been limited to the economic, ecological, and urban benefits of car-sharing, such as the number of privately owned cars that could be replaced by car-sharing vehicles or the potential to save parking space. These analyses disregard the user’s behavior and patterns of usage. However, to analyze, e.g., future market shares of car-sharing, we first have to evaluate how car-sharing members use car-sharing and what purposes the trips might serve. One such study has been conducted in Germany, however, using free-floating car-sharing data. The focus of research is put on data from a station-based car-sharing provider and what kind of user or usage profiles can be identified. The authors investigated this by performing a cluster analysis using the k-means algorithm. The results indicate that there are five types of station-based car-sharing users and usage respectively. There are commercial users, users who use car-sharing for regular and users who use it for irregular activities. Furthermore, car-sharing vehicles are used to replace a second car and also for long distance travels. These findings are in part consistent with the study on free-floating car-sharing but also show some dissimilarities, as to be expected since the two systems generally serve different purposes.
  • Prediction of Telecommuting Engagement through Machine Learning to Enhance Travel Survey Data
    Item type: Other Conference Item
    Reiffer, Anna; Kagerbauer, Martin; Vortisch, Peter (2024)
    2024 TRB Annual Meeting Online Program Archive
  • Generierung von Aktivitätenplänen für agenten-basierte Nachfragemodelle
    Item type: Conference Paper
    Reiffer, Anna (2024)
    FGSV Tagungsberichte ~ HEUREKA ’24: Optimierung in Verkehr und Transport
    Aktivitätenbasierte Verkehrsnachfragemodelle haben Fortschritte gemacht, fokussieren jedoch meist auf einzelne Tage, verwenden oft vereinfachte Aktivitätenhierarchien und berücksichtigen selten Haushaltsinteraktionen. In diesem Beitrag wird ein Modellansatz zur Generierung von Ak tivitätenplänen für eine Woche unter Berücksichtigung von Interaktionen zwischen Haushalts mitgliedern vorgestellt. Dazu wird im ersten Schritt für jeden Haushalt die gesamte Zeitverwen dung je Aktivität für eine Woche bestimmt. Basierend auf der Zeitverwendung eines Haushal tes, wird zur Generierung von Aktivitätenepisoden ein Mulitkriterielles Lineares Optimierungs problem formuliert. Dieses dient als Input für ein Constraint-based Optimierungsproblem zur Erstellung von Aktivitätenplänen. Das Modell eignet sich als Grundlage für agenten-basierte Verkehrsnachfragemodelle.
  • Design of a stated-preference survey to analyze intermodal choice behavior of car sharing users
    Item type: Other Conference Item
    Reiffer, Anna; Kagerbauer, Martin; Hilgert, Tim; et al. (2019)
    Conference Proceedings mobil.TUM 2019: Transportation Systems of the Future
  • Analyzing the effects of new forms of work on travel demand
    Item type: Other Conference Item
    Reiffer, Anna (2021)
Publications 1 - 10 of 26