What's Your Value of Travel Time? Collecting Traveler-Centered Mobility Data via Crowdsourcing

Authors: Cristian Consonni, Silvia Basile, Matteo Manca, Ludovico Boratto, André Freitas, Tatiana Kovacikova, Ghadir Pourhashem, Yannick Cornet

10 pages, 1 figure, LaTeX. Final camera-ready version accepted at the 15th International AAAI Conference on Web and Social Media (ICWSM 2021) - 7-11 June 2021
License: CC BY-SA 4.0

Results of the summarizing process for the arXiv paper: 2104.05809v1

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The integration of information and communication technologies (ICT) with transportation has transformed mobility in the last two decades. This has led to new forms of offerings such as on-demand services and even whole new business models for transport, where users can share rides or even private cars. Novel mobility paradigms have emerged, in which users' value of travel time (VTT) is defined as the combination of different factors such as emissions, costs, and fitness for the user. However, reliance upon private cars remains a challenge. To address this challenge, crowdsourcing can become a valuable means towards gathering data from a vast audience of travelers about both their travel preferences and wishes and their actual day-to-day transport usage. The extraction of actionable knowledge from user mobility has been a central perspective mainly for mobility stakeholders - such as policy-makers, planners, and transport operators - who used this knowledge to adapt services to end-users. However, under this paradigm end-users have mostly been passive actors. In contrast to traditional approaches that focus on time savings by proposing solutions that include the shortest or fastest paths without considering the traveler's perspective, we argue that worthwhile time is a central concept for data collection. While traditional views consider travel time as something to minimize, we consider it an opportunity characterized by other activities. To ground the definition of worthwhile time into multiple dimensions we collected data through a dedicated mobile app called Woorti. Each trip contains multi-faceted information: from the transport mode through its evaluation to positive and negative experience factors. We present a new dataset containing data about travelers and their journeys collected from Woorti across ten European countries: Belgium Croatia Finland France Italy Norway Portugal Slovakia Spain Switzerland. A key challenge was engaging users across multiple countries for an extended period actively using the smartphone app for at least 14 days. To facilitate this process we framed it as a challenge between users: data-collection campaigns (DCCs) would group users together and reward the most active ones in each campaign. We partnered with thematic organizations across Europe such as cycling associations and appointed DCC managers as liaisons with the community to recruit participants promote and monitor the data collection process. To showcase this new dataset's potential we present a use case that compares corresponding trip legs with different transport modes studying experience factors that negatively impact users using cycling and public transport as alternatives to cars.
AI-generated keywords: Crowdsourcing Mobility Sustainable Transportation Data Collection User Experience

AI-generated Key Points

  • Integration of ICT with transportation has transformed mobility in the last two decades
  • New forms of offerings such as on-demand services and whole new business models for transport have emerged
  • Novel mobility paradigms have emerged, where users' value of travel time (VTT) is defined by different factors such as emissions, costs, and fitness for the user
  • Crowdsourcing can be a valuable means towards gathering data from a vast audience of travelers about both their travel preferences and wishes and their actual day-to-day transport usage
  • Extraction of actionable knowledge from user mobility has been a central perspective mainly for mobility stakeholders such as policy-makers, planners, and transport operators who used this knowledge to adapt services to end-users
  • Traditional approaches that focus on time savings without considering the traveler's perspective are not sufficient. Worthwhile time is a central concept for data collection.
  • A new dataset containing data about travelers and their journeys collected from Woorti across ten European countries: Belgium Croatia Finland France Italy Norway Portugal Slovakia Spain Switzerland.
  • Engaging users across multiple countries for an extended period actively using the smartphone app was a key challenge. Data-collection campaigns (DCCs) would group users together and reward the most active ones in each campaign.
  • A use case that compares corresponding trip legs with different transport modes studying experience factors that negatively impact users using cycling and public transport as alternatives to cars is presented.
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Abstract: Mobility and transport, by their nature, involve crowds and require the coordination of multiple stakeholders - such as policy-makers, planners, transport operators, and the travelers themselves. However, traditional approaches have been focused on time savings, proposing to users solutions that include the shortest or fastest paths. We argue that this approach towards travel time value is not centered on a traveler's perspective. To date, very few works have mined data from crowds of travelers to test the efficacy and efficiency of novel mobility paradigms. In this paper, we build upon a different paradigm of worthwhile time in which travelers can use their travel time for other activities; we present a new dataset, which contains data about travelers and their journeys, collected from a dedicated mobile application. Each trip contains multi-faceted information: from the transport mode, through its evaluation, to the positive and negative experience factors. To showcase this new dataset's potential, we also present a use case, which compares corresponding trip legs with different transport modes, studying experience factors that negatively impact users using cycling and public transport as alternatives to cars. We conclude by discussing other application domains and research opportunities enabled by the dataset.

Submitted to arXiv on 12 Apr. 2021

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