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

TL;DR

This paper introduces a traveler-centered mobility dataset collected via a mobile app, emphasizing the value of travel time for activities beyond speed, and demonstrates its potential through a comparative analysis of transport modes.

Contribution

It presents a novel dataset capturing traveler experiences and perceptions, shifting focus from traditional time-saving metrics to traveler-centered mobility data.

Findings

Trip experience factors differ significantly between transport modes.

Crowdsourced data reveals insights into traveler preferences and negative factors.

The dataset enables new research avenues in mobility and traveler behavior.

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.