Smartphone based travel diary collection: experiences from a field trial in Stockholm

Allström, Andreas; Kristoffersson, Ida; Susilo, Yusak O.

doi:10.1016/j.trpro.2017.07.006

Cited by 35 publications

(17 citation statements)

References 9 publications

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“…A main reason for the lack of research on perception in the domain of mobile assessments is that, in the past, methods in exposure science have been too limited to capture subjective opinions or active user feedback while mobile. Some studies used travel diaries to recall opinions about cycling behavior, but the data were only recorded at the end of the day and could contain erroneous information due to biased memories [30].…”

Section: Introductionmentioning

confidence: 99%

Cyclists’ Multiple Environmental Urban Exposures—Comparing Subjective and Objective Measurements

et al. 2019

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Citizens in urban areas are exposed to multiple environmental stressors like noise, heat, and air pollution, with impact on human health. There is a great deal of evidence that connects human health, objective environmental exposure, and place of residence. However, little is known about subjective and objective multiple personal exposures while being mobile. To address this research gap, this paper presents results from a mixed-methods exploratory study with cyclists in the City of Leipzig, Germany. In the summer of 2017, cyclists (n = 66) wore a unique combination of sensors that measured particle number counts (PNC), noise, humidity, temperature, geolocation, and the subjective perception of each exposure on everyday routes for one week (n = 730). A smartphone application was developed to question participants about their perception of subjective exposure. The data were analyzed with three aims: (i) to compare the multiple exposure profiles of the cyclists, (ii) to contrast the objective data and subjective individual perception, and (iii) to examine the role of route decision-making and awareness of health impacts for healthier route choices. The results indicate distinct differences between the exposure profiles of cyclists. Over 80% of the cyclists underestimated their exposure to noise and air pollution. Except for heat, no significant associations between the objective and subjective data were found. This reveals an exposure awareness gap that needs to be considered in urban health planning and risk communication. It is argued that knowledge about health impacts and route characteristics plays a crucial role in decision-making about route choices. The paper concludes with suggestions to harness smart sensing for exposure mitigation and research in health geography.

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Section: Introductionmentioning

confidence: 99%

Cyclists’ Multiple Environmental Urban Exposures—Comparing Subjective and Objective Measurements

et al. 2019

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“…Recently, an alternative data collection method [35][36][37][38] employing smartphones has emerged. Since most smartphones are equipped with various sensors (GPS and accelerometer), and since smartphones are integrated in the daily life of most people, they provide an unprecedented opportunity for large-scale travel data collection.…”

Section: Discussion Of the Resultsmentioning

confidence: 99%

An Empirical Activity Sequence Approach for Travel Behavior Analysis in Vilnius City

Dumbliauskas

2020

Sustainability

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The approach defines the process of conducting an empirical research of the travel behavior patterns of residents of Vilnius city. It defines survey methodology and important mobility parameters such as activity sequences and their probabilities of homogeneous urban population segments during the weekday. This empirical research is based on a travel diary survey that was planned and executed in cooperation with Vilnius Municipality during preparation of sustainable mobility plan. The following work describes the research object, the questionnaire design, sampling strategy and the analysis of results based on characteristics of respondents. An innovative activity sequence-focused travel behavior research approach designed to collect data for a tour-based travel demand model.

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“…In recent research projects, the feasibility of replacing or complementing the traditional travel diary with a suite of tools that make use of travel data collected smartphone has been studied; for overviews, see Zhao et al ( 5 ) and Berger and Platzer ( 7 ). There have been attempts to make the completion of the whole data collection process on respondents’ mobile (cell) phones either manual or semi-automatic ( 8 – 10 ). In the past two years, more smartphone-based travel surveys were field evaluated and documented ( 11 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…SmartMo is a system that is manually completed on respondents’ mobile phones and was field-tested in 2013 in Austria ( 7 ). Another example is MEILI, a system that includes a smartphone application for capturing the movement of users and a web application that allows the users to annotate their movements; it was tested in Stockholm in 2015 ( 9 ). These systems, although smartphone based, required heavy involvement of participants by providing/verifying the entities and their attributes.…”

Section: Literature Reviewmentioning

confidence: 99%

Enriching Activity-Based Models using Smartphone-Based Travel Surveys

Nahmias-Biran

Han

Bekhor

et al. 2018

Transportation Research Record

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Smartphone-based travel surveys have attracted much attention recently, for their potential to improve data quality and response rate. One of the first such survey systems, Future Mobility Sensing (FMS), leverages sensors on smartphones, and machine learning techniques to collect detailed personal travel data. The main purpose of this research is to compare data collected by FMS and traditional methods, and study the implications of using FMS data for travel behavior modeling. Since its initial field test in Singapore, FMS has been used in several large-scale household travel surveys, including one in Tel Aviv, Israel. We present comparative analyses that make use of the rich datasets from Singapore and Tel Aviv, focusing on three main aspects: (1) richness in activity behaviors observed, (2) completeness of travel and activity data, and (3) data accuracy. Results show that FMS has clear advantages over traditional travel surveys: it has higher resolution and better accuracy of times, locations, and paths; FMS represents out-of-work and leisure activities well; and reveals large variability in day-to-day activity pattern, which is inadequately captured in a one-day snapshot in typical traditional surveys. FMS also captures travel and activities that tend to be under-reported in traditional surveys such as multiple stops in a tour and work-based sub-tours. These richer and more complete and accurate data can improve future activity-based modeling.

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Smartphone based travel diary collection: experiences from a field trial in Stockholm

Cited by 35 publications

References 9 publications

Cyclists’ Multiple Environmental Urban Exposures—Comparing Subjective and Objective Measurements

Cyclists’ Multiple Environmental Urban Exposures—Comparing Subjective and Objective Measurements

An Empirical Activity Sequence Approach for Travel Behavior Analysis in Vilnius City

Enriching Activity-Based Models using Smartphone-Based Travel Surveys

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