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Lessons from a trial of MEILI, a smartphone based semi-automatic activity-travel diary collector, in Stockholm city, Sweden
KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.ORCID iD: 0000-0001-7124-7164
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics. (Geoinformatics)ORCID iD: 0000-0002-0916-0188
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics. (Geoinformatics)ORCID iD: 0000-0003-1164-8403
Sweco.
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

This paper describes the lessons learned from the trial of MEILI, a smartphone based semi-automatic activity-travel diarycollection system, in Stockholm city, Sweden. The design of the system, together with state-of-the-art improvements of different elements of the tool, are presented before and after the trial to better illustrate the improvements based on the lessons learned. During the trial, both MEILI and a paper-based diary captured about 65% of the total number of detected trips, but only about half of the trips were captured by both systems. The unmatchable trips are partly due to different activity declaration and system specific destination specification, i.e., a verbose specification of address in the paper-and-pencil survey and a point of interest selection / declaration in MEILI. In terms of subjective appreciation, the user experiences vary greatly between the different participants in the pilot. Presumably, this is mainly due to different level of IT-knowledge of the respondents, but also due to the occasionally non-uniform behaviour of the location collection service caused by hardware and / or software difficulties. Based on these inputs, further web and support system improvements have been implemented for future trials.

Keyword [en]
smartphone based survey; semi-automatic travel diary collection system; activity-travel diary; destination and purpose inference; travel mode detection
National Category
Transport Systems and Logistics
Research subject
Transport Science; Geodesy and Geoinformatics
Identifiers
URN: urn:nbn:se:kth:diva-187489OAI: oai:DiVA.org:kth-187489DiVA: diva2:930571
Projects
TRV 2014/10422
Note

QC 20160525

Available from: 2016-05-24 Created: 2016-05-24 Last updated: 2016-05-25Bibliographically approved
In thesis
1. Capturing travel entities to facilitate travel behaviour analysis: A case study on generating travel diaries from trajectories fused with accelerometer readings
Open this publication in new window or tab >>Capturing travel entities to facilitate travel behaviour analysis: A case study on generating travel diaries from trajectories fused with accelerometer readings
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The increase in population, accompanied by an increase in the availability of travel opportunities have kindled the interest in understanding how people make use of the space around them and their opportunities. Understanding the travel behaviour of individuals and groups is difficult because of two main factors: the travel behaviour's wide coverage, which encompasses different research areas, all of which model different aspects of travel behaviour, and the difficulty of obtaining travel diaries from large groups of respondents, which is imperative for analysing travel behaviour and patterns.

A travel diary allows an individual to describe how she performed her activities by specifying the destinations, purposes and travel modes occurring during a predefined period of time. Travel diaries are usually collected during a large-scale survey, but recent developments show that travel diaries have important drawbacks such as the collection bias and the decreasing response rate. This led to a surge of studies that try to complement or replace the traditional declaration-based travel diary collection with methods that extract travel diary specific information from trajectories and auxiliary datasets.

With the automation of travel diary generation in sight, this thesis presents a suitable method for collecting data for travel diary automation (Paper I), a framework to compare multiple travel diary collection systems (Paper II), a set of relevant metrics for measuring the performance of travel mode segmentation methods (Paper III), and applies these concepts during different case studies (Paper IV).

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2016. 88 p.
Series
TRITA-SOM, ISSN 1653-6126 ; 2016-05
Keyword
travel diary automation, trajectory segmentation, travel data collection, travel diary collection system evaluation and comparison
National Category
Transport Systems and Logistics Computer Science Human Geography
Research subject
Geodesy and Geoinformatics
Identifiers
urn:nbn:se:kth:diva-187491 (URN)978-91-7595-958-0 (ISBN)
Presentation
2016-06-07, L1, Drottning Kristinas väg 30, Stockholm, 09:00 (English)
Opponent
Supervisors
Note

QC 20160525

Available from: 2016-05-25 Created: 2016-05-24 Last updated: 2016-05-25Bibliographically approved

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