Comparative framework for activity-travel diary collection systems
2015 (English)In: 2015 International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2015, IEEE conference proceedings, 2015, 251-258 p.Conference paper (Refereed)Text
The needs for cheaper and less intrusive ways to collect activity-travel diaries led scientist to pursue new technologies, e.g., positioning technologies like GPS. While a fully, reliable and widely accepted automatic activity-travel diary collection system is yet to be developed, scientists have presented systems that automate parts of an activity-travel diary collection. In the advent of automated systems, it is important to discuss how to analyse the potential of such systems and how to compare different activity-travel diary collection systems. To achieve this objective, this paper introduces a parallel survey design and a comparison framework for collection systems. The framework can be used as a development tool to optimise system design, to report and monitor progress of different system designs, to objectively weigh benefits in decision making, and to automate systematic analysis. In particular, the framework can be used as a comparison tool to reveal the qualitative difference in the data gathered using different collection systems. To achieve this, the framework defines: 1) a number of activity-travel diary measurement entities (trips and triplegs), entity attributes (e.g., trip purpose, origin / destination, etc.), 2) similarity functions between instances of the same entities, and 3) spatial and temporal quality indices to establish a notion of ground truth. The utility of the proposed framework is demonstrated by analysing the results of a trial survey where data is collected via two activity-travel collection systems: a web-based system (PP) and a smartphone-app-based system (MEILI). PP was collected for one day period and MEILI was used for one week period (with one day overlapping). The results show that half of the trips are captured by both systems, while each system roughly captures the same number of trips as the other. The strengths and weaknesses of MEILI are analysed using the framework on the entire week dataset.
Place, publisher, year, edition, pages
IEEE conference proceedings, 2015. 251-258 p.
activity-travel diary collection, comparison of collection methods, ground truth, spatial and temporal quality indices, Automation, Decision making, Intelligent systems, Intelligent vehicle highway systems, Surveys, Systems analysis, Collection methods, Origin destination, Positioning technologies, Qualitative differences, Similarity functions, Systematic analysis, Temporal quality, Transportation
IdentifiersURN: urn:nbn:se:kth:diva-181605DOI: 10.1109/MTITS.2015.7223264ISI: 000380478600032ScopusID: 2-s2.0-84951044698ISBN: 9789633131428 (print)OAI: oai:DiVA.org:kth-181605DiVA: diva2:912373
International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2015, 3 June 2015 through 5 June 2015
QC 201603162016-03-162016-02-022016-11-03Bibliographically approved