Sökning: "travel data collection"

Visar resultat 1 - 5 av 37 avhandlingar innehållade orden travel data collection.

  1. 1. Capturing travel entities to facilitate travel behaviour analysis : A case study on generating travel diaries from trajectories fused with accelerometer readings

    Författare :Adrian Corneliu Prelipcean; Yusak Octavius Susilo; Gyözö Gidofalvi; Stefan van der Spek; KTH; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; travel diary automation; trajectory segmentation; travel data collection; travel diary collection system evaluation and comparison; Geodesy and Geoinformatics; Geodesi och geoinformatik;

    Sammanfattning : 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. LÄS MER

  3. 2. Understanding Human Mobility with Emerging Data Sources: Validation, spatiotemporal patterns, and transport modal disparity

    Författare :Yuan Liao; Chalmers tekniska högskola; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; travel mode; data mining; travel time; mobility; social media data; gravity model; Twitter; geographical information systems;

    Sammanfattning : Human mobility refers to the geographic displacement of human beings, seen as individuals or groups, in space and time. The understanding of mobility has broad relevance, e.g., how fast epidemics spread globally. LÄS MER

  4. 3. MEILI : Multiple Day Travel Behaviour Data Collection, Automation and Analysis

    Författare :Adrian Corneliu Prelipcean; Yusak Octavius Susilo; Gyözö Gidofalvi; Zachary Pattersson; KTH; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; multiple day travel diary collection; trajectory segmentation; travel mode destination and purpose inference; travel diary collection system comparison; travel pattern stability and variability over time; Transportvetenskap; Transport Science; Computer Science; Datalogi; Geodesy and Geoinformatics; Geodesi och geoinformatik;

    Sammanfattning : Researchers' pursuit for the better understanding of the dynamics of travel and travel behaviour led to a constant advance in data collection methods. One such data collection method, the travel diary, is a common proxy for travel behaviour and its use has a long history in the transportation research community. LÄS MER

  5. 4. Understanding Mobility and Transport Modal Disparities Using Emerging Data Sources: Modelling Potentials and Limitations

    Författare :Yuan Liao; Chalmers tekniska högskola; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; data mining; geographical information systems; mobility models; big trip data; transport modes; traffic data; social media data;

    Sammanfattning : Transportation presents a major challenge to curb climate change due in part to its ever-increasing travel demand. Better informed policy-making requires up-to-date empirical mobility data to model viable mitigation options for reducing emissions from the transport sector. LÄS MER

  7. 5. Human mobility behavior : Transport mode detection by GPS data

    Författare :Paria Sadeghian; Johan Håkansson; Xiaoyun Zhao; Kenneth Carling; Gyözö Gidofalvi; Högskolan Dalarna; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Transport mode detection; Machine learning; Statistical learning; Rule-based method; Data labeling;

    Sammanfattning : GPS tracking data are widely used to understand human travel behavior and to evaluate the impact of travel. A major advantage with the usage of GPS tracking devices for collecting data is that it enables the researcher to collect large amounts of highly accurate and detailed human mobility data. LÄS MER