In-vehicle Data Mining

In-Vehicle Data Mining is a computational methodology within telematics analytics that involves the systematic extraction, analysis, and interpretation of vehicle-generated data streams to uncover latent patterns, behaviors, and insights specific to vehicular operations and driver dynamics.

66

Publications

3.1K

Citations

221

Authors

98

Institutions

Publications per year

2017–2026

43

Authors

221

  1. MV
    Mario V. Wüthrich

    ETH Zurich, Switzerland

    3 publications · 110 citations

    3

    h-index

  2. GG
    Guangyuan Gao

    Renmin University of China, China

    3 publications · 89 citations

    3

    h-index

  3. AC
    Ashok Chaitanya Koppisetty

    Volvo Cars (Sweden)

    2 publications · 44 citations

    2

    h-index

  4. KN
    Kazunari Nawa

    Toyota Motor Corporation (Switzerland), Switzerland

    2 publications · 31 citations

    2

    h-index

  5. MP
    Marina Papatriantafilou

    Chalmers University of Technology, Sweden

    2 publications · 44 citations

    2

    h-index

1–5 of 221

Venues

  1. Accident Analysis & Prevention

    4 publications · 184 citations

    5

    h-index

  2. 4

    h-index

  3. Transportation Research Interdisciplinary Perspectives

    TRIP · 2 publications · 40 citations

    2

    h-index

  4. 2

    h-index

  5. European Actuarial Journal

    2 publications · 99 citations

    2

    h-index

1–5