Traffic Mining Applied to Police Activities

Proceedings of the 1st Italian Conference for the Traffic Police (TRAP- 2017)

  • Fabio Leuzzi
  • Stefano Ferilli
Conference proceedings TRAP 2017

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 728)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Invited Talks

  3. Technical Contributions

    1. Front Matter
      Pages 17-17
    2. Fabio Leuzzi, Emiliano Del Signore, Rosanna Ferranti
      Pages 19-35
    3. Jinzhi Liao, Xiang Zhao, Jiuyang Tang, Chong Zhang, Mingke He
      Pages 69-82
    4. Jose Manuel Rodriguez-Jimenez, Jesus Cabrerizo, Dario Perez, Ignacio Sanchez
      Pages 83-95
    5. Massimo Bernaschi, Alessandro Celestini, Stefano Guarino, Flavio Lombardi, Enrico Mastrostefano
      Pages 97-114
    6. Samuele Capobianco, Luca Facheris, Fabrizio Cuccoli, Simone Marinai
      Pages 115-128
    7. Massimo Bernaschi, Alessandro Celestini, Stefano Guarino, Flavio Lombardi, Enrico Mastrostefano
      Pages 129-143
    8. Fabio Fumarola, Pasqua Fabiana Lanotte
      Pages 145-153
  4. Back Matter
    Pages 155-155

About these proceedings

Introduction

This book presents high-quality original contributions on the development of automatic traffic analysis systems that are able to not only anticipate traffic scenarios, but also understand the behavior of road users (vehicles, bikes, trucks, etc.) in order to provide better traffic management, prevent accidents and, potentially, identify criminal behaviors. Topics also include traffic surveillance and vehicle accident analysis using formal concept analysis, convolutional and recurrent neural networks, unsupervised learning and process mining. The content is based on papers presented at the 1st Italian Conference for the Traffic Police (TRAP), which was held in Rome in October 2017. This conference represents a targeted response to the challenges facing the police in connection with managing massive traffic data, finding patterns from historical datasets, and analyzing complex traffic phenomena in order to anticipate potential criminal behaviors. The book will appeal to researchers, practitioners and decision makers interested in traffic monitoring and analysis, traffic modeling and simulation, mobility and social data mining, as well as members of the police.

Keywords

Traffic Surveillance Vehicle Accident Analysis Traffic Classification Data Traffic Analysis Traffic Analysis Systems Traffic Data Collection Automatic Number Plate Reading Systems Police Investigations TRAP 2017

Editors and affiliations

  1. 1.Italian National PoliceRomeItaly
  2. 2.University of BariBariItaly

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-75608-0
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-75607-3
  • Online ISBN 978-3-319-75608-0
  • Series Print ISSN 2194-5357
  • Series Online ISSN 2194-5365
  • About this book