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Application of automated video analysis to road user behaviour

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Author

Summary, in English

The successful planning, design and management of a traffic system is impossible without knowledge of how the traffic environment affects the behaviour of road users and how the behaviour is related to the main qualities of the traffic system (e.g. safety, efficiency). Automated video analysis is a promising tool for traffic behaviour research in that it enables collection of micro-level behaviour data for large populations of road users and provides a detailed description of their motion. This thesis describes the tests done with an automated video analysis system developed at Lund University. The system was used in two large scale studies with the main task of detecting the presence of road users of a particular type. Accuracy of position and speed estimates were tested in a study specially designed for that purpose. The thesis also elaborates on the problem of relating the behaviour of road users to safety and proposes organising all the elementary events in traffic (defined here as encounters between two road users) into a severity hierarchy. The process of an encounter is described with a set of continuous safety indicators that can handle the various approach angles and transfer between being and not being on a collision course. When an objective measure for an encounter severity is found, the severity hierarchies may be used not only for describing safety but also for studying the balance between safety and other qualities valued by road users.

Publishing year

2010

Language

English

Document type

Dissertation

Topic

  • Infrastructure Engineering

Keywords

  • safety indicators
  • traffic safety
  • traffic conflicts
  • Video analysis
  • road user behaviour

Status

Published

Supervisor

  • Christer Hydén
  • Åse Svensson

ISBN/ISSN/Other

  • ISBN: 978-91-628-8003-3

Defence date

29 January 2010

Defence time

10:15

Defence place

Room V:B, V-building, John Ericssons väg 1, Lund University Faculty of Engineering

Opponent

  • Oliver Carsten (Professor)