• Medientyp: E-Book; Dissertation; Elektronische Hochschulschrift
  • Titel: Simulation of Spatial Learning Mechanisms
  • Beteiligte: Weinmann, Siegfried [VerfasserIn]
  • Erschienen: ETH, 2013
  • Sprache: Englisch
  • DOI: https://doi.org/20.500.11850/75151; https://doi.org/10.3929/ethz-a-010039157
  • Schlagwörter: GEOMETRIC REASONING + SPATIAL REASONING (ARTIFICIAL INTELLIGENCE) ; Data processing ; MASCHINELLES LERNEN (KÜNSTLICHE INTELLIGENZ) ; GEOMETRISCHES SCHLIESSEN + RÄUMLICHES SCHLIESSEN (KÜNSTLICHE INTELLIGENZ) ; computer science ; MACHINE LEARNING (ARTIFICIAL INTELLIGENCE)
  • Entstehung:
  • Anmerkungen: Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
  • Beschreibung: The evolution of information technology brings an entirely new perspective to old issues of transportation and the problem of overloaded road traffic networks. At the forefront of progress in the field of information technology is the opportunity for the driver to acquire knowledge through media. The present study is aimed at investigating effects of spatial orientation in typical situations. To this end, it starts out from the following exemplary scenario: Traffic in the Zurich metropolitan area is congested. Vehicles often move at walking pace. Traffic demand leads to an average volume of 118 vehicles per kilometer. Every driver has planned his itinerary with the help of an off-the-shelf navigation device and sticks to his shortest route. In view of this situation, the question investigated in this study is: How much will the traffic situation improve if part of the drivers use real-time navigation information (such as may be available via smartphone)? The research to answer this question proceeds on the assumption that a driver behaves either in a “conventional” or in a “progressive” manner. The conventional drivers move along on the route they perceived as the shortest one when they planned it before starting on their trip. The progressive drivers are informed about the current traffic situation and head for their destination dynamically by choosing the currently most advantageous link at each traffic node on their trip. The decision processes of the informed drivers will be mapped in a simplified form and microscopically simulated using the MATSim software. A model postulated for the route choice describes the behavior of drivers guided by real-time navigation information, but not obstinately following it; their experience regarding the reliability of the traffic information also influences their route choice. The model analyzes how differing knowledge levels and modes of behavior of the drivers affect the state of the traffic system in the real-world setting of the Zurich metropolitan area. The results of ...
  • Zugangsstatus: Freier Zugang
  • Rechte-/Nutzungshinweise: Urheberrechtsschutz - Nicht kommerzielle Nutzung gestattet