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Microscopic Car Modeling for Intelligent Traffic and Scenario Generation in the UCF Driving Simulator : Year 2
  • Published Date:
    2000
  • Language:
    English
Filetype[PDF-512.28 KB]


Details:
  • Creators:
  • Resource Type:
  • Geographical Coverage:
  • TRIS Online Accession Number:
    800178
  • NTL Classification:
    NTL-HIGHWAY/ROAD TRANSPORTATION-HIGHWAY/ROAD TRANSPORTATION ; NTL-OPERATIONS AND TRAFFIC CONTROLS-Traffic Flow
  • Format:
  • Abstract:
    A multi-year project was initiated to introduce autonomous vehicles in the University of Central Florida (UCF) Driving Simulator for real-time interaction with the simulator vehicle. This report describes the progress during the second year. In the first two years, a traffic network consisting of several one and two-way roads, an outer loop and intersections with traffic control devices was created and populated with vehicles moving in a random manner. The network is completely defined in terms of a set of nodes and links. Using a Windows PC, the scientific and engineering program MATLAB was used to calculate positions and headings of the simulated vehicles with respect to the link/node coordinate system of the network. MATLAB was chosen because of its powerful data analysis, visualization and programming environment, extensive library of mathematical functions and its capability to produce easily customizable Graphical User Interfaces (GUIs). Initial traffic densities on the links are set by the user, as are the arrival patterns of new vehicles entering the network at the source nodes. An onscreen map of the network displaying the simulated traffic movement, with zoom and scroll is useful for off-line software development purposes. The link/node vehicle coordinates are transformed in the PC to x,y and heading coordinates for communication to the simulation control program running in the host computer. The traffic generation frame rate is a function of the number of cars and other factors, which affect the computational load on the PC. Traffic generation output is interpolated to synchronize with the basic simulator frame rate, which is dictated by the vehicle dynamics model. During the last year, some intelligence has been added to the driving patterns of the ambient traffic. This report describes the algorithms employed to accomplish this. It concludes with a brief discussion of the remaining work to achieve a fully interactive driving simulator with intelligent traffic. 4 Figures, 9 p.

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