Exact(7)
This paper aims to examine the accuracy of journeys simulated by an activity-based travel simulator, FEATHERS Seoul (FS), against smartcard and car navigation device data collected in Seoul.
Thomas Demand's big color photographs of a dense forest interior and an Apollo space travel simulator -- things that look real but turn out to be carefully constructed of paper, plastic and other inexpensive materials -- are as visually magical and philosophically provocative as ever.
This paper proposes a travel simulator for collecting behavioral data on driver response to GRIP.
The development of this tool has been strongly influenced by an existing one, the Travel Simulator Laboratory or TSL [22, 25], developed at the Delft University of Technology.
The results imply that an activity-based travel simulator needs to improve its incorporation of geographical characteristics using big data engineering to enhance the simulated travel accuracy.
For example, accurate information regarding travel time, link traffic volume and trip distribution is essential for sensitivity analysis using an activity-based travel simulator.
Similar(53)
Activity-based travel simulators have been experiencing difficulty obtaining high quality activity-travel data and network information, which limits the applicability of the simulator to real world problems.
Travel simulators have been adopted in several cases in order to carry out SP experiments [1, 3, 4, 6, 11, 21, 29].
The aim of this paper is to ascertain whether and to what extent the way data are collected and used can affect the interpretation of experimental results obtained by stated preference (SP) surveys based on the use of travel simulators and applied through repeated choices.
The demand simulator simulates network-wide demand patterns through time-dependent origin destination (OD) matrices, and captures the travel choices of individual motorists (e.g. route choice).
At the beginning of the simulation the simulator allocates a pattern of travel for each EV.
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