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Trajectory Data Analyses for Pedestrian Space-time Activity Study
Published on: February 25, 2013
Dataset on commuting patterns and mode-switching behavior under prospective policy scenarios for public transport
Cristian Toşa1, Tomio Miwa2, Takayuki Morikawa3
1School of Civil Engineering, Technical University of Cluj-Napoca, Romania.
Abstract:
This paper covers a broadly used methodology used in travel behavior research aiming at determining individual and alternative-specific variables that influence the choice of the transportation mode for commuting trips. Data used in the analysis were obtained in July 2015 by means of a computer-assisted telephonic interview survey conducted in Cluj Metropolitan Area, Romania. The survey collected a wide range of day-by-day travel patterns, socioeconomic data, and attitudes and perceptions toward urban transportation services. Given the lack of studies from emerging, post-socialist countries, the survey assigned a section dedicated to an alternative ticketing policy for public transport services in order to evaluate the willingness of commuters to switch to a more sustainable transportation through non-coercive interventions. A revealed preference - stated preference modelling methodology was adopted in order to reveal the role of socioeconomic characteristics, along with features of transport supply and built environment in explaining commuting patterns and forecast sustainable modal splits. Both the survey and the methodology are scalable and flexible to be used, adapted, and applied in a wide range of transport policies regarding modal shifting strategies.
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What is a Mode?
There can be more than one mode in a data set if multiple values have the same highest frequency. For instance, suppose that the Statistics exam scores of 20 students are: 50; 53; 59; 59; 63; 63; 72; 72; 72; 72; 72; 76; 78; 81; 83; 84; 84; 84; 90; 93. Here, the mode is 72, as it occurs most frequently, five times.
A data set with two modes is called bimodal. For example,...
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