Urban travel behavior analyses and route prediction based on floating car data

摘要: The lack of sufficient data is the result inherent complexity gathering and subsequently analyzing route choice behavior, which unfortunately hasn’t been revealed much by existing literatures. With assistance GIS technology taxi-based floating car data, authors found that majority urban drivers would not travel along shortest or fastest paths. This paper studies factors influence commuters’ switching based on objective real-world observations behavior. Possible may affect driver’s are then analyzed regression methods were introduced to attain if there a clear quantitative relationship between drivers’ these factors. indicates such connection difficult be established. Consequently, eight scenarios proposed quantify various potential Analysis shows distance, time road preference have comparable higher choice. To this end, new prediction model proposed, adopting usage as weight route’s length constraints. was implemented validated using FCD Shenzhen, China. results indicate combining external with personal preference, predicted has matching ratio actual one, consequently effectiveness model.