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

Abstract

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

Vulnerability Analysis of Urban Rail Transit Networks: A Case Study of Shanghai, China

“…Vulnerabilities of different urban rail transit networks could be analyzed and compared based on the model, and a reliable network geometry could then be obtained. Such a tool can provide theoretical support to the design and optimization of network layout and be used to explore possible improvements to network reliability when new lines are built [29].…”

An analysis of drivers route choice behaviour using GPS data and optimal alternatives

“…To observe routes the researcher have mainly adopted shortest distance and shortest time paths for comparison (see, e.g., Prato and Bekhor, 2006;Jan et al, 2000;Schüssler and Axhausen, 2009;Sun et al, 2014). Shortest paths with turn-penalty and stop lights-penalty have been also used, for instance by Bekhor et al (2006) who evaluated frequent routes using a sample of 188 respondents, corresponding to 91 origin-destination pairs.…”

GIS and Transport Modeling—Strengthening the Spatial Perspective

“…Floating Car Data (FCD), for example, are still sensed within closed systems. Floating car fleets are established for research purposes [50][51][52], but mainly for proprietary services of private data and navigation providers (TomTom (Amsterdam, Netherlands), INRIX (Kirkland, WA, USA) and others).…”