Travel Time Prediction by Combining Real-Time and Statistical Data According to Congestion Level Li, Lan ; Liu, Bo ; Mizuta, Hiroaki
Publication details: Bryssel ITS in daily life: 16th world congress and exhibition on intelligent transport systems and services, Stockholm 21-25 September 2009. Paper, 2009Description: 8 sSubject(s): Bibl.nr: VTI P1835:16 [World]Location: Abstract: In recent years, besides real-time traffic data, statistical data based on historical traffic data has also been used as a useful compensation to predict the travel time. According to the research on traffic information quality in some big cities of China, it is found that the accuracy is different between real-time and statistical traffic data, and the comparison result depends on the congestion level (smooth, light and heavy congestion). This paper shows these differences and proposes a method to promote the travel time prediction by combining real-time and statistical data according to the congestion level of each road link.| Current library | Status | |
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| Statens väg- och transportforskningsinstitut | Available |
In recent years, besides real-time traffic data, statistical data based on historical traffic data has also been used as a useful compensation to predict the travel time. According to the research on traffic information quality in some big cities of China, it is found that the accuracy is different between real-time and statistical traffic data, and the comparison result depends on the congestion level (smooth, light and heavy congestion). This paper shows these differences and proposes a method to promote the travel time prediction by combining real-time and statistical data according to the congestion level of each road link.