Abstract In order to handle the increasing volume of traffic, measures are required which help optimising the use of existing transport infrastructure and avoid further upgrading and construction of new road infrastructure. To control traffic, knowledge about its flows and travel times is of great importance. The present study examines whether the travel time can be sufficiently described by statistical models based on cross section count data. Data derived from the research project "Travel Time Regcognition B17" which has been commissioned by ITS Vienna Region and processed by AIT (Austrian Institute of Technology), Mobility Department. In the course of the project the travel time of vehicles has been measured by automatic number plate recognition on four cross sections on B17 northwards. Furthermore, on these cross sections traffic counts have been carried out. Thus it has been possible to analyse the correlation of travel times and data of traffic counts. For each section between the four cross sections a multiple regression model has been developed which bases on a capacity restrain function. It became evident that these models describe travel times well. However, many peaks which were shown in the course of travel time could not be explained by the variables used in the models. To find explanations for these peaks, further possible factors that might have an influence on travel time have been examined. The results showed that the models cannot be used for routes which are very inhomogenous and that they cannot replace measurement of travel time for high-quality telematic tools. However, the results of the models developed in this study can help to improve the measurement of travel time.
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|Publikationsstatus||Veröffentlicht - 2010|
- Ehemaliges Research Field - Mobility Systems