Abstract
Abstract
In many Austrian regions the subordinate road network plays an important role.
There is, however, presently almost no traffic information available for roads of this
category. Due to the heterogeneity of such roadways a prognosis of overall journey
time from cross section count data, as is often done on the superior network, is
difficult. In the course of a project conducted at arsenal research the traffic situation
of a section of the B20, the "Mariazeller Bundesstraße", was analyzed. Overall
journey time was calculated based on automatic number plate recognition, while
simultaneously retrieving cross section count data with radar sensors at the starting
and end point of the stretch respectively. The mainpart of this study is dedicated to
the analysis of the impact of different traffic and non-traffic related data on the
journey times. Based on capacity restraint functions a model for calculating overall
journey time from cross section count data as well as from non-traffic related data
(e.g. weather data) was developed. It was found that the traffic volume detected at
the cross section had the biggest influence on the journey time of the about 14 km
long stretch. The model could forecast the average journey time quite well, the high
variance of the data (delays higher than five minutes), however, not. This study can
be seen as an important basis in the direction of an integral image of the traffic
situation that supplies traffic information on and predictions for different categories of
roads.
Original language | German |
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Awarding Institution |
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Supervisors/Advisors |
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Publication status | Published - 2008 |
Research Field
- Former Research Field - Mobility Systems
Keywords
- ANPR Automatic Number Plate Recognition