  Measuring and analyzing sensor data is the basic technique in vehicle
dynamics development and with the advancement of embedded and data acquisition
systems it is possible to analyze large data sets. In this paper a detailed
method is presented for assessing and mapping isochronous trajectory patterns
in Graz (Austria) by using data fusion from video, ArduinoUno and the compass
sensor HDMM01. The predictive isochronous trajectory patterns are derived from
the data values for a predefined time horizon. Both extreme driving behavior
and hazardous road geometries can be identified. It is possible to provide
instant road sensor data which can be used to compare the data from a
trajectory path as well as for different time instances. Results of this study
show that the trajectory patterns are successful in predicting the likely
evolution of a current trajectory pattern and can provide assessment on future
driving situations. The obtained data from this study can be useful as
reference in future city planning for energy saving driving pathways as well as
vehicle design and engineering improvements based on quantitative and relevant
dynamic measurements.
