Intelligent Transportation Systems aims at improving efficiency and safety of the transportation system by acting either on vehicle performances or assisting the driver with information on vehicle and traffic status. Although digital road graphs are available to derive quantitative parameters that describe the road geometry, the information provided usually includes speed limits and repetition of road signs. On the other hand, a huge amount of data is available on individual vehicle speeds and trajectories collected as Floating Car Data (FCD) but they are not combined with road parameters to derive information on how drivers perceive the infrastructure and behave when traveling on it.
In the proposed research, a methodology will be studied to evaluate the consistency between drivers' behavior and a theoretical safety speed determined from road geometry.
The research will be addressed to several possible applications to compare the posted speed limits applied in horizontal curves with the estimated safety speed and review them, if necessary and confirmed by the assessment of safety against other criteria; consider the need for further interventions other than the posted speed limits if they demonstrated to be breached by significant fractions of drivers; rank the roads with respect to the safety indices in order to plan a review of posted speed limits and other possible interventions aimed at increasing the road safety.
This analysis will carry out a comparison between the estimated safety speed values with accident data to verify which percentile is significantly correlated with the actual accident occurrences and to adjust the hypothesized values of the parameters used to determine the safety speed, such as side friction and superelevation, to maximize the correlation with the accidence occurrence or with a more general indicator of potential accidents.
The research innovation respect to the state of the art mainly consists in:
- Comparing different data sources, digital graphs, that provides an approximate representation of road geometry, and real trajectory data collected in the field that represent the actual drivers' trajectories
- A statistical analysis of drivers speeds carried out in the two spatial and temporal dimensions with high granularity derived from a Big Floating Car dataset.
- The research gets a high potentiality to achieve significant improvement with respect to the current state of the art because:
- it is based on a Big Floating Car dataset, obtained from a fleet of 30,000 vehicles equipped with a GPS device that provides the position and instantaneous speed of the vehicles, measured every 30s, for one year;
- the method is applicable to ancient roads whose geometric was not designed according to standard guidelines, that represent a large portion of the Italian infrastructures and have been neglected by most studies in the international literature.
By exploiting data collected by GPS-equipped vehicles owned by private drivers it will be possible, on one hand, to observe the real driving behavior on the road in different conditions on a large sample of drivers and, on the other hand, to perform a pervasive analysis on a large part of the roads of Latium Region, approximatively over 1000 km.