A Kalman filter based on single-clothoid and new road model uses these offsets as measurements and estimates road geometry. The estimated road geometry is compared to the simulated road geometry and errors computed. The performance of this model is currently being evaluated on roads obtained from the NavTech database. HRL has also developed an adaptive Kalman filter approach for road geometry and host state estimation which is superior to a conventional Kalman filter. The adaptive Kalman filter performs better during sharp transitions in road geometry compared to a conventional Kalman filter.
Performance evaluation using real data is in progress.
We developed a fuzzy-rule based algorithm to estimate driver distraction. The data fusion subsystem provides an estimate of driver distraction by monitoring if the driver is performing a secondary task. In our working model, there are two major categories of secondary tasks that may affect driver situation awareness. The first one is a simple task that just requires one glance to complete the necessary visual aspect. The second one is complex and requires many short sampling glances away from the forward view.