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As vehicle and computer technology are more and more merging, new forms of assistance and automation in vehicles open up the potential to increasing safety and improving comfort. In HAVEit, an EU-FP7 Integrating Project, car and truck manufacturers, suppliers and research organizations explore highly automated driving applications, where the automation can take over substantial parts of the driving task, but where the driver is still in the loop. The interaction between the human and such an automation becomes a crucial part for a successful, dynamic balance between human and machine. Starting with design explorations, generic interaction and display schemes for highly automated driving were derived, implemented, tested in assessments and experiments, and finally applied to the demonstrator vehicles of HAVEit.

This paper presents an evaluation method for the accuracy of automotive occupancy grids and results for the influence of the discretization and pose estimation of a radar based grid mapping algorithm. An automotive centric review of evaluation methods and map quality measures developed for robotic applications is given. Based on the results of the review, an extensible toolset to create ground truth maps and to compare them against automotive grid maps using different map quality measurements is proposed. Several map quality measures are compared and the best performing method to evaluate the accuracy of a radar based occupancy grid mapping algorithm is chosen.

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