Adaptions for Automotive Radar Based Occupancy Gridmaps

Prophet R, Stark H, Hoffmann M, Sturm C, Vossiek M (2018)


Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2018

Publisher: IEEE

Event location: Munich DE

DOI: 10.1109/icmim.2018.8443484

Abstract

Environment models are necessary for autonomous driving. The distinction between drivable and non-drivable underground is elementary. This paper presents adaptions for radar based occupancy gridmaps, which are a common representation of the environment. In contrast to standard occupancy gridmaps or in general standard inverse radar sensor models, our approach works with velocity dependent parameters and extends free space calculations. Consequently, the map quality varies less and the information content of the ego vehicle's immediate vicinity is higher. Experiments with ground truth data show that the proposed algorithm produces accurate environment models in urban scenes.

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How to cite

APA:

Prophet, R., Stark, H., Hoffmann, M., Sturm, C., & Vossiek, M. (2018). Adaptions for Automotive Radar Based Occupancy Gridmaps. In Proceedings of the IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM 2018). Munich, DE: IEEE.

MLA:

Prophet, Robert, et al. "Adaptions for Automotive Radar Based Occupancy Gridmaps." Proceedings of the IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM 2018), Munich IEEE, 2018.

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