Multi-sensor Data Fusion in Automotive Applications

Herpel T, Lauer C, German R, Salzberger J (2008)

Publication Type: Conference contribution

Publication year: 2008

Edited Volumes: Proceedings of the 3rd International Conference on Sensing Technology, ICST 2008

Pages Range: 206-211

Conference Proceedings Title: Proc. of 3rd Intern. Conf. on Sensing Technology

Event location: Tainan, Taiwan TW

DOI: 10.1109/ICSENST.2008.4757100


The application of environment sensor systems in modern - often called "intelligent" - cars is regarded as a promising instrument for increasing road traffic safety. Based on a context perception enabled by well-known technologies such as radar, laser or video, these cars are able to detect threats on the road, anticipate emerging dangerous driving situations and take proactive actions for collision avoidance. Besides the combination of sensors towards an automotive multi-sensor system, complex signal processing and sensor data fusion strategies are of remarkable importance for the availability and robustness of the overall system. In this paper, we consider data fusion approaches on near-raw sensor data (low-level) and on pre-processed measuring points (high-level). We model sensor phenomena, road traffic scenarios, data fusion paradigms and signal processing algorithms and investigate the impact of combining sensor data on different levels of abstraction on the performance of the multi-sensor system by means of discrete event simulation. © 2008 IEEE.

Authors with CRIS profile

Involved external institutions

How to cite


Herpel, T., Lauer, C., German, R., & Salzberger, J. (2008). Multi-sensor Data Fusion in Automotive Applications. In Proc. of 3rd Intern. Conf. on Sensing Technology (pp. 206-211). Tainan, Taiwan, TW.


Herpel, Thomas, et al. "Multi-sensor Data Fusion in Automotive Applications." Proceedings of the (ICST 2008), Tainan, Taiwan 2008. 206-211.

BibTeX: Download