Safety application specific requirements on the data processing of environmental sensors

Jordan, Rüdiger; Lucas, Bernhard; Randler, M.; Wilhelm, Ulf

doi:10.1109/ivs.2004.1336506

Cited by 3 publications

(1 citation statement)

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“…As a result, the lowest possible accuracy level of object state observations, the maximum object state evolution and the maximum system latency that can occur in an advanced driver assistance system have to be taken into account when determining which feature specific accuracy demand can be satisfied [34]. Because the accuracy level of an object state observation from a single-sensor may be subject to fluctuations [49], [7], [28], single-sensor advanced driver assistance systems are often limited to low feature service specific accuracy demands. One approach to deal with this problem comprises updating the real-time images of the object states with redundant object state observations derived from heterogeneous sensors [16], [14].…”

Section: Introductionmentioning

confidence: 99%

State-of-the-art Versus Time-triggered Object Tracking in Advanced Driver Assistance Systems

Koplin

Elmenreich

2013

International Journal of Advanced Robotic Systems

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Most state-of-the-art driver assistance systems cannot guarantee that real-time images of object states are updated within a given time interval, because the object state observations are typically sampled by uncontrolled sensors and transmitted via an indeterministic bus system such as CAN. To overcome this shortcoming, a paradigm shift toward time-triggered advanced driver assistance systems based on a deterministic bus system, such as FlexRay, is under discussion.In order to prove the feasibility of this paradigm shift, this paper develops different models of a state-of-the-art and a time-triggered advanced driver assistance system based on multi-sensor object tracking and compares them with regard to their mean performance. The results show that while the state-of-the-art model is advantageous in scenarios with low process noise, it is outmatched by the time-triggered model in the case of high process noise, i.e., in complex situations with high dynamic.

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