Abstract
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.
Highlights
In 2009, 397448 people were injured and 4154 people were killed in road accidents in Germany
As soon as object state observations are received by the object tracking subsystem and no task is processed simultaneously, the object position observations can be fused with associated images of the object states (“fusion task”) hereby taking into account the particulars of out‐ of‐sequence measurements
Assuming that all relevant objects are detected by the sensors and that the number of false positives (“ghost” objects) and false negatives is negligible, the mean performance of both models can be expressed by the mean error covariance matrix trace of the real‐time images of the object states
Summary
In 2009, 397448 people were injured and 4154 people were killed in road accidents in Germany. A time‐triggered deterministic bus system establishes a global time‐base and synchronizes the clocks of all nodes, which allows for deterministic sensor scheduling, measurement transmission and processing, and leads to guaranteed accuracy intervals, bounded detection latency for timing and omission errors, replica determinism and temporal composability. This paradigm shift is expected to affect the mean system performance, as the gained temporal determinism may introduce additional delays and demand supplementary hardware resources [32], [47]. Due to the difficulty in accomplishing reproducible conditions for the high number of test drives that would be necessary to produce statistically meaningful results for a set of scenarios in field tests [22], this paper tackles the posed question through simulation
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