International Journal of Advanced Robotic Systems | |
State-of-the-art Versus Time-triggered Object Tracking in Advanced Driver Assistance Systems | |
关键词: Decentralized Control; High-Order Neural Networks; Extended Kalman Filter; Backstepping; | |
DOI : 10.5772/52348 | |
学科分类:自动化工程 | |
来源: InTech | |
【 摘 要 】
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.
【 授权许可】
CC BY
【 预 览 】
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RO201902189913577ZK.pdf | 849KB | download |