Operating-Condition Residual Normalization: A Bio-Inspired Operator for Sensor Integrity Monitoring in Automated Vehicles
Mehmet Bilban, Onur İnan · 2026
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Description
Mehmet Bilban and Onur İnan presented a method to watch sensor health in self-driving vehicles in 2026. Reports of such monitors often give one pooled score, which mixes how well the method works with how the test was run. Their approach borrows a principle from biology about signals the body expects from its own motion.
A simple forward model of the vehicle is fit from data, and its error signal is scaled by operating state. Across a large sample from five towns and four road grip levels, that scaling step gained more score than the detection rule and other parts combined. The monitor reached high precision with a low false alarm rate under their counting rules.
Catalog record
| CREATOR | Mehmet Bilban, Onur İnan |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 75 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |