Autonomous Vehicle Navigation and Communication by Passive Radio Frequency (RFID) Tags
Bibliographic record
Abstract
This paper assesses the feasibility of using Passive UHF Radio-Frequency Identity (RFID) tags to augment the existing technologies for Autonomous Vehicle (AV) limitations such as camera occlusions, traffic-sign tempering, and spotty GPS signals interrupting AV localization. The study finds the Received Signal Strength Indicator (RSSI) and the number of tag reads in various propagation mediums such as Ice, Water, and Snow with single and dual-antenna configurations. A reader was mounted onto the AV, and readings were collected by driving it over the tags. Experiments were conducted with an AV on a test track with speeds up to 90 km/h. Due to the track constraints, speeds higher than that could not be tried. One research, however, was able to read the Passive tags up to 200 km/h. This paper finds that the technology in its current form is suitable for controlled indoor and confined environments. However, if more antennas and readers are experimented with - and more Passive RFID equipment is developed for AVs, it could show promise against the current AV limitations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".