Data · dataset · 2025
APACC Cross-Domain Validation Data (Automotive/Railway)
Listed in Teesside University Research Data Repository
Validation datasets for Artificial Precognition Adaptive Cognised Control (APACC), a neuro-symbolic MIMO control architecture for safety-critical autonomous systems (US Patent 9,645,576 B2).
Description
Automotive domain: 10,000 trials across 8 scenario types (urban intersection, pedestrian crossing, highway merging/overtaking, emergency avoidance, adverse weather) using CARLA simulator with Honda Civic parameters. Compares APACC against PID, MPC, DRL, and Hybrid controllers.
Key result: 51% reduction in peak deceleration vs PID baseline. Railway domain: 168 hours continuous deployment on UK Network Rail infrastructure (Workington–Sellafield route, 32 km) under Government SBRI
Read the rest (3 more)
Project
EDGE. Includes 6,026 telemetry records across 4 MNOs (EE, Vodafone, Three, O2) with Iridium satellite backup, plus 256 handover events. Key result: 94.9% handover prediction accuracy.
Package contains: raw trial data, MIMO telemetry, configuration files (NSSD parameters, fuzzy rulesets, full architecture specification), analysis scripts, and dataset generators for reproducibility. Accompanies manuscripts submitted to IEEE Access and Robotics and Autonomous Systems (Elsevier).
Links
Where it is published
- DOI doi.org/10.17632/vr8pvg398v.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Artificial intelligence · Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/vr8pvg398v.1 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:4602 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Artificial Intelligence'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |