A Unity-Based Digital Twin for Preliminary System Design of Multi-Lane License Plate Recognition
1st International Conference on Emerging Technologies and Engineering Systems, ICETES 2026, Hybrid, Amman, Ürdün, 7 - 09 Nisan 2026, ss.372-377, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/icetes68504.2026.11518718
- Basıldığı Şehir: Hybrid, Amman
- Basıldığı Ülke: Ürdün
- Sayfa Sayıları: ss.372-377
- Anahtar Kelimeler: Camera Placement, Digital Twin, License Plate Recognition Systems (LPRS), Preliminary System Design, Unity Simulation
- Gazi Üniversitesi Adresli: Evet
Özet
License Plate Recognition Systems (LPRS) are a core component of smart city, smart building, and security solutions. On public multi-lane roads where lane reduction is impractical, the conventional solution relies on gantry installations spanning all lanes with per-lane cameras and auxiliary illumination, which increases installation time and cost. This paper presents a simulation-only Unity-based digital twin for preliminary system design of multi-lane LPRS camera layouts. A three-lane roadway is modeled with four layout scenarios: (i) gantry with one camera per lane, (ii) right-side roadside single camera, (iii) left-side roadside single camera, and (iv) dual-side roadside cameras with a union-based sensor fusion rule. Lane-based vehicle passages are generated, and within a defined read zone each passage is evaluated using measurable proxy criteria (plate pixel footprint and view angle), producing per-lane success counts and success rates. Results show a critical failure mode for single-side roadside layouts in the evaluated three-lane geometry, yielding 0% success for one lane, whereas the dual-side configuration with union fusion achieves lane-level performance close to the gantry baseline across the tested traffic regimes (e.g., 81.7% vs. 80.7% lane-average success under crowded traffic settings). These findings indicate that the proposed digital-twin workflow can support early-stage layout decisions and help screen feasible roadside alternatives before field deployment, reducing the need for costly trial-and-error installation and on-site tests.