Abstract
This paper introduces a system of real-time Traffic Light (TL) recognition, which is an essential element for unmanned autonomous vehicles when driving through urban city. The system of TL recognition is an integrating system that fuses a binary processing method, a network model method, and an ITS information. By using two algorithms that processes results through a mono camera, we enhance our recognition accuracy when ITS information is not confirmed properly. We evaluated the individual and integrated TL recognition performance of the system in actual testbed to ensure that our system is satisfied the performance for our autonomous driving scenario. The result of the experiment met our autonomous driving scenario conditions.
| Original language | English |
|---|---|
| Pages (from-to) | 102-108 |
| Number of pages | 7 |
| Journal | Journal of Image and Graphics(United Kingdom) |
| Volume | 10 |
| Issue number | 3 |
| DOIs | |
| State | Published - Sep 2022 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 11 Sustainable Cities and Communities
Keywords
- autonomous driving
- deep learning
- image processing
- ITS
- traffic light recognition
Fingerprint
Dive into the research topics of 'Traffic Light Recognition for Autonomous Driving Vehicle: Using Mono Camera and ITS'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver