TY  - JOUR
PY  - 2023//
TI  - Development of radar-enabled AI convergence transportation entities detection system for Lv.4 connected autonomous driving in adverse weather
JO  - International journal of advanced smart convergence
A1  - Oh, Myoungho
A1  - Park, Mun-Yong
A1  - Lim, Kwang-Hyun
SP  - 190
EP  - 201
VL  - 12
IS  - 4
N2  - Securing transportation safety infrastructure technology for Lv.4 connected autonomous driving is very important for the spread of autonomous vehicles, and the safe operation of level 4 autonomous vehicles in adverse weather has limitations due to the development of vehicle-only technology. We developed the radar- enabled AI convergence transportation entities detection system. This system is mounted on fixed and mobile supports on the road, and provides excellent autonomous driving situation recognition/determination results by converging transportation entities information collected from various monitoring sensors such as 60GHz radar and EO/IR based on artificial intelligence. By installing such a radar-enabled AI convergence transportation entities detection system on an autonomous road, it is possible to increase driving efficiency and ensure safety in adverse weather. To secure competitive technologies in the global market, the development of four key technologies such as  AI-enabled transportation situation recognition/determination algorithm, ② 60GHz radar development technology, ③ multi-sensor data convergence technology, and ④ AI data framework technology is required.     Keywords: AI data framework, AI-enabled transportation situation recognition/determination algorithm, Lv.4 connected autonomous driving, Multi-sensor data convergence, 60GHz radar<p />  <p>Language: en</p>
LA  - en
SN  - 2288-2847
UR  - http://dx.doi.org/10.7236/IJASC.2023.12.4.190
ID  - ref1
ER  -