TY - GEN
T1 - Lightweight Collaboration of Detecting and Tracking Algorithm in Low-Power Embedded Systems for Forward Collision Warning
AU - Hong, Sunghoon
AU - Park, Daejin
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/8/17
Y1 - 2021/8/17
N2 - The cause of the majority of vehicle accidents is a safety issue due to the driver's inattention, such as drowsy driving. A forward collision warning system (FCWS) can significantly reduce the number and severity of accidents by detecting the risk of collision with vehicles in front and providing an advanced warning signal to the driver. This paper describes a low power embedded system based FCWS for highway safety. The algorithm described in this paper computes time to collision (TTC) through detection, tracking, distance calculation for the vehicle ahead and current vehicle speed information with a single camera. Additionally, in order to operate in real time even in a low-performance embedded system, an optimization technique in the program with high and low levels will be introduced. The system has been tested through the driving video of the vehicle in the embedded system. As a result of using the optimization technique, the execution time was about 170 times faster than that when using the previous non-optimized process.
AB - The cause of the majority of vehicle accidents is a safety issue due to the driver's inattention, such as drowsy driving. A forward collision warning system (FCWS) can significantly reduce the number and severity of accidents by detecting the risk of collision with vehicles in front and providing an advanced warning signal to the driver. This paper describes a low power embedded system based FCWS for highway safety. The algorithm described in this paper computes time to collision (TTC) through detection, tracking, distance calculation for the vehicle ahead and current vehicle speed information with a single camera. Additionally, in order to operate in real time even in a low-performance embedded system, an optimization technique in the program with high and low levels will be introduced. The system has been tested through the driving video of the vehicle in the embedded system. As a result of using the optimization technique, the execution time was about 170 times faster than that when using the previous non-optimized process.
KW - Forward collision warning system
KW - hardware-software acceleration
KW - low-power vision processing
KW - object detection
UR - http://www.scopus.com/inward/record.url?scp=85113943661&partnerID=8YFLogxK
U2 - 10.1109/ICUFN49451.2021.9528771
DO - 10.1109/ICUFN49451.2021.9528771
M3 - Conference contribution
AN - SCOPUS:85113943661
T3 - International Conference on Ubiquitous and Future Networks, ICUFN
SP - 159
EP - 162
BT - ICUFN 2021 - 2021 12th International Conference on Ubiquitous and Future Networks
PB - IEEE Computer Society
T2 - 12th International Conference on Ubiquitous and Future Networks, ICUFN 2021
Y2 - 17 August 2021 through 20 August 2021
ER -