TY - GEN
T1 - State observation and communication for cloud vehicle control
AU - Ogitsu, Takeki
AU - Omae, Manabu
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/7/1
Y1 - 2015/7/1
N2 - In this study, a new method was developed to automate vehicles. Numerous vehicle control systems have been realized for electronic steering, driving, and braking. Higher-standard vehicle control systems have increased costs. This study focused on cloud vehicle control using roadside sensors and computers. If a high-standard vehicle control system can be realized by using vehicles with no sensors or computers, this can create a new service model for transport. The key point was to obtain state quantities of vehicles and to maintain vehicle-to-roadside communication. The proposed method obtains state quantities of vehicles with roadside sensors by using the iterative closest point algorithm. The vehicle positions are correlated with communication information. The control quantities of the vehicles are received by roadside computers. Experiments using electric vehicles showed that the proposed method can realize high-standard vehicle control for self-driving vehicles.
AB - In this study, a new method was developed to automate vehicles. Numerous vehicle control systems have been realized for electronic steering, driving, and braking. Higher-standard vehicle control systems have increased costs. This study focused on cloud vehicle control using roadside sensors and computers. If a high-standard vehicle control system can be realized by using vehicles with no sensors or computers, this can create a new service model for transport. The key point was to obtain state quantities of vehicles and to maintain vehicle-to-roadside communication. The proposed method obtains state quantities of vehicles with roadside sensors by using the iterative closest point algorithm. The vehicle positions are correlated with communication information. The control quantities of the vehicles are received by roadside computers. Experiments using electric vehicles showed that the proposed method can realize high-standard vehicle control for self-driving vehicles.
KW - Cloud vehicle control
KW - Guidance control
KW - Intelligent transportation systems
KW - Laser range finder
KW - V-to-R communication
KW - Vehicle recognition
UR - http://www.scopus.com/inward/record.url?scp=84940399216&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84940399216&partnerID=8YFLogxK
U2 - 10.1109/VTCSpring.2015.7146106
DO - 10.1109/VTCSpring.2015.7146106
M3 - Conference contribution
AN - SCOPUS:84940399216
T3 - IEEE Vehicular Technology Conference
BT - 2015 IEEE 81st Vehicular Technology Conference, VTC Spring 2015 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 81st IEEE Vehicular Technology Conference, VTC Spring 2015
Y2 - 11 May 2015 through 14 May 2015
ER -