TY - GEN
T1 - Use cases for rider assistant mobile application evaluation using travelling simulator
AU - Hashimoto, Naohisa
AU - Okuma, Takashi
AU - Miyakoshi, Seiichi
AU - Tomita, Kohji
AU - Matsumoto, Osamu
AU - Smirnov, Alexander
AU - Kashevnik, Alexey
AU - Lashkov, Igor
N1 - Publisher Copyright:
© 2016 FRUCT.
PY - 2017/4/4
Y1 - 2017/4/4
N2 - Today's personal mobility vehicles have been considered as a solution for solving the last/first mile problem of a rider in big cities. It is important to investigate the rider factors, rider behavior, and rider-machine interface while using personal mobility vehicles in order to propose useful and safe personal mobility systems (including vehicles and software for the rider assistance). These factors can be evaluated using a simulator that attains realistic environments. The paper presents use cases for the rider assistant using a personal mobile application and their evaluation using the developed travelling simulator. The mobile application for the rider assistant is generated recommendations for the rider based on detected dangerous situation during the riding to prevent an accident. Dangerous situations detection is based on images analysis of the rider face taken from the front camera of the rider's mobile device mounted in the personal mobility vehicle.
AB - Today's personal mobility vehicles have been considered as a solution for solving the last/first mile problem of a rider in big cities. It is important to investigate the rider factors, rider behavior, and rider-machine interface while using personal mobility vehicles in order to propose useful and safe personal mobility systems (including vehicles and software for the rider assistance). These factors can be evaluated using a simulator that attains realistic environments. The paper presents use cases for the rider assistant using a personal mobile application and their evaluation using the developed travelling simulator. The mobile application for the rider assistant is generated recommendations for the rider based on detected dangerous situation during the riding to prevent an accident. Dangerous situations detection is based on images analysis of the rider face taken from the front camera of the rider's mobile device mounted in the personal mobility vehicle.
UR - http://www.scopus.com/inward/record.url?scp=85018639949&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85018639949&partnerID=8YFLogxK
U2 - 10.23919/FRUCT.2016.7892182
DO - 10.23919/FRUCT.2016.7892182
M3 - Conference contribution
AN - SCOPUS:85018639949
T3 - Conference of Open Innovation Association, FRUCT
SP - 47
EP - 53
BT - Proceedings of the 19th Conference of Open Innovations Association, FRUCT 2016
A2 - Tyutina, Tatiana
A2 - Balandin, Sergey
PB - IEEE Computer Society
T2 - 19th Conference of Open Innovations Association, FRUCT 2016
Y2 - 7 November 2016 through 11 November 2016
ER -