TY - GEN
T1 - Human factor evaluation of in-vehicle signal assistance system
AU - Lee, Joyoung
AU - Gutesa, Slobodan
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/6/26
Y1 - 2018/6/26
N2 - This paper assesses the effectiveness of In-Vehicle Signal Assistance (ISA) that can be deployed to intersections in Smart City. Using Signal Phase and Timing (SPaT) data through wireless connectivity under Smart City environment, ISA assists drivers to perform safe and smooth crossings at the next intersection. Employing a Driving Simulator, ten subject drivers are recruited to examine the impact of ISA from the perspective of human drivers. Based on Likert Scale, a questionnaire is designed to conduct experiments to accurately capture the diverse driving behaviors of the subject drivers. Experiment results showed that between 70% and 90% of subject drivers agree that the ISA application is a useful tool for improving the safety and mobility of their driving conditions. It is also discovered that the ISA application enables the drivers to move vehicles faster, by producing travel time savings of as much as 5 seconds per driver, on average. With the observations discovered from the acceleration profile and trajectory data, the ISA application assisted drivers with conducting smooth driving maneuvers and, in turn, improved the safety, mobility, and comfort of drivers when crossing an intersection.
AB - This paper assesses the effectiveness of In-Vehicle Signal Assistance (ISA) that can be deployed to intersections in Smart City. Using Signal Phase and Timing (SPaT) data through wireless connectivity under Smart City environment, ISA assists drivers to perform safe and smooth crossings at the next intersection. Employing a Driving Simulator, ten subject drivers are recruited to examine the impact of ISA from the perspective of human drivers. Based on Likert Scale, a questionnaire is designed to conduct experiments to accurately capture the diverse driving behaviors of the subject drivers. Experiment results showed that between 70% and 90% of subject drivers agree that the ISA application is a useful tool for improving the safety and mobility of their driving conditions. It is also discovered that the ISA application enables the drivers to move vehicles faster, by producing travel time savings of as much as 5 seconds per driver, on average. With the observations discovered from the acceleration profile and trajectory data, the ISA application assisted drivers with conducting smooth driving maneuvers and, in turn, improved the safety, mobility, and comfort of drivers when crossing an intersection.
KW - Connected Vehicle
KW - Driving Simulator
KW - Human Factor
KW - In-Vehicle Signal Assistance
KW - V2I Communications
UR - http://www.scopus.com/inward/record.url?scp=85050215087&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85050215087&partnerID=8YFLogxK
U2 - 10.1109/UIC-ATC.2017.8397580
DO - 10.1109/UIC-ATC.2017.8397580
M3 - Conference contribution
AN - SCOPUS:85050215087
T3 - 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017 - Conference Proceedings
SP - 1
EP - 6
BT - 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017
Y2 - 4 April 2017 through 8 April 2017
ER -