TY - JOUR
T1 - Seeing Is Believing
T2 - Sharing Real-Time Visual Traffic Information via Vehicular Clouds
AU - Kwak, Daehan
AU - Liu, Ruilin
AU - Kim, Daeyoung
AU - Nath, Badri
AU - Iftode, Liviu
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016
Y1 - 2016
N2 - From today's conventional cars to tomorrow's self-driving cars, advances in technology will enable vehicles to be equipped with more and more-sophisticated sensing devices, such as cameras. As vehicles gain the ability to act as mobile sensors that carry useful traffic information, people and vehicles are sharing sensing data to enhance the driving experience. This paper describes a vehicular cloud service for route planning, where users collaborate to share traffic images by using their vehicles' on-board cameras. We present the architecture of a collaborative traffic image-sharing system called social vehicle navigation, which allows drivers in the vehicular cloud to report and share visual traffic information called NaviTweets. A set of NaviTweets is then filtered, refined, and condensed into a concise, user-friendly snapshot summary of the route of interest, called a traffic digest. These digests can provide more pertinent and reliable information about the road situation and can complement predictions, such as estimated time of arrival, thereby supporting users' route decision making. As proof of concept, this paper presents the system design and a prototype implementation running on the Android smartphone platform, along with its evaluation.
AB - From today's conventional cars to tomorrow's self-driving cars, advances in technology will enable vehicles to be equipped with more and more-sophisticated sensing devices, such as cameras. As vehicles gain the ability to act as mobile sensors that carry useful traffic information, people and vehicles are sharing sensing data to enhance the driving experience. This paper describes a vehicular cloud service for route planning, where users collaborate to share traffic images by using their vehicles' on-board cameras. We present the architecture of a collaborative traffic image-sharing system called social vehicle navigation, which allows drivers in the vehicular cloud to report and share visual traffic information called NaviTweets. A set of NaviTweets is then filtered, refined, and condensed into a concise, user-friendly snapshot summary of the route of interest, called a traffic digest. These digests can provide more pertinent and reliable information about the road situation and can complement predictions, such as estimated time of arrival, thereby supporting users' route decision making. As proof of concept, this paper presents the system design and a prototype implementation running on the Android smartphone platform, along with its evaluation.
KW - Crowdsourcing
KW - navigation systems
KW - route choice/planning
KW - social networks
KW - social sensors
KW - traffic images
KW - vehicular clouds
KW - Vehicular networks
UR - http://www.scopus.com/inward/record.url?scp=85000644027&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2016.2569585
DO - 10.1109/ACCESS.2016.2569585
M3 - Article
AN - SCOPUS:85000644027
SN - 2169-3536
VL - 4
SP - 3617
EP - 3631
JO - IEEE Access
JF - IEEE Access
M1 - 7470581
ER -