Seeing Is Believing: Sharing Real-Time Visual Traffic Information via Vehicular Clouds
Autor: | Ruilin Liu, Daeyoung Kim, Daehan Kwak, Liviu Iftode, Badri Nath |
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Jazyk: | angličtina |
Rok vydání: | 2016 |
Předmět: |
Vehicular communication systems
social networks General Computer Science Computer science Cloud computing 02 engineering and technology 0202 electrical engineering electronic engineering information engineering General Materials Science Android (operating system) traffic images Vehicular ad hoc network business.industry Estimated time of arrival General Engineering navigation systems 020206 networking & telecommunications social sensors Systems design Crowdsourcing 020201 artificial intelligence & image processing lcsh:Electrical engineering. Electronics. Nuclear engineering route choice/planning business Wireless sensor network lcsh:TK1-9971 Computer network |
Zdroj: | IEEE Access, Vol 4, Pp 3617-3631 (2016) |
ISSN: | 2169-3536 |
Popis: | 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. |
Databáze: | OpenAIRE |
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