Paper Info
Title
Traffic Condition Monitoring Using Weighted Kernel Density For Intelligent Transportation
Abstract
Smart transportation is an application of intelligent system on transportation domain, expected to bring the society environmental and economic advantages. By combining with IoT techniques, the concept is being enhanced and raised to a system level. Numerous data are able to collect and effective analysis technique is needed.Here in this paper, we proposed a framework of employing IoT technique to construct a free time navigation system. The system aims at providing a real-time quantification of traffic conditions and suggests optimal route based on the information retrieved. The system can be basically separated into two major components: (i) the traffic condition estimation module and the (ii) real-time routing algorithm. In the first component, traffic conditions of roads will be estimated based the information collected from sensors installed on vehicles. Based on these location and speed information, the traffic condition can be quantified using a weighted kernel density estimation (WKDE) function. This function is a function of time and provides a real time insight of the overall traffic condition. By combining this information and the topological structure of the road network, a more accurate time consumption on each road can be estimated and hence enable a better routing.
Year
Venue
Field
2015
PROCEEDINGS 2015 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS (INDIN)
Kernel (linear algebra),Advanced Traffic Management System,Navigation system,Floating car data,Real-time computing,Engineering,Intelligent transportation system,Traffic conditions,Kernel density estimation,The Internet
DocType
ISSN
Citations 
Conference
1935-4576
1
PageRank 
References 
Authors
0.35
7
7
Name
Order
Citations
PageRank
Chi Chung Lee110.35
Wah Ching Lee232.80
Haoyuan Cai310.35
Hao Ran Chi4459.32
Chung Kit Wu5188.49
Jan Haase6166.08
Mikael Gidlund752352.95